Improving Food Safety Through a One Health Approach: Workshop Summary (2012)

Appendix A

Contributed Manuscripts

A1

EHEC O104:H4 IN GERMANY 2011: LARGE OUTBREAK
OF BLOODY DIARRHEA AND HAEMOLYTIC
URAEMIC SYNDROME BY SHIGA TOXIN—PRODUCING
E. COLI VIA CONTAMINATED FOOD

Reinhard Burger^1,2

In the summer of 2011 Germany experienced one of the largest outbreaks of a food-borne infection caused by enterohaemorrhagic Escherichia coli (EHEC) with the serotype O104:H4. A large number of cases with bloody diarrhea and haemolytic uraemic syndrome (HUS) occurred. Never before was such a high rate of HUS cases observed in an outbreak caused by a food-borne pathogen. The events in Germany caused by EHEC O104:H4 in the summer of 2011 show dramatically how rapidly an infectious agent is able to develop into a major health threat for a whole country. The outbreak caused widespread concern among the population, turning soon into fear. People expecting safe and healthy food felt threatened. It changed the eating habits of the majority of the population, and it had enormous economic consequences, particularly for farmers producing salad ingredients. It resulted in a large number of seriously ill patients and in a substantial number of deaths. The burden of disease and the economic consequences

¹ For the HUS investigation team of the Robert Koch Institute.

² Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany (BurgerR@rki.de).

have made it a tragedy for many. It is important to analyse this outbreak scientifically in order to learn from this unique event and to be prepared for comparable infections in the future. In particular, all the steps regarding detection of cases, diagnostic procedures, identification of vehicle and origin, and infection control measures, all the way to therapy, should be reflected carefully. Usually, even experienced physicians encounter only a few cases of EHEC-induced HUS in adults in their whole career. Therefore, the large number of cases in Germany represents a valuable source of information for future epidemics.

This manuscript summarises the work of the HUS investigation team of the Robert Koch Institute (RKI) and gives an overview of the work done by the colleagues in the Department of Infectious Disease Epidemiology at the RKI (G. Krause, C. Frank, D. Werber, K. Stark, and U. Buchholz), the Department for Infectious Diseases (M. Mielke and A. Fruth), and the RKI-Consultant Laboratory for HUS/EHEC at the University of Münster (H. Karch). Many additional colleagues were involved.

Epidemic Profile and Development of the Outbreak

The extent of the outbreak becomes apparent by comparison with the average annual numbers of EHEC cases or HUS in Germany. In previous years about 1,000 patients per year were identified, with a median age of about 5 years. Of these patients about 70 per year developed HUS, with a median age of about 2 years (Frank et al., 2011a). In the outbreak from May to September 2011, approximately 3,000 EHEC cases were observed with a median age of 46 years, 58 percent of those patients were female, and 18 deaths were observed among the EHEC patients (0.6 percent). An additional 855 EHEC patients who developed HUS were identified (Frank et al., 2011b). This represents more than 20 percent of the total number of patients (3,842). The large majority of these patients were adults, the average age was 42 years, 68 percent of the HUS cases were female, and 35 deaths were observed among the HUS patients (4.1 percent). The total death toll was 53 patients (Figure A1-1).

Analysis of the incidence of HUS by the likely county of infection revealed that northern Germany was mainly affected. The same is true for cases with travel history; also for these patients the county of residence at the time of infection was northern Germany. Most cases were observed in the states of Schleswig-Holstein, Mecklenburg-Western Pomerania, Hamburg, Bremen, and Lower Saxony. Later in the epidemic, cases were found in all of the 16 German states. The incidence in the five northern German states varied from 1.8 to 10 cases per 100,000 persons. All other states had incidence rates with less than 1 case per 100,000 persons (Frank et al., 2011b; Wadl et al., 2011).

A substantial number of EHEC or HUS cases occurred also internationally during this time, particularly in the European Union, but also a few cases in the United States and Canada. Particularly affected was Sweden with 35 EHEC

FIGURE A1-1 Total number of EHEC and HUS cases and associated deaths during the outbreak of EHEC O104:H4 in summer 2011 in Germany and comparison to an average year.

and 18 HUS cases including one fatality, Denmark with 15 EHEC and 10 HUS cases, and France with 10 EHEC and 8 HUS cases. Single cases were found in 12 additional European countries. In the United States 2 EHEC and 4 HUS cases were identified with one fatality, and Canada had a single EHEC case. An epidemiological analysis revealed that—with two exceptions—all cases in this outbreak of EHEC or HUS found internationally were directly or indirectly associated with a visit to Germany during the weeks of the outbreak. Most of these patients visited northern Germany for a shorter or longer period of time during the peak of the outbreak.

The RKI was notified about the outbreak by a phone call from the local health authority of the state of Hamburg on May 19, 2011. Immediately (i.e., the next day), the RKI sent a substantial team of experts to Hamburg in support of the local colleagues. The subsequent epidemiological analysis revealed in retrospect that the outbreak had in fact started at the beginning of May and reached the peak of cases on May 22, 2011 (Figure A1-2). Thus, there was an obvious and substantial notification delay (Altmann et al., 2011). Up to the moment of notifying the RKI, a large proportion of the infections had already occurred. After May 22 both the reported number of EHEC gastroenteritis and the number of HUS cases decreased (Wadl et al., 2011).

The team of epidemiological specialists sent to Hamburg started right away with initial explorative interviews. The team size was enlarged in the next days

FIGURE A1-2 Epidemiological curve of EHEC (gray) and HUS cases (dark) and overview of epidemiological studies performed by the Robert Koch Institute for identification of sprouts as the vehicle of transmission.

SOURCE: Robert Koch Institute.

(up to 15 members), and a substantial number of case-control studies, additional explorative interviews, and cohort studies were started. As early as May 21 (i.e., 2 days after the RKI was notified), the first qualitative evidence for the role of vegetables was obtained. Raw milk products or products from raw meat, which frequently represent a source of infections with EHEC, had already been ruled out as the origin of infection in this outbreak. On May 22 the corresponding information was submitted to the European Early Warning and Response System and to the World Health Organization. Local public health authorities were warned, and initial interviews were given to the German press. During the next few days, information was provided on the website and in a series of press conferences and interviews. On May 25 (i.e., 5 days after the outbreak), the pathogen was identified from patient samples as EHEC O104:H4 by the RKI-Consulting Laboratory for HUS in Münster and the National Reference Centre laboratory for bacterial enteric pathogens at the RKI (Buchholz et al., 2011).

After a number of telephone conferences, the RKI together with the Federal Institute for Risk Assessment and the Federal Office of Consumer Protection

and Food Safety conducted a press conference advising on food consumption. Advice was given not to consume raw tomatoes, cucumbers, and salad in northern Germany. This recommendation was based on the increased risk of illness after consumption of these raw salads in northern Germany. Unfortunately, the majority of the press reported this advice as warning against salad from northern Germany.

Once the magnitude of the outbreak became apparent, the RKI immediately established a website providing all details about the infectious agent, updated as they developed, both for the medical specialists and microbiological laboratories in Germany and abroad and for the general public. Data sheets on the infectious agent and frequently asked questions, sometimes updated several times a day, proved to be an important source of information.

After mid-June 2011 only single cases of HUS occurred. On July 26 the RKI declared in a press conference the end of the outbreak because no new cases clearly associated with the outbreak had been reported for 3 consecutive weeks since the last newly reported illness on July 4.

Identification of the Infection Vehicle

In addition to the explorative interviews and case-control studies, cohort studies in disease clusters proved to be particularly helpful. Beginning on June 1, more than 30 cohorts were investigated in order to identify the vehicle of infections and to identify further cases. Particularly useful were cohort studies of travel groups that included international visitors or tourist groups from abroad. Here a close cooperation with foreign health authorities was instrumental. For a number of travel groups the length of stay, the particular location, and food consumption could be reconstructed in detail. Also, cluster analysis of patients associated with food consumption in different restaurant-associated outbreaks provided information. An analysis of billing data of guests at an affected canteen provided further data. In these studies a detailed investigation was performed using ordering information and additional details documenting the consumption as revealed by the corresponding bills. The most substantial evidence regarding the vehicle of infection was obtained by a so-called recipe-based restaurant cohort study ( Buchholz et al., 2011).

Sprouts as the Responsible Vehicle of Infection

In the course of the epidemiological analysis it became obvious that patient memory is not a reliable source of information. This proved to be particularly true because in these EHEC/HUS patients not only symptoms of gastrointestinal infection and impaired kidney function were observed but also major neurological symptoms, preventing reliable interviews. Therefore, the recipe-based restaurant cohort study was designed to obtain information independent of a functioning patient memory (Figure A1-3).

FIGURE A1-3 Recipe-based restaurant cohort study of the Robert Koch Institute reveals risk for infection associated with the consumption of sprouts.

SOURCE: Taken from Buchholz et al., NEJM, 365, 1763 (2011).

Ten cohorts with a total of 168 guests of a given restaurant in the city of Lübeck in Schleswig-Holstein were identified. All persons had dinner at the same restaurant between May 12 and 16. Eighteen percent of the guests consuming food at this restaurant showed bloody diarrhea or EHEC/HUS within 14 days (31 persons). All persons were questioned about which meals they ordered, using photos of the dishes as a reminder. Booking details and billing documents were utilized. Using these consumption data from the individual guests, the chef of the restaurant was interviewed about the detailed ingredients of each dish ordered by the guests. This included not only the major ingredients of each dish itself but also elements used for decoration of the dish or of the salad served separately. This approach provided reliable information about which food ingredients each guest had actually ordered and eaten. This interview technique and analysis had the major advantage that it was no longer necessary to depend on the memory of the guests to find out what they had eaten. Additional verification was obtained through photos taken at the table by a number of groups. These photos confirmed the details given for the nature of the ordered dish and its contents.

In univariate analysis the relative risk of disease was 14.2 times higher for persons eating sprouts compared to that of persons not eating sprouts (Buchholz et al., 2011). All 31 patients with EHEC/HUS had consumed sprouts. None of the guests who did not consume sprouts became ill. Based on these cohort studies, in a joint press conference of the RKI with the food safety authorities on June 10 the public announcement was made that sprouts were the vehicle of infection. The

earlier warning against the consumption of salad was now focused on a warning against consumption of the salad ingredient sprouts.

Origin of Bacterial Contamination of the Sprouts

The more than 40 clusters within this outbreak were analyzed for a common denominator. The federal authorities responsible for food safety in Germany (the Federal Institute for Risk Assessment and the Federal Office of Consumer Protection and Food Safety) performed an intensive forward-backward tracing of the food supply chain of the various cluster locations (Figure A1-4). Through one or several distributors and intermediates, all clusters turned out to be connected to a specific food enterprise producing sprouts commercially. All infections within this outbreak in the state of Lower Saxony had in common that originally the supply of sprouts came from this single food enterprise.

Two clusters of infection independent of the outbreak in Lower Saxony provided information on the origin of the sprout contamination (Appel et al., 2011). Both clusters had definitely no connection to the sprout producer in Lower Saxony. One cluster consisted of so-called self-sprouters (i.e., consumers who grow their

FIGURE A1-4 Trading network reveals linkage of 41 identified outbreak clusters. Supply chain of contaminated sprouts leads to one single sprout producer farm in Lower Saxony.

SOURCE: Modified from Buchholz et al., NEJM, 365, 1763 (2011).

own sprouts at home from seeds provided by commercial suppliers). The second source of information was a small outbreak comprising 15 cases in the area of Bordeaux in France in mid-June. Detailed and labor-intensive tracing of the delivery channels revealed that the only common feature of the seeds used for growing sprouts in the food enterprises in Lower Saxony, in Bordeaux, and in the private households with the home-grown sprouts was a given lot of fenugreek seeds originating from Egypt. Fenugreek seeds (Trigonella foenum-graecum) are frequently used for the production of sprouts. The seeds are also used in many other food products (e.g., spices, cheese, and even tea) because of their very aromatic taste and intensive smell. The seeds are small (4-5 mm) and have a peanut-like colour.

Through a number of intermediates located in different countries this seed lot had been delivered to these three outbreak locations. No other common ingredient used for the production of sprouts was identified. This was clear evidence that contaminated seeds used for sprout growing were responsible for the outbreak (Appel et al., 2011). By nature, the epidemiological evidence is indirect or circumstantial but it explained the distribution of infections. The corresponding lot of fenugreek seeds was removed from the market. It is difficult to verify how complete this removal was.

“Stealth Food”

When the affected patients were interviewed initially during the first weeks of the outbreak, it became obvious that people do not remember in detail what they ate 1 or 2 weeks ago. Only in retrospect, after the second or third interview together with reports in the press, did they realize and remember that their dishes had in fact contained sprouts. Similar phenomena had been observed internationally in other outbreaks. In 2008, jalapeno chili peppers were contaminated with Salmonella Saintpaul in the United States. Chili peppers are used as an ingredient in tomato sauce-like salsa. The consumers were not aware that one of the spicy ingredients was chili peppers and, when interviewed, denied consumption of this food item, thereby delaying the identification of the vehicle. The identification of sprouts as a source in Germany within less than 3 weeks was quite rapid. The identification of the chili peppers took about 7 weeks. In another outbreak in 1996 with radish sprouts causing an outbreak of EHEC O157 in Japan, 7 weeks were required for the detection of the outbreak and 4 weeks to identify its source.

Microbiological Characterization of EHEC O104:H4

Once the outbreak had been recognized, EHEC O104:H4 was rapidly isolated from stool specimens of affected patients within a few days (Figure A1-5) (Askar et al., 2011, Bielaszewska et al., 2011). This is a rare serotype that had not been described previously in animals. As a rule, faecal contamination by ruminants is responsible for EHEC infections through vegetables or through

FIGURE A1-5 Electron micrograph of EHEC O104:H4.

SOURCE: Laue, Robert Koch Institute.

food products derived from animals (milk, meat). The usual EHEC strains (e.g., EHEC O157) are found in faeces of ruminants. EHEC O104:H4 has only rarely been identified previously in human beings (in a total of seven patients). A closely related EHEC strain, HUSEC041, was identified in 2001 by the laboratory of Karch at the University of Münster, Germany. Later, a few cases were identified in Korea in 2006, in Georgia in 2009, and in Finland in 2010.

A detailed microbiological characterization of EHEC O104:H4 was performed at the National Reference Centre for Gastrointestinal Bacteria at the RKI and the RKI-Consultant Laboratory of Karch in Münster (Bielaszewska et al., 2011; Brzuskiewicz et al., 2011). From the virulence markers, the outbreak strain was negative for Shiga toxin 1 and positive for Shiga toxin 2 (variant vtx2a of Shiga toxin 2). It was negative for Intimin (eae) and also negative for enterohaemolysin (hly). Macrorestriction analysis (pulsed-field gel electrophoresis) with a number of selected isolates obtained from various areas of Germany showed the same pattern, indicating early that the corresponding patients were all affected by one and the same outbreak event.

Surprisingly, the outbreak strain showed virulence characteristics of enteroaggregative E. coli (EAEC). It had the typical EAEC virulence plasmid with adhesion fimbriae type AAF/I. This virulence plasmid has not been described previously in EHEC isolates. All other previously identified EAEC or Shiga toxin—producing E. coli (STEC)/EAEC O104:H4 had AAF/III fimbriae. Subsequent sequencing revealed strong homology to an enteroaggregative E. coli (EAEC 55989). Obviously, the outbreak strain EHEC O104:H4 represents a virulence combination of two different pathogens. The origin of this outbreak strain with the characteristics of two different pathogens remains unclear for the time being. It is unclear whether the new EHEC O104:H4 pathotype had developed from two separate ancestors by horizontal gene transfer, leading to the observed acquisition of virulence factors (Figure A1-6) (Brzuskiewicz et al., 2011; Mellmann et al., 2011; Rasko et al., 2011). A number of mobile genetic elements can transfer traits in E. coli like the Stx-bacteriophage found in EHEC strains. Alternatively, an evolutionary model is discussed, postulating a common progenitor of EAEC

FIGURE A1-6 Putative origin of the EHEC outbreak strain as a combination of virulence traits derived from two different ancestors.

SOURCE: Brzuszkiewicz et al. (2011).

55989 and EHEC O104:H5 developing into two lines, each losing or acquiring virulence factors. The second explanation is favoured by the group from Karch, University of Münster.

The continuously updated EHEC datasheet on the RKI website summarized all known characteristics of the pathogen and suggested the proper microbiological diagnostic procedures.

ESBL Resistance Phenotype

The microbiological characterization revealed a resistance unusual for intestinal E. coli. The outbreak strain had an extended-spectrum β-lactamase (ESBL). This is an unusual property of intestinal E. coli. This resistance phenotype allowed efficient diagnostics of the outbreak strain. It permitted the use of the corresponding selective media for a targeted search in clinical samples, facilitating a rapid diagnosis. Colonies on an ESBL-agar plate were further characterized with multiplex polymerase chain reaction screening for genes of Shiga toxin 1 and 2 and Intimin.

Absence of Direct Microbiological Evidence for Contamination of Seeds with EHEC O104:H4

The identification of seeds as the source and sprouts as the vehicle of infection relied on sophisticated and elegant epidemiological analysis (i.e., indirect evidence). Direct microbiological evidence has not been obtained so far (Aurass et al., 2011). Intensive bacteriological screening of the fenugreek sprouts and seeds was performed. A large number of samples were also taken at the production site of the sprouts, including the water supply or waste water. All attempts to identify the outbreak strain on seeds or sprouts or in the samples obtained at the production site failed. Sampling sprouts in households with EHEC cases was successful in one or two cases. However, these results were more than questionable. One positive result was obtained from a single box of sprouts originating from the incriminated producer. However, it had already been opened in a household with EHEC cases and might simply have been contaminated by the handling. In another example the outbreak strain was identified in salad samples found in a trashcan days after disposal. Also here, the causal connection is unclear.

One reason for the failure to identify the outbreak strain through bacteriological screening may be the enormous size of the incriminated fenugreek seed lot. The lot size was around 15,000 kg. If only a minor part of this lot had indeed been contaminated, searching for contaminated seeds would resemble the search for a needle in a haystack. In addition, on the same day, the sprout-producing enterprise received another lot of seeds from the same seed distributor. The incriminated lot had been distributed to 70 different companies, 54 of them in Germany and 16 of them in 11 European countries (Appel et al., 2011). How-

ever, despite the two additional independent clusters (home-grown sprouts and the cluster in France; see above), no obvious other outbreaks were recognized. Despite all efforts to remove the incriminated lot from the supply chain, it is difficult to estimate how effective and complete this removal has been. Especially in private households, growing sprouts from small aliquots of seeds could lead to new infections. It is known that E. coli can survive on dried seeds for longer periods of time, potentially for years.

Incubation Time and Shedding Time

Detailed analysis revealed a median incubation time of 8 days. The maximum was 18 days. Seventy-five percent of the patients developed clinical symptoms after 10 days. Some of the patients showed a shedding of the pathogen for an extensive period. A few patients shed the pathogens for up to 8 months. It remains to be determined whether shedding might even be longer and whether a carrier status may develop. For enteroaggregative E. coli this extensive shedding period is not unexpected. It is known that aggregative bacteria adhere more strongly and remain in the gastrointestinal tract for longer periods of time. A close collaboration with the local health authorities proved to be important in the analysis of this outbreak (e.g., for these shedding studies) (Robert Koch Institute, 2011).

Secondary Infections

Even after the end of the outbreak had been announced, recommendations were made to enforce the standard hygiene rules, regarding both personal and hand hygiene and in particular kitchen and food hygiene. This included the recommendation to always clean kitchen utensils carefully when preparing food intended for raw consumption. A small number of secondary infections were observed, predominantly consisting of household members of patients. Therefore, stringent adherence to hygienic practices was strongly suggested in those households where EHEC patients or persons with diarrhea were present.

Single nosocomial infections occurred in hospitals (coloscopy). Transmission also occurred through the preparation or distribution of food. Also several laboratory infections were found. Therefore, raised awareness of the risk of infection was also emphasized in public announcements during the months after the official end of the outbreak.

Communication

The RKI made great efforts to inform the medical experts and the public health service and the professional societies (clinical and microbiological) about details of the outbreak in a very timely fashion. During the outbreak, at least daily updates were distributed by e-mail. The Internet proved to be the most important

tool for distribution of information. Usually visits to the RKI homepage result in 4 to 6 million page uses per month. During the outbreak months, May and June 2011, the numbers increased to 16.5 and 17.9 million, respectively. The information provided also included outbreak case definition, forms concerned with sample reporting, diagnostic procedures, information on hygienic measures, etc.

When a whole country is concerned about the safety of its food, the risk communication is important. It proved be helpful to clearly and reliably state the current knowledge and the known risks and their prevention. Also lack of knowledge or uncertainty should be stated clearly, as well as the point in time when new information might be expected. This is important in order to maintain public confidence in recommendations. Farmers requested information because a substantial number of farms suffered economically and were in danger of going out of business.

Conclusion

This outbreak of EHEC infections was the largest recorded outbreak of a bacterial infection observed in Germany in many decades. The enormous rate of HUS cases makes it the largest outbreak of HUS worldwide. It revealed how rapidly a food-borne pathogen can spread and cause serious illness and death. It demonstrates the importance of proper surveillance systems in order to detect an outbreak early and of a rapid reporting system in notifying the corresponding health authorities, in this case the RKI in Germany. According to the specifications of the German Infection Protection Act, a rapid report by the physician or the diagnostic laboratory to the local health authorities is required. In retrospect, between the onset of the disease, the visit to the doctor or hospital, diagnosis, and the report to the local health authority and subsequently to the state authorities and finally to the RKI, a substantial period of time passed, varying from a few days up to several weeks. Measures were taken to improve reporting and to prevent the notification delay. In the analysis of outbreak clusters a close cooperation of health authorities and food safety authorities and a rapid exchange of information is necessary.

The origin of the outbreak strain and how the seeds were contaminated remain unclear. It also remains to be determined whether EHEC O104:H4 will have a reservoir, in human beings, in animals, or in the environment. There is no evidence today that EHEC O104:H4 has become endemic anywhere in humans, animals, or in the environment in Germany. After the sprouts had been identified as the vehicle of this outbreak and after the sprout distribution ended, no further outbreak clusters were identified to be associated with the consumption of sprouts. It is unclear how frequently EHEC is present on sprouts, which are often consumed raw and represent a particularly vulnerable food for bacterial contamination. A rapid and sensitive EHEC diagnostic should also be available in routine diagnostic laboratories in order to identify outbreak events early and

reliably. Detailed subtyping should predominantly be performed in specialized laboratories, also in such an outbreak situation. It seems appropriate to observe these aspects or questions also in the future.

The outbreak had enormous consequences, not only for the patients affected but also economically because of strongly reduced trade in salads and salad ingredients. Spanish cucumbers had been discussed by a local health authority as a potential source of the pathogen. This assumption was not confirmed by laboratory analysis, and attempts to show a connection to the outbreak strain failed; however, it affected the sale and led to a major drop in the consumption and export of Spanish vegetables. Farmers in a number of vegetable-exporting countries were in turn compensated by the European Union in the amount of 220 million Euros for this loss in income.

In summary, the events in Germany during the summer of 2011 revealed the importance of functioning public health institutions, both at the county and state level and at the federal level.

A final detailed report of the EHEC O104:H4 outbreak in Germany is available through the RKI website (http://edoc.rki.de/documents/rki_ab/reQHS31jDrGxc/PDF/23NXL3JomOyAA.pdf) in an English version.

Declaration of Interest

The author declares no conflict of interest and has received no payment in preparation of this manuscript.

References

Altmann, M., A. Spode, D. Altmann, M. Wadl, J. Benzler, T. Eckmanns, G. Krause, and M. an der Heiden. 2011. Timeliness of surveillance during outbreak of Shiga toxin—producing Escherichia coli, Germany. Emerging Infectious Diseases 17:1906-1909.

Appel, B., G. F. Böl, M. Greiner, M. Lahrssen-Wiederholt, and A. Hensel A (Hrsg.). 2011. EHEC-Ausbruch 2011—Aufklärung des Ausbruchs entlang der Lebensmittelkette. Berlin: Bundes-institut für Risikobewertung (BfR-Wissenschaft 04/2011). http://www.bfr.bund.de/cm/350/ehec-ausbruch-2011-aufklaerung-des-ausbruchs-entlang-der-lebensmittelkette.pdf.

Askar, M., M. S. Faber, C. Frank, H. Bernard, A. Gilsdorf, A. Fruth, R. Prager, M. Höhle, T. Suess, M. Wadl, G. Krause, K. Stark, and D. Werber. 2011. Update on the ongoing outbreak of haemolytic uraemic syndrome due to Shiga toxin-producing Escherichia coli (STEC) serotype O104, Germany, May 2011. Eurosurveillance 16(22):pii=19883.

Aurass, P., R. Prager, and A. Flieger. 2011. EHEC/EAEC O104:H4 strain linked with the 2011 German outbreak of haemolytic uremic syndrome enters into the viable but non-culturable state in response to various stresses and resuscitates upon stress relief. Environmental Microbiology 13:3139-3148.

Bielaszewska, M., A. Mellmann, W. Zhang, R. Köck, A. Fruth, A. Bauwens, G. Peters, and H. Karch. 2011. Characterisation of the Escherichia coli strain associated with an outbreak of haemolytic uraemic syndrome in Germany, 2011: A microbiological study. Lancet Infectious Diseases 11:671-676.

Brzuszkiewicz, E., A. Thürmer, J. Schuldes, A. Leimbach, H. Liesegang, F. D. Meyer, J. Boelter, H. Petersen, G. Gottschalk, and R. Daniel. 2011. Genome sequence analyses of two isolates from the recent Escherichia coli outbreak in Germany reveal the emergence of a new pathotype: Entero-aggregative-haemorrhagic Escherichia coli (EAHEC). Archives of Microbiology 193:883-891.

Buchholz, U., H. Bernard, D. Werber, M. M. Böhmer, C. Remschmidt, H. Wilking, Y. Deleré, M. an der Heiden, C. Adlhoch, J. Dreesman, J. Ehlers, S. Ethelberg, M. Faber, C. Frank, G. Fricke, M. Greiner, M. Höhle, S. Ivarsson, U. Jark, M. Kirchner, J. Koch, G. Krause, P. Luber, B. Rosner, K. Stark, M. Kühne, and RKI HUS investigation team (M. Abu Sin, K. Alpers, D. Altmann, M. Altmann, K. Arends, M. Askar, K. Atzpodien, S. Behnke, J. Benzler, A. Bergholz, J. Bielecke, B. Brodhun, R. Burger, W. Cai, H. Claus, C. Cyberski, M. Dehnert, S. Dudareva, T. Gunsenheimer-Bartmeyer, K. Haar, W. Haas, O. Hamouda, B. Hauer, W. Hellenbrand, J. Hermes, K. Köpke, K. Krügermann, G. Laude, M. H. Lee, I. Liss, M. Luchtenberg, M. Marx, D. Meyer, M. Mielke, A. Milde-Busch, K. Prahm, U. Preuß, S. Reiter, A. Reuß, U. Rexroth, M. Richter, T. Rieck, K. Rothe, A. Sailer, C. Santos-Hövener, L. Schaade, S. Schink, D. Schmidt, C. Schoene, I. Schöneberg, M. Schuster, F. Schwarz, B. Schweickert, P. Stöcker, T. Suess, A. Takla, E. Tietze, B. Ultsch, M. Ung-Zu Kang, E. Velasco, M. Wadl, D. Walter, B. Weiß, R. Zimmermann, W. Zhang, and J. Zunk). 2011. German outbreak of Escherichia coli O104:H4 associated with sprouts. New England Journal of Medicine 365:1763-1770.

Frank, C., M. S. Faber, M. Askar, H. Bernard, A. Fruth, A. Gilsdorf, M. Höhle, H. Karch, G. Krause, R. Prager, A. Spode, K. Stark, and D. Werber, on behalf of the HUS investigation team. 2011a. Large and ongoing outbreak of haemolytic uraemic syndrome, Germany, May 2011. Eurosurveillance 16(22):pii=19878.

Frank, C., D. Werber, J. P. Cramer, M. Askar, M. Faber, M. an der Heiden, H. Bernard, A. Fruth, R. Prager, A. Spode, M. Wadl, A. Zoufaly, S. Jordan, K. Stark, and G. Krause, for the HUS Investiation Team (M. Abu Sin, C. Adlhoch, K. Alpers, D. Altmann, M. Altmann, K. Erends, K. Atzpodien, S. Behnke, J. Benzler, A. Bergholz, J. Bielecke, M. Böhmer, B. Brodhun, U. Buchholz, R. Burger, W. Cai, H. Claus, M. Christner, C. Cyberski, M. Dehner, Y. Deleré, S. Dudareva, T. Eckmanns, W. Espelage, G. Falkenhorst, L. Fiebig, K. Fraedrich, A. Gilsdorf, B. Greutélaers, B. Gunsenheimer-Bartmeyer, K. Haar, W. Haas, O. Hamouda, B. Hauer, W. Hellenbrand, J. Hermes, M. Höhle, M.J. Kemper, J. Koch, K. Köpke, K. Krügermann, G. Laude, M.-H. Lee, I. Liss, A. W. Lohse, M. Luchtenberg, M. Marx, D. Meyer, M. Mielke, A. Milde-Busch, I. Mücke, L. Müller, M. Nachtnebel, J. Neifer, S. Nielsen, I. Noll, R. Offergeld, Y. Pfeifer, R. Pohland, K. Prahm, U. Preuß, S. Reiter, C. Remschmidt, A. Reuß, U. Rexroth, M. Richter, T. Rieck, H. Rohde, B. Rosner, A. Sailer, C. Santos-Hövener, L. Schaade, S. Schink, S. Schmiedel, D. Schmidt, C. Schoene, I. Schöneberg, M. Schuster, F. Schwarz, B. Schweickert, P. Stöcker, T. Süß, A. Takla, E. Tietze, B. Ultsch, M. U.-Z. Kang, E. Velasco, D. Walter, B. Weiß, H. Wilking, R. Zimmermann, W. Zhang, J. Zunk). 2011b. Epidemic profile of Shiga-toxin-producing Escherichia coli O104:H4 outbreak in Germany. New England Journal of Medicine365:1771-1780.

Mellmann, A., D. Harmsen, C. A. Cummings, E. B. Zentz, S. R. Leopold, A. Rico, K Prior, R. Szczepanowski, Y. Ji, W. Zhang, S. R. McLaughlin, J. K. Henkhaus, B. Leopold, M. Bielaszewska, R. Prager, P. M. Brzoska, R. L. Moore, S. Guenther, J. M. Rothberg, and H. Karch. 2011. Prospective genomic characterization of the German enterohemorrhagic Escherichia coli O104:H4 outbreak by rapid next generation sequencing technology. PLoS ONE 6:e22751, doi:10.1371/ journal.pone.0022751.

Rasko, D. A., D. R. Webster, J. W. Sahl, A. Bashir, N. Boisen, F. Scheutz, E. E. Paxinos, R. Sebra, C. S. Chin, D. Iliopoulos, A. Klammer, P. Peluso, L. Lee, A. O. Kislyuk, J. Bullard, A. Kasarskis, S. Wang, J. Eid, D. Rank, J. C. Redman, S. R. Steyert, J. Frimodt-Moller, C. Struve, A. Petersen, K. A. Krogfelt, J. P. Nataro, E. E. Schadt, and M. K. Waldor. 2011. Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. New England Journal of Medicine 365:709-717.

Robert Koch Institute. 2011. Report: Final presentation and evaluation of epidemiological findings in the EHEC O104:H4 outbreak, Germany 2011. Berlin: Robert Koch Institute. http://www.rki.de/EN/Home/EHEC_final_report.pdf?__blob=publicationFile (accessed June 26, 2012).

Wadl, M., T. Rieck, M. Nachtnebel, B. Greutélaers, M. an der Heiden, D. Altmann, W. Hellenbrand, M. Faber, C. Frank, B. Schweickert, G. Krause, J. Benzler, and T. Eckmanns, on behalf of the HUS Surveillance and Laboratory Team. 2011. Enhanced surveillance during a large outbreak of bloody diarrhoea and haemolytic uraemic syndrome caused by Shiga toxin/verotoxin-producing Escherichia coli in Germany, May to June 2011. Eurosurveillance 16(22):pii=19893.

A2

ONE HEALTH AND HOTSPOTS OF FOOD-BORNE EIDS

C. Zambrana-Torrelio, K. A. Murray, and P. Daszak³

Summary

In this section, we focus on a One Health approach to food-borne emerging infectious diseases (EIDs), their causes, global patterns, and the drivers of their emergence. First, we review two case studies that show the complexity of food-borne pathogen emergence across the One Health domain. Second, we examine the composition of food-borne diseases with respect to their causal agents (pathogen type), their association with pathogens of zoonotic origin, and their apparent disassociation with pathogens that show drug resistance. Third, we analyze the socioeconomic, environmental, and ecological drivers of food-borne EID events. Finally, we use published, spatially explicit information on the drivers of disease emergence to produce a preliminary “hotspot” map that reveals the epicentres, or hotspots, of food-borne EID events globally.

Introduction

One Health’s focus on the intersection of human, domestic animal, and environmental health is ideally suited to managing emerging zoonoses. However, the patterns of emergence are complex and poorly understood and for food-borne infections may involve multiple pathways. Food-borne infections can include directly transmitted or vector-borne diseases, for example, Rift Valley fever (Arzt et al., 2010). Single strains of drug-resistant microbes can infect livestock, wildlife, and humans (e.g., E. coli O157:H7) (Hughes et al., 2009; Nielsen et al., 2004; Rahn et al., 1997). Finally, viral pathogens that originate in wildlife may be driven to emerge by the intensification of livestock production (Pulliam et al., 2011) or by contamination of bush meat (Wolfe et al., 2005) or other food sources

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³ EcoHealth Alliance, 460 West 34th Street, New York, NY 10001, USA.

(Khan et al., 2011). Our ability to predict the emergence of food-borne infections is hampered by this complexity. However, recent efforts to analyse disease emergence (Jones et al., 2008; Taylor et al., 2001) have provided a strategy that can be adapted to analyzing the origins of food-borne infections.

Following our first efforts to predict global patterns of disease emergence (Jones et al., 2008), we have continued to compile data on human EID events and their drivers under the aegis of the U.S. Agency for International Development—funded Emerging Pandemic Threats PREDICT project (Daszak, 2011). In the updated database, when the EID events are classified according to their disease transmission modes (Figure A2-1), we find that food-borne pathogens are responsible for 14.9 percent of known EIDs.

In this section, we focus on food-borne EIDs, their causes, global patterns, and the drivers of their emergence. First, we review two case studies that show

FIGURE A2-1 Proportion of EID events categorized by transmission mode.

the complexity of food-borne pathogen emergence across the One Health domain. Second, we examine the composition of food-borne diseases with respect to their causal agents (pathogen type), their association with pathogens of zoonotic origin, and their apparent disassociation with pathogens that show drug resistance. Third, we analyze the socioeconomic, environmental, and ecological drivers of food-borne EID events. Finally, we use published, spatially explicit information on the drivers of disease emergence to produce a preliminary “hotspot” map that reveals the epicentres, or hotspots, of food-borne EID events globally.

Food-Borne, Wildlife-Origin Pathogens: Two Case Studies

Nipah virus (NiV) is a paramyxovirus that first emerged in Malaysia in 1999, causing encephalitis with a 40 percent case fatality rate in humans (Chua et al., 2000). The virus originated in fruit bats of the genus Pteropus but was first transmitted to domestic pigs, which amplified the virus via a rapidly spreading respiratory infection. Subsequent transmission to people occurred via droplets or fomites contaminated with pig saliva. The initial spillover of NiV seems to have occurred when fruit bats fed on mango and other fruit trees planted next to pigsties at the index farm as a source of additional income and to increase shade. The question remained: Why did it suddenly emerge in this pig farm and not in pig farms 20 years earlier or 20 years later?

To answer this question we analyzed pig production and the age structure of NiV dynamics within the index farm population (Pulliam et al., 2011). We produced a mathematical model, parameterized with detailed data from the index farms and other similar farms still in existence in Malaysia today. This model allowed us to re-create the conditions of the farm when NiV first emerged and to test hypotheses on the drivers of its emergence. Our analyses suggest that repeated introduction of NiV from bats changed infection dynamics in pigs. Initial viral introduction produced an epizootic that drove itself to extinction within 1 to 2 months. Subsequent introduction into a now partially immune population, coupled with the gradual loss of maternal antibodies in pigs born to sows infected in the initial outbreak, led to ideal conditions for pathogen persistence and a prolonged window of spillover to people and regional spread as infected pigs were sold. The structured, compartmentalized nature of the index farm was critical to the emergence of NiV and was a product of agricultural intensification.

A similar scenario surrounds the emergence of highly pathogenic influenza A/H5N1. This virus is able to infect wild waterbirds, domestic poultry, and humans, and its emergence is linked to both intensive production of poultry and the patterns of rice farming within Southeast Asia. When rice is double-cropped, it attracts ducks throughout the year and allows greater potential for new strains of influenza to cross over into pigs and for subsequent crossover of those strains (Gilbert et al., 2008). Analysis of the patterns of double-cropping in Southeast Asia shows that it is possible to predict the risk of its presence throughout

the region based on the type of agricultural system (Gilbert et al., 2008). Poultry production in this region includes large intensive and small “backyard” farms, all connected via trade routes into markets and through the supply of breeding stock and their contact with wild birds. We have used a similar modeling approach for A/H5N1 to examine how farm size and connectivity matter as risk factors for the emergence of avian influenza. Our modeling shows that both factors interact to produce specific conditions conducive to outbreaks. When the vast majority of farms are of small size, outbreaks occur more frequently and last longer, but they involve few individual birds and therefore have a lower risk of infecting people. When farms are poorly connected these outbreaks die out because of stochastic factors. When large intensive farms predominate, outbreaks are very few in number, but their duration is relatively short because so many birds die in such a short space of time that the cause is rapidly recognized and the farm culled. The peak in duration and intensity of outbreaks occurs when there is a mixture of intensive and backyard farming. These are the conditions that occur most commonly in Southeast Asia because of the rapid growth of some economies and efforts to intensify poultry production.

Causes, Patterns, and Drivers of Food-Borne EIDs

How important are food-borne infections in the context of global disease emergence events? Going back to Figure A2-1, approximately 15 percent of human EID events are associated with food-borne transmission pathways. With 475 EID events in the updated database, this translates to 71 separate food-borne EIDs, at an average emergence rate of just under one completely new, previously unknown EID event per year reported globally.

When broken down by causal pathogen type (Figure A2-2), food-borne EIDs are usually bacterial in origin, with smaller proportions of protozoan and helminth-driven diseases. While bacteria are also the major causes of EIDs associated with the contaminated environment and fomites, food-borne EIDs are generally more common and therefore account for the highest number of EIDs of bacterial origin (50) among all of the transmission modes. Hence, when bacteria are the causal agent implicated in EID events, they are more likely to be food-borne than of any other transmission mode. In contrast to the other transmission mode groups, food-borne EIDs are very rarely viral, accounting for only one (1.4 percent) food-borne EID (hepatitis A) compared to ~20 to 45 percent (average 30.9 percent) in the other groups. However, many viral pathogens (e.g., NiV and H5N1) are considered simply zoonotic because the role of food-borne transmission is either less well known or less well understood.

Our analyses suggest that the vast majority of food-borne EIDs are indeed zoonotic; in fact, an even higher proportion of food-borne EIDs are zoonotic (84.5 percent) than the background rate of all EIDs in the updated database (62.3 percent) and of any other transmission mode (Figure A2-3). Clearly, patho-

FIGURE A2-2 Number of EID events per transmission mode classified by pathogen type.

gens from animals entering the food-production chain are of significant concern for their potential to become EIDs.

One of our earlier findings (Jones et al., 2008) was that a majority (54.3 percent) of human EIDs were bacterial/rickettsial in origin, reflecting a large number (20.8 percent of all EIDs) of new drug-resistant pathogen strains. We show above that if an EID was identified as being caused by bacteria, it was most likely to be food-borne, and similarly if an EID was linked with food it was most likely to be bacterial than of another transmission mode. Given the propensity of bacteria to develop drug resistance, and the abundance of food-borne infections of bacterial origin, is there any evidence that food-borne pathogens are contributing to new drug-resistant diseases?

FIGURE A2-3 Number of EID events per transmission mode categorized by zoonotic origin.

Perhaps surprisingly, the answer is no: when EID events are split into categories reflecting the presence or absence of drug resistance (ignoring for a moment the secondary split on whether the pathogen was zoonotic or not), food-borne pathogens are very unlikely to be drug resistant (Figure A2-4). Although it is true that drug resistance is relatively infrequently observed across most transmission modes (the exception being fomite-associated EIDs), resistance is particularly infrequent in food-borne (as well as vector-borne) EIDs. Hence, even though bacteria are quite likely to cause food-borne EIDs and bacteria also cause the majority of new drug-resistant diseases, this is quite unlikely to occur together, resulting in very few drug-resistant food-borne EIDs. Why is drug resistance not more common in this group?

FIGURE A2-4 Proportion of drug-resistant and nonresistant EID events of zoonotic (1), or non-zoonotic origin (0).

The answer may be related to whether the causal agent is zoonotic or not. Generally speaking, there is a low frequency of zoonotic EIDs that exhibit drug resistance (6.0 percent), regardless of the transmission mode (Figure A2-4). Non-zoonotic EIDs are far more likely to be associated with drug resistance (40.9 percent), again across all groups. This is consistent with the idea that new drug-resistant pathogens result from selection on our own circulating pathogens by the routine use of antimicrobial drugs, and not on the pathogens circulating in the food industry that originate in animals. In other words, even though most food-borne EIDs are caused by bacteria, which generally show high potential for becoming drug resistant, the fact that most food-borne EIDs are zoonotic means that the group is quite unlikely to experience strong selection pressure from

routine drug administration in human patients. Obviously there are limitations to this type of analysis, particularly in how extensive the data are, but it is clear that this issue is an important target for future research.

Finally, what are the drivers of food-borne pathogens, and are they an ongoing concern for their EID potential? As we have seen, food-borne EIDs are common, usually zoonotic, usually bacterial, and not likely to exhibit drug resistance. So what factors are driving them to emerge? What factors are allowing them to enter and circulate within the food-production system to subsequently cause disease in humans? In Figure A2-5, we analyse the underlying drivers listed in a previous Institute of Medicine report (IOM, 2003) for food-borne EIDs and find that the vast majority of food-borne EIDs are associated with “technology and industry,” and to a lesser extent with “international trade and commerce” and “human susceptibility to infection.” This is consistent with previous studies that have suggested that outbreaks of food-borne infections are likely to be associated with changes in livestock production and centralization of slaughtering

FIGURE A2-5 Association of food-borne EIDs with other drivers.

SOURCE: Following IOM (2003).

and processing (IOM, 2003; Tauxe, 1997). As a result of these analyses, we can hypothesize that the global distribution of food-borne EIDs is driven by a process of intensive production of livestock and food, not simply the number of livestock produced in a region.

Food-Borne EID Hotspots

Our previous approach to predicting the future geographic origins of new EIDs (Jones et al., 2008) can be adapted for food-borne EIDs. This approach involves identifying the geographic and temporal origins of previous disease emergence events and correcting them for surveillance biases. We then identify correlations between these and purported socioeconomic (demography, travel, trade), environmental (climate, land cover), and ecological drivers ( biodiversity, species interactions). Considering all EIDs together, these models suggest that surveillance should be directed toward regions of high biodiversity and dense human populations, which mainly occur in tropical and subtropical latitudes (Jones et al., 2008). When we adapt this approach to food-borne EID events and use the same drivers as in our earlier analysis, human population density and human population growth emerge as the most important in the emergence of novel food-borne outbreaks (Figure A2-6). This suggests that rapidly developing regions are the sites where most novel food-borne pathogens will emerge in future. This may appear to be in conflict with Figure A2-5; however, this is because the spatial analyses have so far been limited primarily by the availability of relevant spatial information. Human population density and growth are likely to be meaningful proxies for a range of other mechanistically more relevant drivers. One of our main goals more recently has thus been to improve our database of detailed drivers. We have, for

FIGURE A2-6 Relative risk of food-borne EID events, based on Jones et al. (2008). Human population density and human population growth are the most important variables.

SOURCE: Reprinted by permission from Macmillan Publishers Ltd: Nature, (Jones et al., 2008).

example, begun to include spatial information on land-use change (cropping and pasture) and livestock density (including cattle, pigs, buffalo, goats, and sheep) into the predictive models. We are currently validating these new data sources for use in future models.

We conclude that food-borne EIDs are a common and important group within emerging diseases that emerge through complex pathways involving wildlife, livestock, and humans. They are therefore ideal candidates for a One Health approach but have rarely been considered in this way previously. Our analyses show that the majority of food-borne EIDs (1) are bacterial; (2) are, if bacterial, more likely to be food-borne than of any other transmission mode; (3) are zoonotic; (4) do not tend to be associated with drug resistance, perhaps because zoonotic pathogens in general show little tendency to become resistant; and (5) are driven by changes in human food-production systems, including intensification and centralization as human populations grow larger and more dense.

References

Arzt, J., W. R. White, B. V. Thomsen, and C. C. Brown. 2010. Agricultural diseases on the move early in the third millennium. Veterinary Pathology 47:15-27.

Chua, K. B., W. J. Bellini, P. A. Rota, B. H. Harcourt, A. Tamin, S. K. Lam, T. G. Ksiazek, P. E. Rollin, S. R. Zaki, W. Shieh, C. S. Goldsmith, D. J. Gubler, J. T. Roehrig, B. Eaton, A. R. Gould, J. Olson, H. Field, P. Daniels, A. E. Ling, C. J. Peters, L. J. Anderson, and B. W. Mahy. 2000. Nipah virus: A recently emergent deadly paramyxovirus. Science 288:1432-1435.

Daszak, P. 2011. Smart surveillance: Analyzing environmental drivers of emergence to predict and prevent pandemics. Ecohealth 7:S12-S13.

Gilbert, M., X. M. Xiao, D. U. Pfeiffer, M. Epprecht, S. Boles, C. Czarnecki, P. Chaitaweesub, W. Kalpravidh, P. Q. Minh, M. J. Otte, V. Martin, and J. Slingenbergh. 2008. Mapping H5N1 highly pathogenic avian influenza risk in Southeast Asia. Proceedings of the National Academy of Sciences of the United States of America 105:4769-4774.

Hughes, L. A., M. Bennett, P. Coffey, J. Elliott, T. R. Jones, R. C. Jones, A. Lahuerta-Marin, K. McNiffe, D. Norman, N. J. Williams, and J. Chantrey. 2009. Risk factors for the occurrence of Escherichia coli virulence genes eae, stx1 and stx2 in wild bird populations. Epidemiology and Infection 137:1574-1582.

IOM (Institute of Medicine). 2003. Microbial threats to health: Emergence, detection, and response. Washington, DC: The National Academies Press.

Jones, K. E., N. Patel, M. Levy, A. Storeygard, D. Balk, J. L. Gittleman, and P. Daszak. 2008. Global trends in emerging infectious diseases. Nature 451:990-994.

Khan, M. S. U., J. Hossain, E. S. Gurley, N. Nahar, R. Sultana, and S. P. Luby. 2011. Use of infrared camera to understand bats’ access to date palm sap: Implications for preventing Nipah virus transmission. Ecohealth 7:517-525.

Nielsen, E. M., M. N. Skov, J. J. Madsen, J. Lodal, J. B. Jespersen, and D. L. Baggesen. 2004. Verocytotoxin-producing Escherichia coli in wild birds and rodents in close proximity to farms. Applied and Environmental Microbiology 70:6944-6947.

Pulliam, J. R., J. H. Epstein, J. Dushoff, S. A. Rahman, M. Bunning, A. A. Jamaluddin, A. D. Hyatt, H. E. Field, A. P. Dobson, and P. Daszak. 2011. Agricultural intensification, priming for persistence and the emergence of Nipah virus: A lethal bat-borne zoonosis. Journal of the Royal Society Interface 9(66):89-101. doi: 10.1098/ rsif.2011.0223.

Rahn, K., S. A. Renwick, R. P. Johnson, J. B. Wilson, R. C. Clarke, D. Alves, S. McEwen, H. Lior, and J. Spika. 1997. Persistence of Escherichia coli O157:H7 in dairy cattle and the dairy farm environment. Epidemiology and Infection 119:251-259.

Tauxe, R. V. 1997. Emerging foodborne diseases: An evolving public health challenge. Emerging Infectious Diseases 3:425-434.

Taylor, L. H., S. M. Latham, and M. E. J. Woolhouse. 2001. Risk factors for human disease emergence. Philosophical Transactions of the Royal Society of London, B 356:983-989.

Wolfe, N. D., P. Daszak, A. M. Kilpatrick, and D. S. Burke. 2005. Bushmeat hunting, deforestation and prediction of zoonotic emergence. Emerging Infectious Diseases 11:1822-1827.

A3

PLANT FOOD SAFETY ISSUES: LINKING PRODUCTION AGRICULTURE WITH ONE HEALTH

Marilyn C. Erickson and Michael P. Doyle⁴

During the past decade, fruits and vegetables have become leading vehicles of food-borne illnesses. Furthermore, many plant-based foods and ingredients, not previously considered a risk, have been associated with food-borne disease outbreaks. Most of the pathogens that have been identified as causative agents in these illnesses or outbreaks are enteric zoonotic pathogens that are typically associated with animal hosts. Transmission of zoonotic pathogens from animals to plant systems occurs by a variety of routes, but the initial contributing factor is the discharge of animal manure into the environment. Using a “One Health” approach that focuses on animal, human, and environmental health concurrently can provide practical and effective interventions for reducing the incidence of such outbreaks. This paper addresses this concept by providing recent food-borne disease outbreak data related to fruits and vegetables, delineating findings regarding the prevalence of pathogens in animal manures and describing the vehicles that transmit pathogens from manure to produce fields, and discussing the merits of reducing pathogen transmission through interventions that would not adversely affect the health of the environment or animals.

Outbreaks and Illnesses Associated with Fresh Fruits and Vegetables

Food-borne illnesses have been a persistent challenge to public health and are now being detected with greater frequency largely because of enhanced surveillance systems that have been implemented in many countries. These enhanced surveillance systems have during the past decade revealed that the proportion of total outbreaks attributed to produce is significant (Lynch et al., 2009) but varies with the country. For example, only 4 percent of all food-borne outbreaks

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⁴ Center for Food Safety, University of Georgia, 1109 Experiment Street, Griffin, GA 30223, USA.

reported in Australia from 2001 to 2005 were attributed to fresh produce (Kirk et al., 2008); similarly, in Canada, between 1976 and 2005, 3.7 percent of 5,745 outbreaks with a known vehicle of transmission were attributed to produce (Ravel et al., 2009). However, in contrast, data from the Centers for Disease Control and Prevention (CDC) identified produce as either the first or second leading vehicle in food-borne disease outbreaks attributed to a single commodity within the United States for the period 2006-2008 (Table A3-1). Furthermore, outbreak surveillance data of produce items compiled by the CDC during the period 2000-2009 revealed that leafy greens were the most common item associated with food-borne disease, followed by tomatoes and cantaloupes (Table A3-2). Moreover, attribution risk rankings of fresh produce—associated outbreaks in the United States identified enterohemorrhagic Escherichia coli in leafy greens as the leading pathogen-produce vehicle combination, followed by Salmonella spp. in tomatoes, and Salmonella spp. in leafy greens (Anderson et al., 2011). Further differentiation of vehicles of produce-associated outbreaks that occurred in the United States during the period of 1998-2008 revealed that fresh-cut produce accounted for 56 percent, 36 percent, and 17 percent of the outbreaks attributed to leafy greens, tomatoes, and melons, respectively (Sneed, 2010).

An evaluation of selected produce-associated outbreaks that occurred during the past 5 years revealed several common features (Table A3-3). These outbreaks often were multistate or multinational in nature and reflect the large areas to which the foods are distributed. With imports accounting for nearly 39 percent of fresh fruits and 14 percent of fresh vegetables in 2005 (Johnson, 2012), improved sampling and pathogen testing of produce at the borders of the United States offers one barrier for reducing the likelihood of contaminated produce

TABLE A3-1 Food-Borne Disease Outbreaks Attributed to a Single Commodity by Leading Food Vehicles, 2006-2008

SOURCE: CDC (2009a, 2010c, 2011e).

TABLE A3-2 Number of Outbreaks (illnesses) Reported Between 2000 and 2009 in the United States That Were Associated with Selected Fresh Produce Items as a Function of their Etiology^a,b

^a Data compiled from the CDC website on outbreak surveillance (http://www.cdc.gov/outbreaknet/surveillance_data.html).

^b Outbreaks/illnesses attributed to each pathogen group includes both confirmed and suspected.

^c Includes other Shiga toxin–producing Escherichia coli.

^d Includes where multiple bacterial pathogens have been found and cases involving the agents of Bacillus cereus, Clostridium botulinum, C. perfringens, Listeria monocytogenes, and Staphylococcus aureus.

SOURCE: CDC.

from entering the retail sector. However, better implementation both domestically and abroad of best food safety practices for producing and processing fruits and vegetables would have even more impact on reducing pathogen contamination and the likelihood of produce-borne illnesses. This approach would address a significant contributing factor associated with several recent produce outbreaks, which is that contamination occurs on the farm where production and processing can occur. For example, in a multistate outbreak of listeriosis in 2011 that resulted in 34 deaths and was the most deadly food-borne outbreak in the United States since 1924, four outbreak-associated strains of Listeria monocytogenes were traced back to whole cantaloupes and packing equipment on Jensen Farms in Colorado (CDC, 2011c). In another 2011 outbreak, fenugreek seeds that were likely contaminated with fecal matter led to the largest outbreak in the number of cases of hemolytic uremic syndrome (22.3 percent of 4,075 total cases) ever reported in the world (WHO, 2011).

Surveillance of Pathogens in Retail Produce

A number of studies have been conducted to determine the prevalence of enteric pathogens on fruits and vegetables, and the results varied with respect

to the country of origin and the target pathogen. For Salmonella, there was for most developed countries a very low prevalence in cabbage, lettuce, and mixed salads, whereas higher prevalences were observed for developing countries where agricultural production and hygienic practices were of a lower level of sanitation (Table A3-4). The presence of helminth and protozoan parasites in leafy greens (Table A3-5), however, likely reflects the ability of these pathogens to resist standard chlorine-based wastewater treatments (Erickson and Ortega, 2006; Graczyk et al., 2007). The relatively low occurrence of pathogen contamination on produce makes it inherently difficult to rank the degree of risk associated with the various sources of contamination by which enteric pathogens are transmitted from animals to plant production environments.

Pathogens in Manures from Domesticated Animal

A large number of zoonotic pathogens reside and grow in the gastrointestinal tract of domesticated animals (poultry, cattle, swine, sheep, and goats) and are shed in their feces asymptomatically, often in very large numbers. Those enteric pathogens associated with the largest number of food-borne disease outbreaks and illnesses include Campylobacter jejuni, Salmonella spp., Shiga toxin—producing

TABLE A3-3 Selected Food-Borne Disease Outbreaks Attributed to Produce During the Period of 2006-2011

SOURCE: CDC.

enterohemorrhagic Escherichia coli (STEC), and Cryptosporidium parvum. Many studies have been conducted to determine the prevalence of these pathogens in the feces of domesticated animals. A selection of results of recent studies are shown in Tables A3-6 to A3-9 to illustrate the range of pathogen prevalences and cell numbers that may occur within animal wastes and between and within different groups of animals. For Cryptosporidium, not all species are pathogenic for humans. For example, currently there are at least 16 recognized species of Crypto-sporidium, of which two most affect humans, C. hominis and C. parvum (Jagai et al., 2010). Therefore, when results do not differentiate species of Cryptosporidium, the potential risk of those manures to human health may be overestimated.

SOURCE: CDC.

Management of Wastes from Domesticated Animals

Globally, food animal production has increased more than fivefold in the past 50 years due in large part to the adoption of the industrialized concentrated animal production model. With multinational companies expanding their operations overseas, estimates indicate that concentrated animal feeding operations (CAFOs) provide 74 percent of poultry, 50 percent of pork, and 43 percent of beef produced worldwide (Halweil and Nierenberg, 2004). Accompanying this expansion in production has been the challenge of managing the massive quantities of animal wastes that are generated in one location. For example, in China, animal waste was estimated to be 3.2 billion tons, which was three times the amount of

TABLE A3-4 Prevalence of Salmonella in Lettuce, Cabbage, and Mixed Salads Throughout the World (2001-2011)

SOURCE: CDC.

industrial solid waste produced in that same year (Wang et al., 2005). Within the United States, it has also been reported that confined food animals produce approximately 335 million dry tons of waste per year, which is more than 40 times the amount of human biosolids waste generated from wastewater treatment plants (Graham and Nachman, 2010). The vast majority of this animal waste is applied to land without any required treatment for reduction of pathogens as is required for human biosolids (EPA, 2004).

There are two primary forms of animal wastes generated at CAFOs. In the case of broiler units, solid waste is generated either as single-use, partial reuse, or multiuse litter (Bolan et al., 2010). In confined swine and cattle operations, water is used to flush waste from the floors where the animals are housed, and the liquid slurry is channeled into large ponds for storage (Graham and Nachman, 2010). The application of animal wastes to land is largely based on agronomic requirements, geography, and commodity choices. For example, corn receives more than half of the land-applied manure, of which most of the manure is from dairy and hog stock because of the use of corn as a major feed crop for dairy and hog operations and the high growth nutrient requirement of corn for nitrogen-rich manure. Hay and grasses are the second largest of the crops fertilized by manure, which is mostly from hog, broiler, and dairy producers (MacDonald et al., 2009). Poultry litter, on the other hand, is frequently used as a fertilizer for cotton, peanuts, and fresh produce (Boyhan and Hill, 2008).

Direct Transmission of Enteric Pathogens from
Animal Wastes to Produce Fields

Animal manures applied to fields to be used for fruit and vegetable production have the potential to be a direct source of enteric pathogens if there has not been sufficient holding time between planting and harvest. The U.S. Department of Agriculture (USDA) National Organic Program permits the incorporation of raw manure into soil 120 days before harvest if the food crop has direct contact with the soil; however, only 90 days prior to harvest is required if crops have no contact with the soil (7 Code of Federal Regulations [CFR] 205.203). In contrast, more stringent requirements have been set by the Leafy Greens Marketing Agreement in which 1 year between application of raw manure and harvest of the crop is advocated (LGMA, 2012). As part of the Food Safety Modernization Act, it is anticipated that the Food and Drug Administration will include in its produce rule a required time interval between manure application to fields and either the planting or harvest of crops that would be consumed raw.

Transmission via Runoff of Enteric Pathogens from
Animal Waste—Applied Lands to Produce Fields

One of the routes by which enteric pathogens may be indirectly transferred to produce fields from domesticated animal waste deposited or stored on land

TABLE A3-5 Prevalence of Helminth and Protozoan Parasites in Leafy Greens from 2005-2010

SOURCE: CDC.

adjacent to produce fields is via storm runoff. Many studies have revealed that enteric pathogens can move both horizontally and vertically to contaminate land, surface waters, and ground waters adjacent to produce fields (Cooley et al., 2007; Forslund et al., 2011). In these situations, the risk of pathogen contamination of produce will be dependent on a number of factors, including the attachment strength of the pathogen to soil particles, the interval between the manure application and the precipitation events, the kinetic energy of the rainfall, the topographical slope that affects the direction and velocity of water flow, and the density of vegetation between the waste source and the destination site (Ferguson et al., 2007; Hodgon et al., 2009; Jamieson et al., 2002; Lewis et al., 2010; Mishra et al., 2008; Saini et al., 2003; Tyrrel and Quinton, 2003). In addition, the physical state of the waste will also affect the direction of movement of the pathogens with greater percolation occurring by a liquid slurry source and greater overland transport for a solid manure source (Forslund et al., 2011; Semenov et al., 2009).

Transmission of Enteric Pathogens from Waste-
Contaminated Water Sources to Produce Fields

Storm runoff carrying pathogens from animal wastes does not necessarily have to pass through agricultural produce fields to be a source of contamination. Collection in surface waters and subsequent use of that water to irrigate produce crops is another means to disseminate the pathogens. Surveys of environmental water sources for pathogen contamination have revealed significant contamina-

tion with Salmonella spp., STEC, and protozoan parasites (Table A3-10); however, contamination appears to be sporadic and is often associated with recent rain events and seasonality (Gaertner et al., 2009; Haley et al., 2009). Enhanced survival of pathogens in the sediment (Chandran et al., 2011; Garzio-Hadzick et al., 2010) and resuspension of the organisms into the water column may also perpetuate the risk. Contamination of surface waters, moreover, has been associated with the concentration of food animals raised in the area (Cooley et al., 2007; Johnson et al., 2003; Tserendorj et al., 2011; Wilkes et al., 2011). Salmonella and Cryptosporidium contamination of watersheds not impacted by human or domesticated animal production has been observed (Edge et al., 2012; Patchanee et al., 2010), which suggests that there is a level of natural occurrence of these pathogens from wildlife sources.

Several epidemiological studies lend support to the role that contaminated irrigation water serves as a transmission vehicle of enteric pathogens to fresh produce. In 2002 and 2005, two outbreaks of S. Newport infection in the United States were associated with eating tomatoes and the outbreak strain was isolated from the pond water used to irrigate the tomato fields (Greene et al., 2008). Irrigation of fields with contaminated irrigation waters was also indicated as a possible source of contamination of imported cantaloupe associated with an outbreak of S. Poona infection in the United States in consecutive years during 2000-2002 (CDC, 2002). Given the often sporadic nature of contamination of irrigation water, these documented cases linking irrigation water to an outbreak may represent only a small fraction of the contamination events that actually occur. World-

TABLE A3-6 Prevalence and Cell Numbers of Salmonella spp. in Manures from Domesticated Animals

NOTE: CFU, colony forming unit; MPN, most probable number.

TABLE A3-7 Prevalence and Cell Numbers of Campylobacter spp. in Manures from Domesticated Animals

NOTE: CPU. colony forming unit.

TABLE A3-8 Prevalence and Cell Numbers of Shiga Toxin–Producing E. coli in Manures from Domesticated Animals

NOTE: CFU, colony forming unit; STEC, Shiga toxin-producing Escherichia coli.

TABLE A3-9 Prevalence and Cell Numbers of Cryptosporidium spp. in Manures from Domesticated Animals

NOTE: CFU, colony forming unit.

TABLE A3-10 Prevalence of Salmonella spp., STEC, and Protozoan Parasites in Environmental Waters

wide it is estimated that 17 percent of the world’s cropland (1.4 billion hectares) is irrigated and, of that, 20 million hectares are irrigated with untreated wastewater (Jimenez et al., 2010). In the United States and the United Kingdom, extensive irrigation of fresh produce crops occurs and, of the acreage irrigated, 48 percent and 78 percent, respectively, are derived from non-groundwater sources (Knox et al., 2011; USDA NASS, 2009), which are subject to intermittent inputs of pathogens from animal husbandry operations.

Contribution of Bioaerosols to Dissemination of Enteric Pathogens from Animal Production Operations to Produce Fields

Aerosolization of microbial pathogens is an inevitable consequence associated with animal production operations as well as the handling and disposition of animal manure. However, estimating the impact of bioaerosol dispersal on pathogen dissemination has been hampered by the notable absence of standardized and validated methods for enumeration of various types of microorganisms in outdoor bioaerosols. Hence, there has been a wide range of prevalence and cell number values reported across very diverse types of animal operations and landscapes (Millner, 2009).

Studies addressing bioaerosol levels in outdoor air generally address fecal indicator organisms because they are more abundant and easily identified in the aerosols, although it is acknowledged that they may behave differently than the pathogens. The general trend that has been observed is decreasing airborne microorganism concentrations as the distance from the source increases with relative humidity, temperature, and solar irradiance being major factors affecting viability (Dungan, 2010). Other pertinent observations made in studies addressing the levels of the indicator organism, E. coli, in aerosols of poultry houses are that the levels of airborne bacteria are intricately linked to the levels of those bacteria in the litter (Chinivasagam et al., 2009; Smith et al., 2012) and the type of ventilation system affects the distance that E. coli is disseminated, with E. coli traversing 11.1 and 7.5 m downwind from houses using tunnel and conventional fans, respectively (Smith et al., 2012).

Limited studies have been conducted addressing bioaerosol transport following land application of animal manures in contrast to those addressing the application of municipal wastes (Pillai and Ricke, 2002). Although there may be some similar behavior between these two sources, there could be differences given that they vary in their organic matter content that can provide differences in the degree of protection against ultraviolet radiation and drying (Dungan, 2010). In one of the few studies addressing land application of cattle and swine slurry and the method used to disperse the wastes, total bacterial counts in the air were greater at greater distances from spray guns that discharged the slurry upward into the air compared to tank spreading that sprayed the slurries closer to the ground (Boutin et al., 1988). In another study in which swine manure was ap-

plied through a center pivot irrigation system, coliform concentrations decreased to near background concentrations at 23 m downwind (Kim et al., 2008). Wind speed and topography, however, are likely to also factor into the distances traversed by pathogens and, hence, safe distances between produce fields and animal production activities will likely be site specific.

Wildlife as a Vehicle to Transmit Pathogens from
Domesticated Animal Waste to Produce Fields

The recent focus on wildlife as a potential source of pathogen contamination of produce fields was driven by the isolation of E. coli O157:H7 from feral swine that occupied areas near spinach fields and cattle farms in California following the 2006 spinach outbreak (Jay et al., 2007). More recently, Campylobacter jejuni was isolated both from Sandhill crane feces and raw peas and several of the isolates had pulsed-field gel electrophoresis (PFGE) patterns indistinguishable from clinical samples obtained during a C. jejuni gastroenteritis outbreak that occurred in Alaska in 2008 (Gardner et al., 2011). Attention was again focused on wildlife as a potential source of contamination when E. coli O157:H7 isolated from deer feces was determined to have an identical PFGE pattern as the isolates responsible for 15 people who were ill from eating contaminated fresh straw berries in Oregon in 2011 (IEH Laboratories & Consulting Group, 2011). Given that the same strain was also isolated from soil raises the question as to whether the deer were actually the source of the outbreak or were infected when they ate the contaminated strawberries. Most evidence indicating that wildlife is a potential source of food-borne contamination is from the isolation of clinically relevant pathogens from the animal’s feces. In one example, Renter et al. (2006) isolated from deer fecal samples four Salmonella serovars (Litchfield, Dessau, Infantis, and Enteritidis) known to be pathogenic to humans and animals. In another example, subtyping of STEC isolates from wildlife meat in Germany identified virulence genes associated with severe clinical outcome (stx2, stx2d, and eae) in 46 of the 140 STEC samples (Miko et al., 2009). More definitive proof that specific types of wildlife could be transmission vectors of pathogens from domesticated animal facilities was obtained with a study of European starlings (Williams et al., 2011). In that study, distinct molecular types of E. coli O157:H7 were similar in starlings and cattle on different farms, and these birds were capable of shedding the pathogen in their feces for more than 3 days (Kauffman and LeJeune, 2011). Hence, it is reasonable to assume that European starlings could serve as a vector of pathogens from cattle and dairy farms to produce fields.

In response to the limited studies linking wildlife to produce contamination, processors and buyers have become overreactive in many cases in requiring the absence of many types of wildlife from farms. To illustrate this trend, the percentage of growers that reported being told by their processors or buyers that feral pigs, deer, birds, rodents, and amphibians were a significant risk was 19, 28,

44, 47, and 28 percent, respectively (Lowell et al., 2010). Several studies, however, have revealed that some groups of animals have a very low prevalence of contamination with relevant human enteric pathogens (Table A3-11). It is likely that all animal groups have the potential to be contaminated with a food-borne pathogen, but whether they are significant harbingers of human enteric pathogens is likely dependent on their access to animal husbandry sites as well as on their social behavior (i.e., existence of a social group and its size). This would also be the case with insects. For example, filth flies collected in leafy green fields were believed to have originated from nearby rangelands that contained fresh cattle manure (Talley et al., 2009).

Persistence of Pathogens on Produce in Fields Requires a Systems Approach to Prevent and Monitor Pathogen Introduction

Many field studies have revealed the persistence of human enteric pathogens, albeit typically at low levels, in a number of different vegetables contaminated at various points during their cultivation (Erickson et al., 2010; Gutiérrez-Rodriguez et al., 2011; Islam et al., 2004a, 2004b, 2004c, 2005; Moyne et al., 2011). This is noteworthy because chemical disinfectants typically used during minimal processing of fresh produce are not fully effective in eliminating pathogen contamination (Doyle and Erickson, 2008). Hence, it is paramount to prevent the introduction of these pathogens into produce fields. The primary approach currently used to reduce the risk of pathogen contamination in fields is the application of good agricultural practices (GAPs). To prevent the introduction of pathogens through nontraditional vehicles (storm runoff, intrusions by pathogen-carrying wildlife) will require the development of novel approaches in addition to GAPs. Given that the environment surrounding the produce field would likely be impacted by these pathogen control practices, it is important to implement a systems approach and consider all ramifications to the adoption of any intervention practices. It is also important to be cognizant that storm runoff and fecal deposits from wildlife may only contaminate the plants at discrete locations within a field. The ability to detect this contamination by current sampling plans that rely on uniform contamination is therefore limited and efforts are needed to develop new monitoring systems that can detect contamination when such pathogen introductions occur.

Concluding Comments

Vegetables, fruits, and a variety of plant foods and ingredients are now recognized as major vehicles of food-borne disease outbreaks, and a primary source of pathogen contamination of this commodity group is animal manure. There are several routes by which pathogens can be transmitted from animal production sites to produce fields. The vehicles likely presenting the greatest risk are manure-contaminated soil amendments and irrigation water. Wildlife, insects,

TABLE A3-11 Prevalence of Enteric Food-Borne Pathogens in Wildlife and Insects

and vermin, however, may also serve as intermediate vectors of pathogens from animal wastes to plants in the field. The multifaceted routes by which pathogens may be transmitted to produce crops illuminates the value of a One Health approach to minimize pathogen contamination in the production environment while ensuring that adverse effects to the environment be minimized.

References

Abadias, M., J. Usall, M. Anguera, C. Solsona, and I. Viñas. 2008. Microbiological quality of fresh, minimally-processed fruit and vegetables, and sprouts from retail establishments. International Journal of Food Microbiology 123:121-129.

Abougrain, A. K., M. H. Nahaisi, N. S. Madi, M. M. Saied, and K. S. Ghenghesh. 2010. Parasitological contamination in salad vegetables in Tripoli-Libya. Food Control 21:760-762.

Ahmed, W., S. Sawant, F. Huygens, A. Goonetilleke, and T. Gardner. 2009. Prevalence and occurrence of zoonotic bacterial pathogens in surface waters determined by quantitative PCR. Water Research 43:4918-4928.

Alam, M. J., and L. Zurek. 2004. Association of Escherichia coli O157:H7 with houseflies on a cattle farm. Applied and Environmental Microbiology 70:7578-7580.

Alam, M. J., and L. Zurek. 2006. Seasonal prevalence of Escherichia coli O157:H7 in beef cattle feces. Journal of Food Protection 69:3018-3020.

Amoah, P., P. Drechsel, R. C. Abaidoo, and W. J. Ntow. 2006. Pesticide and pathogen contamination of vegetables in Ghana’s urban markets. Archives of Environmental Contamination and Toxicology 50:1-6.

Amorós, I., J. L. Alonso, and G. Cuesta. 2010. Cryptosporidium oocysts and Giardia cysts on salad products irrigated with contaminated water. Journal of Food Protection 73:1138-1140.

Anderson, M., L.-A. Jaykus, S. Beaulieu, and S. Dennis. 2011. Pathogen-produce pair attribution risk ranking tool to prioritize fresh produce commodity and pathogen combinations for further evaluation (P³ARRT). Food Control 22:1865-1872.

Arthur, L., S. Jones, M. Fabri, and J. Odumeru. 2007. Microbial survey of selected Ontario-grown fresh fruits and vegetables. Journal of Food Protection 70:2864-2867.

Berg, J., T. McAllister, S. Bach, R. Stilborn, D. Hancock, and J. LeJeune. 2004. Escherichia coli O157:H7 excretion by commercial feedlot cattle fed either barley- or corn-based finishing diets. Journal of Food Protection 67:666-671.

Bolan, N. S., A. A. Szogi, T. Chuasavathi, B. Seshadri, M. J. Rothrock, Jr., and P. Panneerselvam. 2010. Uses and management of poultry litter. World’s Poultry Science Journal 66:673-698.

Bornay-Llinares, F. J., L. Navarro-i-Martínez, F. García-Orenes, H. Araez, M. D. Pérez-Murcia, and R. Moral. 2006. Detection of intestinal parasites in pig slurry: A preliminary study from five farms in Spain. Livestock Science 102:237-242.

Boutin, P., M. Torre, R. Serceau, and P. J. Rideau. 1988. Atmospheric bacterial contamination from landspreading of animal wastes: Evaluation of the respiratory risk for people nearby. Journal of Agricultural Engineering Research 39:149-160.

Boyhan, G. E., and C. R. Hill. 2008. Organic fertility sources for the short-day organic onion transplants. HortTechnology 18:227-231.

Briones, V., S. Téllez, J. Goyache, C. Ballesteros, M. del Pilar Lanzarot, L. Domínguez, and J. F. Fernández-Garayzábal. 2004. Salmonella diversity associated with wild reptiles and amphibians in Spain. Environmental Microbiology 6:868-871.

Callaway, T. R., R. C. Anderson, G. Tellez, C. Rosario, G. M. Nava, C. Eslava, M. A. Blanco, M. A. Quiroz, A. Olguín, M. Herradora, T. S. Edrington, K. J. Genovese, R. B. Harvey, and D. J. Nisbet. 2004. Prevalence of Escherichia coli O157 in cattle and swine in Central Mexico. Journal of Food Protection 67:2274-2276.

Calvin, L. 2007. Outbreak linked to spinach forces reassessment of food safety practices. Amber Waves 5(3):24-31. http://www.ers.usda.gov/AmberWaves/June07/PDF/Spinach.pdf (accessed January 6, 2011).

Castañeda-Ramírez, C., V. Cortes-Rodríguez, N. de la Fuente-Salcido, D. K. Bideshi, M. Cristina, M. C. del Rincón-Castro, and J. E. Barboza-Corona. 2011. Isolation of Salmonella spp. from lettuce and evaluation of its susceptibility to novel bacteriocins of Bacillus thuringiensis and antibiotics. Journal of Food Protection 74:274-278.

CDC (Centers for Disease Control and Prevention). 2002. Multistate outbreaks of Salmonella serotype Poona infections associated with eating cantaloupe from Mexico—United States and Canada, 2000-2002. Morbidity and Mortality Weekly Report 51(46):1044-1047.

———. 2006a. Botulism associated with commercial carrot juice—Georgia and Florida, Septem ber 2006. Morbidity and Mortality Weekly Report 55:1098-1099. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5540a5.htm (accessed January 8, 2011).

———. 2006b. Salmonellosis—outbreak investigation, October 2006. http://www.cdc.gov/ncidod/dbmd/diseaseinfo/salmonellosis_2006/outbreak_notice.htm (accessed January 6, 2011).

———. 2008a. Investigation of outbreak of infections caused by Salmonella Litchfield. http://www.cdc.gov/salmonella/litchfield/ (accessed January 6, 2011).

———. 2008b. Outbreak of Salmonella serotype Saintpaul infections associated with multiple raw produce items—United States, 2008. Morbidity and Mortality Weekly Report 57:929-934. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5734a1.htm (accessed January 6, 2011).

———. 2009a. Surveillance for foodborne disease outbreaks—United States. 2006. Morbidity and Mortality Weekly Report 58:609-615, expanded Table 2. http://www.cdc.gov/outbreaknet/pdf/surveillance/2006_reported_outbreaks_illnesses.pdf (accessed March 14, 2012).

———. 2009b. Outbreak of Salmonella serotype Saintpaul infections associated with eating alfalfa sprouts—United States, 2009. Morbidity and Mortality Weekly Report 58:500-503.

———. 2010a. Investigation update: Multistate outbreak of human Salmonella Newport infections linked to raw alfalfa sprouts. http://www.cdc.gov/salmonella/newport/index.html (accessed January 6, 2011).

———. 2010b. Investigation update: Multistate outbreak of human E. coli O145 infections linked to shredded romaine lettuce from a single processing facility (final update). http://www.cdc.gov/ecoli/2010/ecoli_o145/index.html (accessed July 21, 2011).

———. 2010c. Surveillance for foodborne disease outbreaks—United States, 2007. Morbidity and Mortality Weekly Report 59:973-579, expanded Table 2. http://www.cdc.gov/outbreaknet/pdf/2007MMWRSurveillanceOutbreaks_ExpandedTable2_WEB.pdf (accessed March 14, 2012).

———. 2011a. Investigation of a multistate outbreak of human Salmonella I 4,[5],12:i:- infections linked to alfalfa sprouts (January 6, 2011 report). http://www.cdc.gov/salmonella/i4512i-/010611/index.html (accessed January 6, 2011).

———. 2011b. Investigation update: Multistate outbreak of Salmonella Panama infections linked to cantaloupe. http://www.cdc.gov/salmonella/panama0311/062311/index.html (accessed March 10, 2012).

———. 2011c. Multistate outbreak of listeriosis linked to whole cantaloupes from Jensen Farms, Colorado (final update). http://www.cdc.gov/listeria/outbreaks/cantaloupes-jensen-farms/120811/index.html (accessed March 10, 2012).

———. 2011d. Surveillance for foodborne disease outbreaks—United States, 2008. Morbidity and Mortality Weekly Report 60:1197-1202, expanded Table 2. http://www.cdc.gov/outbreaknet/pdf/2008MMWR-Table2.pdf (accessed March 14, 2012).

Chandran, A., S. Varghese, E. Kandeler, A. Thomas, M. Hatha, and A. Mazumder. 2011. An assessment of potential public health risk associated with the extended survival of indicator and pathogenic bacteria in freshwater lake sediments. International Journal of Hygiene and Environmental Health 214:258-264.

Chen, Z., R. Mi, H. Yu, Y. Shi, Y. Huang, Y. Chen, P. Zhou, Y. Cai, and J. Lin. 2011. Prevalence of Cryptosporidium spp. in pigs in Shanghai, China. Veterinary Parasitology 181:113-119.

Chinivasagam, H. N., T. Tran, L. Maddock, A. Gale, and P. J. Blackall. 2009. Mechically ventilated broiler sheds: A possible source of aerosolized Salmonella, Campylobacter, and Escherichia coli. Applied and Environmental Microbiology 75:7417-7425.

Cho, S., F. Diez-Gonzalez, C. P. Fossler, S. J. Wells, C. W. Hedberg, J. B. Kaneene, P. L. Ruegg, L. D. Warnick, and J. B. Bender. 2006. Prevalence of shiga toxin-encoding Escherichia coli isolates from dairy farms and county fairs. Veterinary Microbiology 118:289-298.

Čížek, A., P. Alexa, I. Literák, J. Hamrík, P. Novák, and J. Smola. 1999. Shiga toxin-producing Escherichia coli O157 in feedlot cattle and Norwegian rats from a large-scale farm. Letters in Applied Microbiology 28:435-439.

Colles, F. M., J. S. Ali, S. K. Sheppard, N. D. McCarthy, and M. C. J. Maiden. 2011. Campylobacter populations in wild and domesticated Mallard ducks (Anas platyrhynchos). Environmental Microbiology Reports 3:574-580.

Cooley, M., D. Carychao, L. Crawford-Miksza, M. T. Jay, C. Myers, C. Rose, C. Keys, J. Farrar, and R. E. Mandrell. 2007. Incidence and tracking of Escherichia coli O157:H7 in a major produce production region in California. PLoS ONE 11:E1159.

Cox, P., M. Griffith, M. Angles, D. Deere, and C. Ferguson. 2005. Concentrations of pathogens and indicators in animal feces in the Sydney watershed. Applied and Environmental Microbiology 71:5929-5934.

De Giusti, M., C. Aurigemma, L. Marinelli, D. Tufi, D. De Medici, S. Di Pasquale, and C. De Vito. 2010. The evaluation of the microbial safety of fresh ready-to-eat vegetables produced by different technologies in Italy. Journal of Applied Microbiology 109:996-1006.

Doane, C. A., P. Pangloli, H. A. Richards, J. R. Mount, D. A. Golden, and F. A. Draughon. 2007. Occurrence of Escherichia coli O157:H7 in diverse farm environments. Journal of Food Protection 70:6-10.

Doyle, M. P., and M. C. Erickson. 2008. The problems with fresh produce: An overview. Journal of Applied Microbiology 105:313-330.

Droppo, I. G., S. N. Liss, D. Williams, T. Nelson, C. Jaskot, and B. Trapp. 2009. Dynamic existence of waterborne pathogens within river sediment compartments. Implications for water quality regulatory affairs. Environmental Science & Technology 43:1737-1743.

Dungan, R. S. 2010. Fate and transport of bioaerosols associated with livestock operations and manures. Journal of Animal Science 88:3693-3706.

Dunn, J. R., J. E. Keen, R. Del Vecchio, T. E. Wittum, and R. Alex Thompson. 2004. Escherichia coli O157:H7 in a cohort of weaned, preconditioned range beef calves. Journal of Food Protection 67:2391-2396.

Edge, T. A., A. El-Shaarawi, V. Gannon, C. Jokinen, R. Kent, I. U. H. Khan, W. Koning, D. Lapen, J. Miller, N. Neumann, R. Phillips, W. Robertson, H. Schreier, A. Scott, I. Shtepani, E. Topp, G. Wilkes, and E. van Bochove. 2012. Investigation of an Escherichia coli environmental benchmark for waterborne pathogens in agricultural watersheds in Canada. Journal of Environmental Quality 41:21-30.

Edrington, T. S., T. R. Callaway, D. M. Hallford, R. C. Anderson, and D. J. Nisbet. 2007. Influence of exogenous triiodothyronine (T₃) on fecal shedding of Escherichia coli O157 in cattle. Microbial Ecology 53:664-663.

EFSA (European Food Safety Authority). 2011. Shiga toxin-producing E. coli (STEC) O104:H4 2011 outbreaks in Europe: Taking stock. EFSA Journal 9:2390.

Eleftheriadou, M., A. Varnava-Tello, M. Metta-Loizidou, A-S. Nikolaou, and D. Akkelidou. 2002. The microbiological profile of foods in the Republic of Cyprus: 1991-2000. Food Microbiology 19:463-471.

Elviss, N. C., C. L. Little, L. Hucklesby, S. Sagoo, S. Surman-Lee, E. de Pinna, and E. J. Threlfall. 2009. Microbiological study of fresh herbs from retail premises uncovers an international outbreak of salmonellosis. International Journal of Food Microbiology 134:83-88.

Emberland, K. E., S. Ethelberg, M. Kuusi, L. Vold, L. Jensvoll, B-A. Lindstedt, K. Nygård, C. Kjelsø, G. Sørensen, T. Jensen, S. Lukinmaa, T. Niskanen, and G. Kapperud. 2007. Outbreak of Salmonella Weltevreden infections in Norway, Denmark and Finland associated with alfalfa sprouts, July-October 2007. Eurosurveillance 12(48):Article 4. http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=3321 (accessed January 6, 2011).

EPA (U.S. Environmental Protection Agency). 2004. Managing manure nutrients at concentrated animal feeding operations. Washington, DC. http://tammi.tamu.edu/final-manure-guidance.pdf (accessed March 11, 2012).

Erickson, M. C., and Y. R. Ortega. 2006. Inactivation of parasites in food, water, and environmental systems. Journal of Food Protection 69:2786-2808.

Erickson, M. C., C. C. Webb, J. C. Diaz-Perez, S. C. Phatak, J. J. Silvoy, L. E. Davey, A. S. Payton, J. Liao, L. Ma, and M. P. Doyle. 2010. Surface and internalized Escherichia coli O157:H7 on field-grown spinach and lettuce treated with spray-contaminated irrigation water. Journal of Food Protection 73:1023-1029.

Erdogrul, Ö., and H. Şener. 2005. The contamination of various fruits and vegetable with Enterobius vermicularis, Ascaris eggs, Entamoeba histolyca cysts and Giardia cysts. Food Control 16:559-562.

Ethelberg, S., M. Lisby, B. Böttiger, A. C. Schultz, A. Villif, T. Jensen, K. E. Olsen, F. Scheutz, C. Kjelsø, and L. Müller. 2010. Outbreaks of gastroenteritis linked to lettuce, Denmark, January 2010. Eurosurveillance 15(6):Article 1. http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19484 (accessed January 6, 2011).

Farzan, A., L. Parrington, T. Coklin, A. Cook, K. Pintar, F. Pollari, R. Friendship, J. Farber, and B. Dixon. 2011. Detection and characterization of Giardia duodenalis and Cryptosporidium spp. on swine farms in Ontario, Canada. Foodborne Pathogens and Disease 8:1207-1213.

FDA (Food and Drug Administration). 2006. UPDATE: E. coli O157:H7 Outbreak at Taco Bell restaurants likely over. FDA traceback investigation continues. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2006/ucm108805.htm (accessed January 6, 2011).

———. 2007. FDA and states closer to identifying source of E. coli contamination associ ated with illnesses at Taco John’s restaurants. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2007/ucm108827.htm (accessed January 6, 2011).

Ferguson, C. M., C. M. Davies, C. Kaucner, M. Krogh, J. Rodehutskors, D. A. Deere, and N. J. Ashbolt. 2007. Field scale quantification of microbial transport from bovine feces under simulated rainfall events. Journal of Water and Health 5:83-95.

Forslund, A., B. Markussen, L. Toenner-Klank, T. B. Bech, O. S. Jacobsen, and A. Dalsgaard. 2011. Leaching of Cryptosporidium parvum oocysts, Escherichia coli, and a Salmonella enterica serovar Typhimurium bacteriophage through intact soil cores following surface application and injection of slurry. Applied and Environmental Microbiology 77:8129-8138.

Friesema, I., G. Sigmundsdottir, K. van der Zwaluw, A. Heuvelink, B. Schimmer, C. de Jager, B. Rump, H. Briem, H. Hardardottir, A. Atladottir, E. Gudmundsdottir, and W van Pelt. 2007. An international outbreak of Shiga toxin-producing Escherichia coli O157 infection due to lettuce, September-October 2007. Eurosurveillance 13:50. http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19065 (accessed January 6, 2011).

Fröder, H., C. G. Martins, K. L. Oliveira de Souza, M. Landgraf, B. D. G. M. Franco, and M. T. Destro. 2007. Minimally processed vegetable salads: Microbial quality evaluation. Journal of Food Protection 70:1277-1280.

Gaertner, J. P., T. Garres, J. C. Becker, M. L. Jimenez, M. R. J. Forstner, and D. Hahn. 2009. Temporal analyses of Salmonellae in a headwater spring ecosystem reveals the effects of precipitation and runoff events. Journal of Water and Health 7:115-121.

Gardner, T. J., C. Fitzgerald, C. Xavier, R. Klein, J. Pruckler, S. Stroika, and J. B. McLaughlin. 2011. Outbreak of campylobacteriosis associated with consumption of raw peas. Clinical Infectious Diseases 53:16-21.

Garzio-Hadzick, A., D. R. Shelton, R. L. Hill, Y. A. Pachepsky, A. K. Guber, and R. Rowland. 2010. Survival of manure-borne E. coli in streambed sediment: Effects of temperature and sediment properties. Water Research 44:2753-2762.

Gorski, L., C. T. Parker, A. Liang, M. B. Cooley, T. M. Jay-Russell, A. G. Gordus, E. R. Atwill, and R. E. Mandrell. 2011. Prevalence, distribution, and diversity of Salmonella enterica in a major produce region of California. Applied and Environmental Microbiology 77:2734-2748.

Graczyk, T. K., F. E. Lucy, L. Tamang, and A. Miraflor. 2007. Human enteropathogen load in activated sewage sludge and corresponding sewage sludge end products. Applied and Environmental Microbiology 73:2013-2015.

Graham, J. P., and K. E. Nachman. 2010. Managing waste from confined animal feeding operations in the United States: The need for sanitary reform. Journal of Water and Health 8:646-670.

Greene, S. K., E. R. Daly, E. A. Talbot, L. J. Demma, S. Holzbauer, N. J. Patel, T. A. Hill, M. O. Walderhaug, R. M. Hoekstra, M. F. Lynch, and J. A. Painter. 2008. Recurrent multistate outbreak of Salmonella Newport associated with tomatoes from contaminated fields, 2005. Epidemiology & Infection 136:157-165.

Gunn, G. J., I. J. McKendrick, H. E. Ternent, F. Thomson-Carter, G. Foster, and B. A. Synge. 2007. An investigation of factors associated with the prevalence of verocytotoxin producing Escherichia coli O157 shedding in Scottish beef cattle. The Veterinary Journal 174:554-564.

Gutiérrez-Rodriguez, E., A. Gundersen, A. O. Sbodio, and T. V. Suslow. 2011. Variable agronomic practices, cultivar, strain source, and initial contamination dose differentially affect survival of Escherichia coli on spinach. Journal of Applied Microbiology 112:109-118.

Haley, B. J., D. Cole, and E. K. Lipp. 2009. Distribution, diversity and seasonality of water-borne Salmonella in a rural watershed. Applied and Environmental Microbiology 75:1248-1255.

Halweil, B., and D. Nierenberg. 2004. State of the world 2004: Special focus: The consumer society. In Watching what we eat. Washington, DC: The Worldwatch Institute.

Hancock, D. D., T. E. Besser, D. H. Rice, E. D. Ebel, D. E. Herriott, and L. V. Carpenter. 1998. Multiple sources of Escherichia coli O157 in feedlots and dairy farms in the northwestern USA. Preventive Veterinary Medicine 35:11-19.

Hansson, I., N. Pudas, B. Harborn, and E. O. Engvall. 2010. Within-flock variations of Campylobacter loads in caeca and on carcasses from broilers. International Journal of Food Microbiology 141:51-55.

Harwood, V. J., A. D. Levine, T. M. Scott, V. Chivukula, J. Lukasik, S. R. Farrah, and J. B. Rose. 2005. Validity of the indicator organism paradigm for pathogen reduction in reclaimed water and public health protection. Applied and Environmental Microbiology 71:3163-3170.

Henzler, D. J., and H. M. Opitz. 1992. The role of mice in the epizootiology of Salmonella enteritidis infection on chicken layer farms. Avian Diseases 36:625-631.

Heuvelink, A. E., J. T. M. Zwarkruis, C. Van Heerwaarden, B. Arends, V. Stortelder, and E. de Boer. 2008. Pathogenic bacteria and parasites in wildlife and surface water. Tijdschrift Voor Diergeneeskunde 133:330-335.

Hjertqvist, M., A. Johansson, N. Svensson, P. E. Aborn, C. Magnusson, M. Olsson, K. O. Hedlund, and Y. Andersson. 2006. Four outbreaks of norovirus gastroenteritis after consuming raspberries, Sweden, June—August 2006. Eurosurveillance 11(36). http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=3038 (accessed January 6, 2011).

Hodgon, C. J., N. Bulmer, D. R. Chadwick, D. M. Oliver, A. L. Heathwaite, R. D. Fish, and M. Winter. 2009. Establishing relative release kinetics of faecal indicator organisms from different fecal matrices. Letters in Applied Microbiology 49:124-130.

Holt, P. S., C. J. Geden, R. W. Moore, and R. K. Gast. 2007. Isolation of Salmonella enterica serovar Enteritidis from houseflies (Musca domestica) found in rooms containing Salmonella serovar Enteritidis-challenged hens. Applied and Environmental Microbiology 73:6030-6035.

Hutchison, M. L., L. D. Walters, S. M. Avery, B. A. Synge, and A. Moore. 2004. Levels of zoonotic agents in British livestock manures. Letters in Applied Microbiology 39:207-214.

Hutchison, M. L., L. D. Walters, S. M. Avery, F. Munro, and A. Moore. 2005. Analyses of livestock production, waste storage, and pathogen levels and prevalences in farm manures. Applied and Environmental Microbiology 71:1231-1236.

IEH Laboratories & Consulting Group. 2011. IEH isolates outbreak strain of E. coli O157:H7 from deer feces at implicated Oregon strawberry farm. http://www.iehinc.com/article/index.jek8_9_11 (accessed March 13, 2012).

Insulander, M., B. de Jong, B. Svenungsson. 2008. A food-borne outbreak of cryptosporidiosis among guests and staff at a hotel restaurant in Stockholm county, Sweden, September 2008. Eurosurveillance 13(51). http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19071 (accessed January 6, 2011).

Islam, M., M. P. Doyle, S. C. Phatak, P. Millner, and X. Jiang. 2004a. Persistence of entero-hemorrhagic Escherichia coli O157:H7 in soil and on leaf lettuce and parsley grown in fields treated with contaminated manure composts or irrigation water. Journal of Food Protection 67:1365-1370.

Islam, M., J. Morgan, M. P. Doyle, S. C. Phatak, P. Millner, and X. Jiang. 2004b. Persistence of Salmonella enterica serovar Typhimurium on lettuce and parsley and in soils on which they were grown in fields treated with contaminated manure composts or irrigation water. Foodborne Pathogens and Disease 1:27-35.

Islam, M., J. Morgan, M. P. Doyle, S. C. Phatak, P. Millner, and X. Jiang. 2004c. Fate of Salmonella enterica serovar Typhimurium on carrots and radishes grown in fields treated with contaminated manure composts or irrigation water. Applied and Environmental Microbiology 70:2497-2502.

Islam, M., M. P. Doyle, S. C. Phatak, P. Millner, and X. Jiang. 2005. Survival of Escherichia coli O157:H7 in soil and on carrots and onions grown in fields treated with contaminated manure composts or irrigation water. Food Microbiology 22:63-70.

Jagai, J. S., J. K. Griffiths, P. H. Kirshen, P. Webb, and E. N. Naumova. 2010. Patterns of protozoan infections: Spatiotemporal associations with cattle density. EcoHealth 7:33-46.

Jamieson, R. C., R. J. Gordon, K. E. Sharples, G. W. Stratton, and A. Madani. 2002. Movement and persistence of fecal bacteria in agricultural soils and subsurface drainage water: A review. Canadian Biosystems Engineering 44:1.1-1.9.

Jay, M. T., M. Cooley, D. Carychao, G. W. Wiscomb, R. A. Sweitzer, L. Crawford-Miksza, J. A. Farrar, D. K. Lau, J. O’Connell, A. Millington, R. V. Asmundson, E. R. Atwill, and R. E. Mandrell. 2007. Escherichia coli O157:H7 in feral swine near spinach fields and cattle, central California coast. Emerging Infectious Diseases 13:1908-1911.

Jenkins, M. B., J. L. Liotta, A. Lucio-Forster, and D. D. Bowman. 2010. Concentrations, viability, and distribution of Cryptosporidium genotypes in lagoons of swine facilities in the Southern Piedmont and in coastal plain watersheds of Georgia. Applied and Environmental Microbiology 76:5757-5763.

Jeon, B. -W., J. -M. Jeong, G. -Y. Won, H. Park, S. -K. Eo, H. -Y. Kang, J. Hur, and J. H. Lee. 2006. Prevalence and characteristics of Escherichia coli O26 and O111 from cattle in Korea. International Journal of Food Microbiology 110:123-126.

Jimenez, V., P. Drechsel, D. Kone, A. Bahri, L. Raschid-Sally, and M. Qadir. 2010. Wastewater, sludge and excreta use in developing countries: An overview. In Wastewater irrigation and health, edited by C. Drechsel, A. Scott, L. Raschid-Sally, M. Redwood, and A. Bahri. London: Earthscan.

Jo, M.-Y., J.-H. Kim, J.-H. Lim, M.-Y. Kang, H.-B. Koh, Y.-H. Park, D.-Y. Yoon, J.-S. Chae, S.-K. Eo, and J. H. Lee. 2004. Prevalence and characteristics of Escherichia coli O157 from major food animals in Korea. International Journal of Food Microbiology 95:41-49.

Johnson, J. Y. M., J. E. Thomas, T. A. Graham, I. Townshend, J. Byrne, L. B. Sellinger, and V. P. J. Gannon. 2003. Prevalence of Escherichia coli O157:H7 and Salmonella spp. in surface waters of southern Alberta and its relation to manure sources. Canadian Journal of Microbiology 49:326-335.

Johnson, R. 2012. The U.S. Trade Situation for Fruit and Vegetable Products. Congressional Research Service Report 7-5700. January 25, 2012. http://www.nationalaglawcenter.org/assets/crs/RL34468.pdf (accessed March 15, 2012). Johnston, L. M., L.-A. Jaykus, D. Moll, J. Anciso, B. Mora, and C. L. Moe. 2006. A field study of the microbiological quality of fresh produce of domestic and Mexican origin. International Journal of Food Microbiology 112:83-95.

Kauffman, M. D., and J. LeJeune. 2011. European starlings (Sturnus vulgaris) challenged with Escherichia coli O157 can carry and transmit the human pathogen to cattle. Letters in Applied Microbiology 53:596-601.

Kijima-Tanaka, M., K. Ishihara, A. Kojima, A. Morioka, R. Nagata, M. Kawanishi, M. Nakazawa, Y. Tamura, and T. Takahashi. 2005. A national surveillance of Shiga toxin-producing Escherichia coli in food-producing animals in Japan. Journal of Veterinary Medicine B 52:230-237.

Kijlstra, A., B. Meerburg, J. Cornelissen, S. De Craeye, P. Vereijken, and E. Jongert. 2008. The role of rodents and shrews in the transmission of Toxoplasma gondii to pigs. Veterinary Parasitology 156:183-190.

Kim, M., J. A. Thurston, and L. J. Hagen. 2008. Computational fluid dynamics (CFD) modeling to predict bioaerosol transport behavior during center pivot wastewater irrigation. Presented at the ASABE Annual International Meeting, Minneapolis, MN. Paper No. 074063.

Kirk, M. C., K. Fullerton, and J. Gregory. 2008. Fresh produce outbreaks in Australia 2001-2006. Board 21. In 2008 International Conference on Emerging Infectious Diseases Program and Abstracts Book. Atlanta, GA: CDC. Pp. 49-50.

Kishima, M., I. Uchida, T. Namimatsu, T. Osumi, S. Takahashi, K. Tanaka, H. Aoki, K. Matsuura, and K. Yamamoto. 2008. Nationwide surveillance of Salmonella in the faeces of pigs in Japan. Zoonoses Public Health 55:139-144.

Klein, M., L. Borwn, R. W. Tucker, N. J. Ashbolt, R. M. Stuetz, and D. J. Roser. 2010. Diversity and abundance of zoonotic pathogens and indicators in manures of feedlot cattle in Australia. Applied and Environmental Microbiology 76:6947-6950.

Knox, J. W., S. F. Tyrrel, A. Daccache, and E. K. Weatherhead. 2011. A geospatial approach to assessing microbiological water quality risks associated with irrigation abstraction. Water and Environment Journal 25:282-289.

Kopanic, R. J., Jr., B. W. Sheldon, and C. G. Wright. 1994. Cockroaches as vectors of Salmonella: Laboratory and field trials. Journal of Food Protection 57:125-132.

Kozan, E., B. Gonenc, O. Sarimehmetoglu, and H. Aycicek. 2005. Prevalence of helminth eggs on raw vegetables used for salads. Food Control 16:239-242.

Kuhnert, P., C. R. Dubosson, M. Roesch, E. Homfeld, M. G. Doherr, and J. W. Blum. 2005. Prevalence and risk-factor analysis of Shiga toxigenic Escherichia coli in faecal samples of organically and conventionally farmed dairy cattle. Veterinary Microbiology 109:37-45.

Kullas, H., M. Coles, J. Rhyan, and L. Clark. 2002. Prevalence of Escherichia coli serogroups and human virulence factors in feces of urban Canada geese (Branta canadensis). International Journal of Environmental Health Research 12:153-162.

Le Bouquin, S., V. Allain, S. Rouxel, I. Petetin, M. Picherot, V. Michel, and M. Chemaly. 2010. Prevalence and risk factors for Salmonella spp. contamination in French broiler-chicken flocks at the end of the rearing period. Preventive Veterinary Medicine 97:245-251.

LeJeune, J. T., D. Hancock, Y. Wasteson, E. Skjerve, and A. M. Urdahl. 2006. Comparison of E. coli O157 and Shiga toxin-encoding genes (stx) prevalence between Ohio, USA and Norwegian dairy cattle. International Journal of Food Microbiology 109:19-24.

Lewis, D. J., E. R. Atwill, M. S. Lennox, M. D. G. Pereira, W. A. Miller, P. A. Conrad, and K. W. Tate. 2010. Management of microbial contamination in storm runoff from California coastal dairy pastures. Journal of Environmental Quality 39:1782-1789.

Lewis, H. C., S. Ethelberg, K. E. P. Olsen, E. M. Nielsen, M. Lisby, S. B. Madsen, J. Boel, R. Stafford, M. Kirk, H. V. Smith, S. Tikumrum, A. Wisetrojana, A. Bangtrakulnonth, J. Vithayarungruangsri, P. Siriarayaporn, K. Ungchusak, J. Bishop, and K. Mølbak. 2009. Outbreaks of Shigella sonnei infections in Denmark and Australia linked to consumption of imported raw baby corn. Epidemiology & Infection 137:326-334.

LGMA (Leafy Green Marketing Agreement). 2012. Commodity specific food safety guidelines for the production and harvest of lettuce and leafy greens. January 20. http://www.caleafygreens.ca.gov/sites/default/files/01.20.12%20CALGMA%20GAPs%20-%20metrics.pdf (accessed March 14, 2012).

Li, X., E. Atwill, T. Vodovoz, E. Vivas, C. Xiao, C. Kilonzo, M. Jay-Russell, and T. Nguyen. 2011. Cryptosporidium spp. in wild rodent populations adjacent to produce production fields. IAFP Annual Meeting Abstracts, Madison, WI, P1-119.

Lienemann, T., T. Niskanen, S. Guedes, A. Siitonen, M. Kuusi, and R. Rimhanen-Finne. 2011. Iceberg lettuce as suggested source of a nationwide outbreak caused by two Salmonella serotypes, Newport and Reading, in Finland in 2008. Journal of Food Protection 74:1035-1040.

Lomonaco, S., L. Decastelli, D. M. Bianchi, D. Nucera, M. A. Grassi, V. Sperone, and T. Civera. 2009. Detection of Salmonella in finishing pigs on farm and at slaughter in Piedmont, Italy. Zoonoses and Public Health 56:137-144.

Loncarevic, S., G. S. Johannessen, and L. M. Rørvik. 2005. Bacteriological quality of organically grown leaf lettuce in Norway. Letters in Applied Microbiology 41:186-189.

Lowell, K., J. Langholz, and D. Stuart. 2010. Co-managing food safety and ecological health in California’s Central Coast region. http://caff.org/wp-content/uploads/2011/09/Safe_Sustainable1.pdf (accessed March 13, 2012).

Lynch, M. F., R. V. Tauxe, and C. W. Hedberg. 2009. The growing burden of foodborne outbreaks due to contaminated fresh produce: Risks and opportunities. Epidemiology & Infection 137:307-315.

MacDonald, J. M., M. O Ribaudo, M. J. Livingston, J. Beckman, and W. Huang. 2009. Manure use for fertilizer and for energy report to Congress. USDA Report AP-037. http://www.ers.usda.gov/Publications/AP/AP037/AP037.pdf (accessed March 11, 2012).

Madden, R. H., K. A. Murray, and A. Gilmour. 2007. Carriage of four bacterial pathogens by beef cattle in Northern Ireland at time of slaughter. Letters in Applied Microbiology 44:115-119.

McMahon, M. A. S., and I. G. Wilson. 2001. The occurrence of enteric pathogens and Aeromonas species in organic vegetables. International Journal of Food Microbiology 70:155-162.

Miko, A., K. Pries, S. Haby, K. Steege, N. Albrecht, G. Krause, and L. Beutin. 2009. Assessment of Shiga toxin-producing Escherichia coli isolates from wildlife meat as potential pathogens for humans. Applied and Environmental Microbiology 75:6462-6470.

Millner, P. D. 2009. Bioaerosols associated with animal production operations. Bioresource Technology 100:5379-5385.

Mishra, A., B. L. Benham, and S. Mostaghimi. 2008. Bacterial transport from agricultural lands fertilized with animal manure. Water, Air, & Soil Pollution 189:127-134.

Moriarty, E. M., L. W. Sinton, M. L. Mackenzie, N. Karki, and D. R. Wood. 2008. A survey of enteric bacteria and protozoans in fresh bovine feces on New Zealand dairy farms. Journal of Applied Microbiology 105:2015-2025.

Moyne, A.-L., M. R. Sudarshana, T. Blessington, S. T. Koike, M. D. Cahn, and L. J. Harris. 2011. Fate of Escherichia coli O157:H7 in field-inoculated lettuce. Food Microbiology 25:1417-1425.

Mukherjee, A., D. Speh, E. Dyck, and F. Diez-Gonzalez. 2004. Preharvest evaluation of coliforms, Escherichia coli O157:H7 in organic and conventional produce grown by Minnesota farmers. Journal of Food Protection 67:894-900.

Mukherjee, A., D. Speh, A. T. Jones, K. M. Buesing, and F. Diez-Gonzalez. 2006. Longitudinal microbiological survey of fresh produce grown by farmers in the Upper Midwest. Journal of Food Protection 69:1928-1936.

Munnoch, S. A., K. Ward, S. Sheridan, G. J. Fitzsimmons, C. T. Shadbolt, J. P. Piispanen, Q. Wang, T. J. Ward, T. L. M. Worgan, C. Oxenford, J. A. Musto, J. Mcanulty, and D. N. Durrheim. 2009. A multistate outbreak of Salmonella Saintpaul in Australia associated with cantaloupe consumption. Epidemiology & Infection 137:367-374.

Okago, C. N., V. J. Uoh, and M. Galadima. 2003. Occurrence of pathogens on vegetables harvested from soils irrigated with contaminated streams. Science of the Total Environment 311:49-56.

Oliveira, M., J. Usall, I. Viñas, M. Anguera, F. Gatius, and M. Abadias. 2010. Microbiological quality of fresh lettuce from organic and conventional production. Food Microbiology 27:679-684.

Olsen, A. R., and T. S. Hammack. 2000. Isolation of Salmonella spp. from the housefly Musca domestica L., and the dump fly, Hydrotaea aenescens (Wiedemann) (Diptera: Muscidae) at caged-layer houses. Journal of Food Protection 63:958-960.

Omeira, N., E. K. Barbour, P. A. Nehme, S. K. Hamadeh, R. Zuray, and I. Bashour. 2006. Microbiological and chemical properties of litter from different chicken types and production systems. Science of the Total Environment 367:156-162.

Oporto, B., J. I. Esteban, G. Aduriz, R. A. Juste, and A. Hurtado. 2008. Escherichia coli O157:H7 and non-O157 Shiga toxin-producing E. coli in healthy cattle, sheep, and swine herds in northern Spain. Zoonoses Public Health 55:73-81.

Patchanee, P., B. Molla, N. White, D. E. Line, and W. A. Gebreyes. 2010. Tracking Salmonella contamination in various watersheds and phenotypic and genotypic diversity. Foodborne Pathogens and Disease 7:1113-1120.

Pezzoli, L., R. Elson, C. L. Little, H. Yip, I. Fisher, R. Yishai, E. Anis, L. Valinsky, M. Biggerstaff, N. Patel, H. Mather, D. J. Brown, J. E. Coia, W. van Pelt, E. M. Nielsen, S. Ethelberg, E. de Pinna, M. D. Hampton, T. Peters, and J. Threlfall. 2008. Packed with Salmonella—investigation of an international outbreak of Salmonella Senftenberg infection linked to contamination of prepacked basil in 2007. Foodborne Pathogens and Disease 5:661-668.

Pillai, S. D., and S. C. Ricke. 2002. Bioaerosols from municipal and animal wastes: Background and contemporary issues. Canadian Journal of Microbiology 48:681-696.

Quiroz-Santiago, C., O. R. Rodas-Suárez, C. R. Vázquez, F. J. Fernández, E. I. Quiñones-Ramírez, and C. Vázquez-Salinas. 2009. Prevalence of Salmonella in vegetables from Mexico. Journal of Food Protection 72:1279-1282.

Rai, P. K., and B. D. Tripathi. 2007. Microbial contamination in vegetables due to irrigation with partially treated municipal wastewater in a tropical city. International Journal of Environmental Health Research 17:389-395.

Ravel, A., J. Grieg, C. Tinga, E. Todd, G. Campbell, M. Cassidy, B. Marshall, and E. Pollari. 2009. Exploring historical Canadian foodborne outbreak data sets for human illness attribution. Journal of Food Protection 72:1963-1976.

Renter, D. G., D. P. Gnad, J. M. Sargeant, and S. E. Hygnstrom. 2006. Prevalence and serovars of Salmonella in the feces of free-ranging white-tailed deer (Odocoileus virginianus) in Nebraska. Journal of Wildlife Diseases 42:699-703.

Renter, D. G., V. Bohaychuk, J. Van Donkersgoed, and R. King. 2007. Presence of non-O157 Shiga toxin-producing Escherichia coli in feces from feedlot cattle in Alberta and absence on corresponding beef carcasses. Canadian Journal of Veterinary Research 71:230-235.

Rimhanen-Finne, R., T. Niskanen, S. Hallanvuo, P. Makary, K. Haukka, S. Pajunen, A. Siitonen, R. Ristolainen, H. Pöyry, J. Ollgren, and M. Kuusi. 2009. Yersinia pseudotuberculosis causing a large outbreak associated with carrots in Finland, 2006. Epidemiology & Infection 137:342-347.

Rodriguez, A., P. Pangloli, H. A. Richards, J. R. Mount, and F. A. Draughon. 2006. Prevalence of Salmonella in diverse environmental farm samples. Journal of Food Protection 69:2576-2580.

Sagoo, S. K., C. L. Little, and R. T. Mitchell. 2001. The microbiological examination of ready-to-eat organic vegetables from retail establishments. Letters in Applied Microbiology 33:434-439.

Sagoo, S. K., C. L. Little, L. Ward, I. A. Gillespie, and R. T. Mitchell. 2003a. Microbiological study of ready-to-eat salad vegetables from retail establishments uncovers a national outbreak of Salmonellosis. Journal of Food Protection 66:403-409.

Sagoo, S. K., C. L. Little, and R. T. Mitchell. 2003b. Microbiological quality of open ready-to-eat salad vegetables: Effectiveness of food hygiene training of management. Journal of Food Protection 66:1581-1586.

Saini, R., L. J. Halverson, and J. C. Lorimar. 2003. Rainfall timing and frequency influence on leaching of Escherichia coli RS2G through soil following manure application. Journal of Environmental Quality 32:1865-1872.

Salleh, N. A., G. Rusul, Z. Hassan, A. Reezal, S. H. Isa, M. Nishibuchi, and S. Radu. 2003. Incidence of Salmonella spp. in raw vegetables in Selangor, Malaysia. Food Control 14:475-479.

Sánchez, S., R. Martínez, A. García, D. Vidal, J. Blanco, M. Blanco, J. E. Blanco, A. Mora, S. Herrera-León, A. Echeita, J. M. Alonso, and J. Rey. 2010. Detection and characterization of O157:H7 and non-O157 Shiga toxin-producing Escherichia coli in wild boars. Veterinary Microbiology 143:420-423.

Santos, F. B. O., X. Li, J. B. Payne, and B. W. Sheldon. 2005. Estimation of most probable number Salmonella populations on commercial North Carolina turkey farms. Journal of Applied Poultry Research 14:700-708.

Sargeant, J. M., M. W. Sanderson, R. A. Smith, and D. D. Griffin. 2004. Associations between management, climate, and Escherichia coli O157 in the faeces of feedlot cattle in the Midwestern USA. Preventive Veterinary Medicine 66:175-206.

Scaife, H. R., D. Cowan, J. Finney, S. F. Kinghorn-Perry, and B. Crook. 2006. Wild rabbits ( Oryctolagus cuniculus) as potential carriers of verocytotoxin-producing Escherichia coli. Veterinary Record 159:175-178.

Semenov, A. V., L. van Overbeek, and A. H. C. van Bruggen. 2009. Percolation and survival of Escherichia coli O157:H7 and Salmonella enterica serovar Typhimurium in soil amended with contaminated dairy manure or slurry. Applied and Environmental Microbiology 75:3206-3215.

Seo, Y. H., J. H. Jang, and K. D. Moon. 2010. Microbial evaluation of minimally processed vegetables and sprouts produced in Seoul, Korea. Food Science and Biotechnology 19:1282-1288.

Skov, M. N., J. J. Madsen, C. Rahbek, J. Lodal, J. B. Jespersen, J. C. Jørgensen, H. H. Dietz, M. Chriél, and D. L. Baggesen. 2008. Transmission of Salmonella between wildlife and meat-production animals in Denmark. Journal of Applied Microbiology 105:1558-1568.

Smith, B. D., M. R. James, P. Millner, F. M. Hashem, C. P. Cotton, and L. E. Marsh. 2012. Pathogen aerosolization and deposition onto nearby leafy greens through various farm operations. Presented at Human Pathogens on Plants Workshop, College Park, MD, February 13-15. Abstract for Poster #14.

Sneed, J. 2010. Safety of fresh fruits and vegetables. Presentation for Association of State and Territorial Public Health Nutrition Directors, October 28. http://www.astphnd.org/resource_files/246/246_resource_file1.pdf (accessed March 8, 2012).

Sproston, E. L., M. Macrae, I. D. Ogden, M. J. Wilson, and N. J. C. Strachan. 2006. Slugs: Potential novel vectors of Escherichia coli O157. Applied and Environmental Microbiology 72:144-149.

Stephens, T. P., T. A. McAllister, and K. Stanford. 2009. Perineal swabs reveal effect of super shedders on the transmission of Escherichia coli O157:H7 in commercial feedlots. Journal of Animal Science 87:4151-4160.

Talley, J. L., A. C. Wayadande, L. P. Wasala, A. C. Gerry, J. Fletcher, U. DeSilva, and S. E. Gilliland. 2009. Association of Escherichia coli O157:H7 with filth flies captured in leafy green fields and experimental transmission of E. coli O157:H7 to spinach leaves by house flies. Journal of Food Protection 72:1547-1552.

Thunberg, R. L., T. T. Tran, R. W. Bennett, R. N. Matthews, and N. Belay. 2002. Microbial evaluation of selected fresh produce obtained at retail markets. Journal of Food Protection 65:677-682.

Thurston-Enriquez, J. A., P. Watt, S. E. Dowd, R. Enriquez, I. L. Pepper, and C. P. Gerba. 2002. Detection of protozoan parasites and microsporidia in irrigation waters used for crop production. Journal of Food Protection 65:378-382.

Tserendorj, A., A. J. Anceno, E. R. Houpt, C. R. Icenhour, O. Sethabutr, C. S. Mason, and O. V. Shipin. 2011. Molecular techniques in ecohealth research toolkit: Facilitating estimation of aggregate gastroenteritis burden in an irrigated periurban landscape. EcoHealth 8:349-364.

Turutoglu, H., D. Ozturk, L. Guler, and F. Pehlivanoglu. 2007. Presence and characteristics of sorbitol-negative Escherichia coli O157 in healthy sheep faeces. Veterinarni Medicina 52:301-307.

Tyrrel, S. F., and J. N. Quinton. 2003. Overland flow transport of pathogens from agricultural land receiving fecal wastes. Journal of Applied Microbiology 94:87S-93S.

USDA (U.S. Department of Agriculture). 2007. Microbiological Data Program progress update and 2009 data summary. http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELPRDC5067866 (accessed January 25, 2011).

———. 2008. Microbiological Data Program progress update and 2009 data summary. http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELPRDC5079908 (accessed January 25, 2011).

———. 2009. Microbiological Data Program progress update and 2009 data summary. http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELPRDC5088761 (accessed January 25, 2011.

USDA NASS (National Agriculture Statistics Service). 2009. 2007 Census of Agriculture. Farm and Ranch Irrigation Survey. http://www.agcensus.usda.gov/Publications/2007/Online_Highlights/Farm_and_Ranch_Irrigation_Survey/index.php (accessed March 12, 2012).

Van Hoorebeke, S., F. Van Immerseel, J. De Vylder, R. Ducatelle, F. Haesebrouck, F. Pasmans, A. de Kruif, and J. Dewulf. 2009. Faecal sampling underestimates the actual prevalence of Salmonella in laying hen flocks. Zoonoses Public Health 56:471-476.

Viswanathan, P., and R. Kaur. 2001. Prevalence and growth of pathogens on salad vegetables, fruits, and sprouts. International Journal of Hygiene and Environmental Health 203:205-213.

Walker, C., X. Shi, M. Sanderson, J. Sargeant, and T. G. Nagaraja. 2010. Prevalence of Escherichia coli O157:H7 in gut contents of beef cattle at slaughter. Foodborne Pathogens and Disease 7:249-255.

Wang, F., Z. Dou, W. Ma, and F. Zhang. 2005. Challenges and opportunities of animal waste management in China. Proceedings of 2005 America Animal Waste Management Symposium. Pp.704-709.

Wasteson, Y., G. S. Johannessen, T. Bruheim, A. M. Urdahl, K. O’Sullivan, and L. M. Rørvik. 2005. Fluctuations in the occurrence of Escherichia coli O157:H7 on a Norwegian farm. Letters in Applied Microbiology 40:373-377.

Wilkes, G., T. A. Edge, V. P. J. Gannon, C. Jokinen, E. Lyautey, N. F. Neumann, N. Ruecker, A. Scott, M. Sunohara, E. Topp, and D. R. Lapen. 2011. Associations among pathogenic bacteria, parasites, and environmental and land use factors in multiple mixed-use watersheds. Water Research 45:5807-5825.

Williams, M. L., D. L. Pearl, and J. T. LeJeune. 2011. Multiple-locus variable-nucleotide tandem repeat subtype analysis implicates European starlings as biological vectors for Escherichia coli O157:H7 in Ohio, USA. Journal of Applied Microbiology 111:982-988.

Woerner, D. R., J. R. Ranson, J. N. Sofos, G. A. Dewell, G. C. Smith, M. D. Salman, and K. E. Belk. 2006. Determining the prevalence of Escherichia coli O157 in cattle and beef from the feedlot to the cooler. Journal of Food Protection 69:2824-2837.

WHO (World Health Organization). 2011. Outbreaks of E. coli O104:H4 infection: Update 30. July 22, 2011. http://www.euro.who.int/en/what-we-do/health-topics/emergencies/international-health-regulations/news/news/2011/07/outbreaks-of-e.-coli-o104h4-infection-update-30 (accessed March 10, 2012).

A4

ONE HEALTH AND FOOD SAFETY—THE CANADIAN EXPERIENCE:
A HOLISTIC APPROACH TOWARD ENTERIC BACTERIAL PATHOGENS AND ANTIMICROBIAL RESISTANCE SURVEILLANCE

Jane Parmley,⁵Zee Leung,⁶David Léger,⁵Rita Finley,⁷Rebecca Irwin,⁵Katarina Pintar,⁵Frank Pollari,⁷Richard Reid-Smith,^5,6David Waltner-Toews,^6,8Mohamad Karmali,⁵and Rainer Engelhardt⁹

Introduction

This paper describes a holistic approach to the prevention and control of human food-borne illness from enteric pathogens, based on implementation of the “One Health” paradigm. Antimicrobial resistance (AMR) has been chosen as a particular illustrative theme for this overview to demonstrate the practical utility of a One Health approach.

The rapid emergence, global spread, morbidity, and mortality associated with emerging infections such as severe acute respiratory syndrome and avian and pandemic influenza is stimulating the global community to develop novel approaches for their prevention and control. Ongoing concerns about food-borne pathogens such as Escherichia coli O157:H7, Listeria monocytogenes, and various species of Salmonella, as well as the arrival and impact of new strains of food-borne pathogens such as E. coli O104 as observed during the 2011 outbreak in Germany, add to the need to take into account the complexity of infection from multiple dimensions. These include the following:

1. Burden of illness. The World Health Organization estimates that infectious and parasitic diseases are the second leading cause of death in the world (WHO, 2008). Enteric pathogens are the third leading cause of infectious disease worldwide and account for almost 2 million deaths every year ( Girard et al., 2006). As in many other countries, these pathogens also cause a significant disease burden in Canada, where there are an estimated 11 million food-borne enteric illnesses per year with an estimated cost of $3.7 billion dollars (Thomas et al., 2008). Although microbial enteric illness can be caused by bacteria, viruses, parasites, and protozoal organisms, bacteria play a major role in enteric disease (Girard et al., 2006)

_______________

⁵ Laboratory for Foodborne Zoonoses, Public Health Agency of Canada.

⁶ Department of Population Medicine, University of Guelph.

⁷ Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada.

⁸ Veterinarians without Borders/Vétérinaires sans Frontières, Canada.

⁹ Public Health Agency of Canada.

and are the major focus of enteric surveillance programs. Although most enteric bacterial infections result in subclinical or mild illness, their high rate of incidence in the population can be expected to have economic impact on a country simply through loss of short-term individual productivity. In addition, bacterial infections can cause severe disease, particularly in children, the elderly, and immunosuppressed individuals.

2. Zoonotic and environmental origins. More than 60 percent of new emerging and reemerging pathogens of humans, including those that are transmitted by food and water, arise from animals and the environment (Jones et al., 2008). The rate of emergence appears to be increasing, most likely related to factors such as human population growth, changing patterns of international trade, globalization, mass population migrations, climate change, and environmental degradation. With regard to food safety pathogens, it is anticipated that the increased industrialization of animal production, as is seen worldwide in both developed and developing countries, creates an environment for increased opportunity for entry of pathogens into the food chain.

3. Antimicrobial resistance. The severity of infections and our success in treating the associated clinical diseases are affected by the presence of antimicrobial resistance. Antimicrobial-resistant bacteria are those that are able to replicate in the presence of antimicrobials, here meaning antibiotics and their synthetic derivatives, at levels that normally suppress growth or kill the bacteria. Antimicrobial resistance is a growing concern that threatens animal and human health worldwide, driven mainly by antimicrobial use, both appropriate and inappropriate.

The One Health Paradigm

“One Health” has emerged as a strategic framework for reducing the risks of infectious diseases arising from the animal—human—ecosystems interface. Although a universal definition of One Health has not been achieved, and there are overlaps with integrative approaches used in international research and development, such as “ecosystem approaches to health” (Charron, 2011), there is consensus that One Health is an approach or method of practice that recognizes linkages among human, animal, ecosystem, and economic domains in the context of human health.

The One Health approach focuses on the dynamic interactions at the interfaces between multiple sectors that contribute to the expression of a public health risk. In that interactive context, the approach becomes a tool for disease prevention and control through more informed risk management, encompassing the separate elements of identification, assessment, avoidance, and mitigation of the public health risk. It is worth noting that One Health is bigger than the zoonotic infectious disease issues described below, and incorporates socioeconomic, cultural,

and community conditions (the social determinants of health), as well as individual lifestyle and hereditary health factors.

The economic relevance of early and comprehensive intervention is often overlooked, but can be significant. For instance, the direct economic impacts of individual zoonotic disease events that have occurred over the past 15 years can be in the billions (Figure A4-1).

Canada has been actively engaged in operationalizing the One Health concept through the development of a community of practice by participating and supporting international conferences encompassing the subject. The Public Health Agency of Canada, recognizing the emerging value of the One Health paradigm, hosted an Expert International Consultation on “One World One Health^TM: from Ideas to Action,” March 16-19, 2009, in Winnipeg, Manitoba (http://www.phac-aspc.gc.ca/publicat/2009/er-rc/index-eng.php). Many other major international meetings have helped define One Health, most recently, in November 2011, the High Level Technical Meeting on Health Risks at the Human—Animal—Ecosystems Interfaces in Mexico City. Upcoming is a meeting scheduled for February 2012 in Davos, Switzerland: Global Risk Forum One Health Summit 2012: One Health—One Planet—One Future.

One Health in relation to food safety has multiple dimensions, including science and research, optimizing animal health and ecosystem health, and food inspection and regulatory activities. In Canada work in this area is conducted by several federal government agencies, such as the Public Health Agency of Canada (surveillance, research, and epidemiology of food-borne illness), the Canadian

FIGURE A4-1 Economic impact examples.

SOURCE: Newcomb et al. (2011).

Food Inspection Agency (animal health and food inspection), Health Canada (food safety regulations and risk assessment), and Agriculture and AgriFood Canada (food animal production). Canada’s provincial and territorial jurisdictions have also started to embrace a One Health approach; for instance, Manitoba has a primer on One Health and food safety and has developed an animal health and food safety strategy for the future (“Protecting Animals, Food and People”), and Québec has an animal health and welfare strategy (“One Health, Health for All”). The Canadian academic sector is a critical contributor to the theme, particularly its five veterinary colleges.

Science and research activities include surveillance, detection, and public health risk assessment of nonhuman bacterial isolates, studies on the population and environmental determinants of food-borne zoonoses, systems modeling of the food chain to identify optimal points of intervention, development of intervention strategies such as vaccines and bacteriophage products, and knowledge translation for uptake by food production and processing workers. The activities also include characterization of impacts of particular practices, such as the use of antibiotics in commercial food animal production and its potential in giving rise to antimicrobial resistance in bacteria pathogenic to humans.

Mechanisms of Antimicrobial Resistance

Resistance can be intrinsic, conferred by naturally occurring characteristics of the bacteria, or acquired. Bacteria can acquire resistance through mutations of preexisting genes or through transfer of resistance determinants from other bacteria (horizontal gene transfer). Horizontal transfer occurs much more commonly than de novo development of resistance through mutation (White et al., 2008). It is through horizontal gene transfer that resistance genes, alone or in groups, can spread within bacterial populations and even to other bacterial species.

Resistance genes provide the molecular tools by which bacteria block or oppose the mechanism of action of antimicrobials. Some genes allow bacteria to physically modify their structure to evade drugs, while other genes express enzymes to directly degrade the antimicrobial agent. In addition, resistance mechanisms that are not specific to antimicrobial agents can also be present. For example, cell pumps that allow bacteria to excrete environmental toxins and prevent them from reaching harmful intracellular concentrations can also help bacteria to resist the harmful effects of antimicrobials.

Not all antimicrobial-resistant bacteria are harmful, and resistance genes can be found in nonpathogenic bacteria (Wright, 2007). However, these benign but resistant bacteria may also pose a threat through the transfer of resistance genes to pathogenic bacteria (Figure A4-2).

FIGURE A4-2 Transfer model for antimicrobial resistance genes.

Antimicrobial Usage and Resistance

Antimicrobial use (AMU) in animal and human populations is considered to be the major driver of AMR emergence and persistence. Use of antimicrobials exerts a powerful selective influence on bacteria, encouraging the survival and propagation of resistant strains and influencing how quickly AMR develops. Because different resistance genes are often clustered close together on the bacterial genome, especially on transmissible genetic elements such as plasmids and transposons, selection for resistance against one type of antimicrobial may also co-select for resistance against other unrelated antimicrobials. In addition, use of one antimicrobial can select for resistance to closely related antimicrobials (cross-resistance). For example, in Europe, use of avoparcin, an antimicrobial growth promoter used in food animals, has been linked with resistance to vancomycin, an antimicrobial “of last resort” in human medicine (Kruse et al., 1999).

Genetic mechanisms leading to the development and maintenance of AMR are complex. At one time, is was thought that AMR universally negatively im-

pacted the fitness of microorganisms and that, by removing the selective pressure imposed by antimicrobial usage, resistance genes would be selected against in future bacterial generations. However, Wright (2007) identified several genetic mechanisms that may be exceptions to this rule: resistance genes that increase fitness, resistance genes that do not have a fitness cost, and compensatory mutations that restore bacterial fitness. Finally, environmental factors may play a large role in the persistence of “unused” antimicrobial resistance genes. Selection of genes conferring protection against environmental stressors such as heavy metals and biocides may also co-select for resistance genes (Alonso et al., 2001).

The genetic regulation of AMR is complex and not fully understood. Despite our gaps in knowledge, prudent AMU and adherence to the principles of good anti microbial stewardship are recommended as key elements in a strategy directed at preserving the efficacy of antimicrobials, particularly those that are very important to human and veterinary medicine.

A Holistic Consideration of AMR and Enteric Disease

Figure A4-3 depicts the complex interactions between enteric organisms, animals, and humans, and the many determinants (socioeconomic, environmental, and geopolitical) that affect these relationships. Antimicrobial-resistant bacteria form the central component of our model. A number of different interactions can be described using this model, some of which require greater insight into their mechanisms and importance. For example, certain bacteria that cause disease in animal hosts may not cause disease in people but may exchange genetic material, including resistance genes, with human pathogens, causing community-acquired and nosocomial infections (Guardabassi et al., 2004).

Enteric infections in people generally occur through fecal—oral transmission, of which several risk factors can be identified: increased contact between humans and animals, extended hospitalization, poor hygiene, consumption of improperly handled and improperly cooked foods including meats, and ingestion of contaminated water. Prior treatment with antimicrobials can also increase an individual’s susceptibility to infection by pathogenic bacteria through disruption of the normal bacterial flora and by conferring a competitive advantage to resistant strains of pathogens such as Salmonella (Barza and Travers, 2002).

Previous infections with resistant bacteria can also predispose individuals to future resistant infections and disease. As seen in Figure A4-3, an individual may be infected with a commensal bacterium carrying resistance genes. Maintenance of resistance within the individual may occur through colonization of the gastrointestinal tract with this commensal bacterium or via horizontal transfer to gut flora as shown in the diagram. If this same individual is later infected with a pathogenic bacterium, then resistance may be transferred to this pathogen through horizontal transfer from the gut flora.

FIGURE A4-3 The intersection of enteric agents, animals, and humans, and the environmental factors that influence the occurrence of zoonotic bacterial infections and the emergence of AMR.

Implications on Global Health

A number of provincial and national reports, including the 2002 Walkerton Commission of Inquiry (Government of Ontario) and the 2004 Renewal of Public Health in Canada report (Government of Canada), have advocated for a holistic approach toward understanding enteric disease. This type of approach is especially useful given the complexity of enteric disease and its importance as a global health issue. AMR also has serious implications for global human and animal health.

AMR impairs our ability to treat infectious diseases and endangers the long-term efficacy of antimicrobial drugs available to human and veterinary medicine. Not only are infections caused by resistant bacteria more difficult and more expensive to treat, but also the longer duration of infection may increase disease shedding and spread. AMR thus has important effects on the pathogenicity and epidemiology of zoonotic bacterial agents.

Along with its global health implications, the emergence of resistant bacteria may have broad economic effects. Weakened public confidence over the safety of agricultural commodities, potential inclusion of AMR bacteria as a product adulterant leading to recalls, and changes to consumer buying patterns are major economic concerns to agricultural industries. At the patient level, AMR may reduce the efficacy of certain antimicrobials and thereby increase the cost of infection (e.g., longer hospital stays and changes in AMU for disease treatment and prevention) in people and animals. As discussed by Foster (2009), the economic burden of AMR may be most dramatic in developing nations because of the higher expense of second- or third-line drugs, and the lack of diagnostic capacity to detect resistance early, which may result in treatment failures and complications in antimicrobial selection.

Developing solutions to AMR and enteric disease requires synthesis of knowledge and analysis of data at the local, national, and global scales. Factors such as agricultural land-use patterns, attitudes toward antimicrobial usage, and the nature and extent of interactions between people and animals can have major effects on the development of AMR at the local and national levels. However, these local influences may also have global significance. Global interactions of people, animals, and animal products mean that AMU and the accompanying regulations in one country can affect the efficacy of a particular antimicrobial in another. Similarly, the global epidemiology of enteric pathogens is important in understanding the local burden of enteric disease. For example, it was estimated that 30 percent of all enteric disease cases at a sentinel site in Ontario, Canada, in 2008 were associated with international travel (Government of Canada, 2009).

Application of a Holistic Approach to
Zoonotic Bacterial Infections and AMR in Canada

The Public Health Agency of Canada supports two complementary surveillance programs that together provide a holistic approach to AMR and enteric

disease (Figure A4-3): (1) the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) and (2) the National Integrated Enteric Pathogen Surveillance Program (C-EnterNet). Both were modeled after similar programs in other countries: NARMS (United States) and DANMAP (Denmark) for CIPARS and FoodNet (United States) and OzFoodNet (Australia) for C-EnterNet. The two Canadian programs generate and collect data that contribute to our understanding of the transmission of zoonotic bacteria, risk factors for infection, and the drivers of AMR and AMU. As surveillance systems, their ongoing and systematic designs allow for the identification of emerging trends and the ability to identify the impacts of prevention and control measures adopted at the national, provincial, and, occasionally, local levels in Canada.

Both programs also provide a research platform that aims to identify and understand how livestock husbandry and production methods, water-borne routes of exposure, wildlife, companion animals, exotic pets, and socioeconomic factors and high-risk human populations are affected by and contribute to zoonotic bacterial infections and AMR.

While CIPARS performs epidemiological surveillance on AMR and AMU through the generation and collection of nationwide data from farms, abattoirs, retail stores, and both human and animal diagnostic health laboratories, C-EnterNet performs epidemiological surveillance on enteric pathogens at intensively sampled local sentinel sites (currently one site in Ontario and one in British Columbia). Like CIPARS, C-EnterNet collects data at the level of the farm, retail store, and human community (via epidemiological and laboratory data on human cases in partnership with the local public health unit). C-EnterNet also performs environmental surveillance by collecting and testing untreated water samples. This parallel testing is critical to understanding the complex system of food and water-borne disease transmission. Results from both programs are publicly accessible through the Public Health Agency of Canada website as well as through annual reports and newsletters.

The epidemiological strength of CIPARS lies in its breadth of surveillance at major points along the farm-to-fork continuum. These data allow for temporal and spatial analyses of provincial and national trends in bacterial recovery and AMR. This is best demonstrated with the recent study of Salmonella Heidelberg and ceftiofur resistance (see the section titled Success Within CIPARS: A Case Example). While CIPARS is most effective at studying trends at broad scales, C-EnterNet’s value is in its ability to detect subtle epidemiological effects that may only be captured at the local level. In addition, it is one of the only systems that can delineate endemic versus travel-acquired human infections (see the section titled Success Within C-EnterNet: A Case Example). The sentinel-site surveillance approach provides rich data that would be cost-prohibitive to collect across all of Canada. But, by understanding sentinel populations, the information can be used to determine the predominant sources of enteric pathogens causing

infection and the risk factors (including individual behaviours) that contribute to the burden of enteric illness.

It is important to recognize the unique operational aspects of both CIPARS and C-EnterNet and their complementary nature. Having two different but linked surveillance models that encompass different scales is essential in providing a comprehensive look at the specific risk factors associated with AMR and enteric disease. When considered together, both programs provide a holistic picture of the complex relationships between enteric pathogens, the environment, and the health of humans and animals.

Success Within CIPARS: A Case Example

Recent analysis of CIPARS data identified a link between ceftiofur (an antimicrobial of high importance to human medicine) usage in poultry and ceftiofur-resistant Salmonella Heidelberg isolates obtained from people and chicken meat in Québec (Dutil et al., 2010), as shown in Figure A4-4. Because S. Heidelberg is a common serotype that infects and can cause disease in people, this finding had important human health implications.

Communication of this information led to a voluntary ban on the use of ceftiofur in 2005, and the ongoing collection of surveillance data provided the opportunity to follow trends in human and animal infection and in AMR. The findings from this work have provided strong evidence pointing toward changing patterns in AMU affecting clinical bacterial resistance in human and animal isolates. This study has been used to inform policy on the appropriate use of this antimicrobial and is helping to guide physicians and veterinarians in their selection of appropriate antimicrobials and how these drugs are dispensed.

Success Within C-EnterNet: A Case Example

The C-EnterNet program recently looked at 1,773 reported cases of disease caused by enteropathogens such as Salmonella, Campylobacter, and verotoxigenic Escherichia coli in Sentinel Site 1 (Region of Waterloo, Ontario) (Ravel et al., 2011). C-EnterNet and its local public health partners found that more than one in four reported cases of enteric infection were related to travel, including 9 percent involving new immigrants. The most popular destinations of the patients studied were the Caribbean, Latin America, and Asia.

The finding illustrates that travel-related cases of diseases caused by enteric pathogens represent a significant proportion of the burden of total diseases in Canada. These results will help to delineate domestically acquired infections from those acquired abroad. In the One Health framework, this will help target more effective prevention and control measures domestically, considering a broad suite of pathogens and the complex routes of transmission.

FIGURE A4-4 Ceftiofur resistance in E. coli from retail chicken and S. Heidelberg from retail chicken and humans, CIPARS 2003-2010.

SOURCE: CIPARS (2003, 2004).

Conclusions and Key Policy Implications

The global, transdisciplinary, multiscalar, and multijurisdictional nature of AMR and enteric disease highlights the utility of the One Health approach in framing these health issues. One Health principles encourage public health practitioners to engage and collaborate with stakeholders and to consider the numerous socioeconomic, geopolitical, zoonotic, and environmental factors involved in health issues (Figure A4-2). Veterinarians and physicians as well as other human, animal, and ecosystem health professionals have important roles to play in preserving the efficacy of our antimicrobials through leadership roles in disease surveillance, AMU decision making, and health management decisions to prevent disease. Communication and collaboration with farms, industry, veterinarians, physicians, and other public health practitioners must be strengthened and is emphasized as key to the success of the approach to AMR and enteric disease.

C-EnterNet and CIPARS have successfully operated for 7 and 10 years, respectively. A large part of this success and the sustainability of these programs can be attributed to ongoing collaborations with multiple stakeholders and the flexibility of all the partners to adapt to changing needs and conditions. These programs serve as a model for how government agencies can address, in an integrated fashion, urgent problems and issues that cut across multiple departments and jurisdictions.

Acknowledgments

This article is based, in part, on one of 31 case studies included in One Health for One World: A Compendium of Case Studies, edited by David Waltner-Toews, Veterinarians without Borders/Vétérinaires sans Frontières—Canada, April 2010 (accessed on November 22, 2011, at http://www.vwb-vsf.ca/english/documents/OHOWCompendiumCaseStudies_001.pdf). This compendium was commissioned by the Public Health Agency of Canada (PHAC) and presented by PHAC and the United Nations System Influenza Coordinator at an Inter-ministerial Meeting of the International Partnership on Avian and Pandemic Influenza in Hanoi, Vietnam, in April 2010.

References

Alonso, A., P. Sánchez, and J. L. Martínez. 2001. Environmental selection of antibiotic resistance genes. Environmental Microbiology 3(1):1-9.

Barza, M., and K. Travers. 2002. Excess infections due to antimicrobial resistance: The “Attributable Fraction.” Clinical Infectious Diseases 34(Suppl. 3):S126-S130.

Charron, D. F. (editor). 2011. Ecohealth research in practice: Innovative applications of an ecosystem approach to health. New York: Springer/Ottawa, ON: International Development Research Centre.

Dutil, L., R. Irwin, R. Finley, L. K. Ng, B. Avery, P. Boerlin, A.-M. Bourgault, L. Cole, D. Daignault, A. Desruisseau, W. Demczuk, L. Hoang, G. B. Horsman, J. Ismail, F. Jamieson, A. Maki, A. Pacagnella, and D. R. Pillai. 2010. Ceftiofur resistance in Salmonella enterica serovar Heidelberg from chicken meat and humans, Canada. Emerging Infectious Diseases 16(1):48-53.

Foster, S. D. 2009. The economic burden of resistance in the developing world. In Antimicrobial resistance in developing countries, edited by A. Sosa and D. K. Byarugaba. New York: Springer Science & Business Media.

Girard, M. P., D. Steele, C.-L. Chaignat, and M. P. Kieny. 2006. A review of vaccine research and development: Human enteric infections. Vaccine 24:2732-2750.

Government of Canada. 2004. Learning from SARS: Renewal of public health in Canada. Ottawa, ON: Health Canada.

Government of Canada. 2009. C-EnterNet Short Report 2008. Guelph, ON: Public Health Agency of Canada.

Government of Ontario. 2002. Report of the Walkerton Inquiry: A strategy for safe drinking water. Toronto: Ontario Ministry of the Attorney General.

Guardabassi, L., S. Schwarz, and D. H. Lloyd. 2004. Pet animals as reservoirs of antimicrobial-resistant bacteria. Journal of Antimicrobial Chemotherapy 54:321-332.

Jones, K. E., N. G. Patel, M. A. Levy, A. Storeygard, D. Balk, J. L. Gittleman, and P. Daszak. 2008. Global trends in emerging infectious diseases. Nature 451(7181):990-993.

Kruse, H., B. K. Johansen, L. M. Rørvik, and G. Schaller. 1999. The use of avoparcin as a growth promoter and the occurrence of vancomycin-resistant enterococcus species in Norwegian poultry and swine production. Microbial Drug Resistance 5(2):135-139.

Newcomb, J., T. Harrington, and S. Aldrich. 2011 (unpublished). The economic impact of selected infectious disease outbreaks.

Ravel, A., A. Nesbitt, B. Marshall, N. Sittler, and F. Pollari. 2011. Description and burden of travel-related cases caused by enteropathogens reported in a Canadian community. Journal of Travel Medicine 18(1):8-19.

Thomas, M. K., S. E. Majowicz, F. Pollari, and P. N. Sockett. 2008. Burden of acute gastrointestinal illness in Canada, 1999-2007: Interim summary of NSAGI activities. Canada Communicable Disease Report 34(5):8-13.

White, J. R., P. Escobar-Paramo, E. F. Mongodin, K. E. Nelson, and J. DiRuggiero. 2008. Extensive genome rearrangements and multiple horizontal gene transfers in a population of Pyrococcus isolates from Vulcano Island, Italy. Applied and Environmental Microbiology 74(20):6447-6451.

WHO (World Health Organization). 2008. The global burden of disease: 2004 update. http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_part2.pdf (accessed June 26, 2012).

Wright, G. 2007. The antibiotic resistome: The nexus of chemical and genetic diversity. Nature 5:175-186.

A5

OVERVIEW OF THE GLOBAL FOOD SYSTEM: CHANGES OVER TIME/SPACE AND LESSONS FOR FUTURE FOOD SAFETY

Will Hueston^10,11and Anni McLeod¹⁰

Food systems emerged with the dawn of civilization when agriculture, including the domestication of animals, set the stage for permanent settlements. Inhabitants could grow more crops and raise more animals than necessary to feed those who tended them. This changed human culture; unlike earlier hunter-gatherers, agriculturalists did not need to be in constant motion to find new sources of food. Cultivating grain allowed for drying and storage of some of the harvest for later consumption. Different grain cultures emerged in each of the cradles of civilization: maize in Mexico, rice in China, and wheat and barley in the Middle East. The ability to produce a surplus of grain also set the stage for the development of art, religion, and government.

Since agriculture began, food systems have constantly evolved, each change bringing new advantages and challenges and ever-greater diversity and complexity. This paper looks backward to the drivers of change and forward to the challenges faced by producers, consumers, and policy makers of tomorrow.

Changes Over Time and Space

The emergence of city-states has been a major driver of food system changes, bringing together large populations within defined boundaries and requiring complex governance to deliver sufficient quantities and quality of food. Advances in food storage, with sealed containers and curing methods, the use of animal transport, sailing ships, and trains to move larger volume than can be carried by individuals; trade in ingredients like salt as well as live animals and agricultural products; and increasing political and military conflict for resources all have been developments of the city-state. Extensive trading routes have existed for salt, spices, tea, and pepper for thousands of years.

The Iron Age and the Roman Empire brought expanding empires and the beginning of global food systems, including regional specialization in products traded throughout empires. Food systems began to be organized on a grand scale to feed larger cities and fuel local economies. Trade networks for grain, nuts, oils, fruit, and wine developed using both road systems and sailing routes. Standardized weights and measures were established along with the expansion of money and accounting.

_______________

¹⁰ Global Initiative for Food Systems Leadership.

¹¹ College of Veterinary Medicine and School of Public Health University of Minnesota.

The Middle Ages saw the emergence of the merchant class and banknotes. Prior to the Middle Ages, selling was considered a task for one of the lower classes of civilization, if not a sin. The equestrii in Roman times did the trading, not the citizens of Rome. The Middle Ages also saw banknotes replacing coinage, first with the Song dynasty in China and then later in Europe around 1661. As a wealthy class emerged, they became more sophisticated in their food preferences. The resulting demand of consumers began to affect trade in addition to supply.

Science and technology represent another major driver, changing the way that food is grown, processed, preserved, and transported. The Industrial Age brought a transition from manual labor and draft animal—based economies to machines. Further increases in agricultural productivity brought about by technology such as the seed drill, the iron plow, and the threshing machine freed up labor for the factories in the 1700s. The Industrial Revolution also created per-capita income growth. The emerging middle class had discretionary income to spend on its food preferences. Transportation breakthroughs were ushered in during the industrial age: canal systems, improved roadways, steam engines used for traction, railroads, and steamships. The Erie Canal, as an example, connected the Great Lakes and the northeastern United States with 363 miles of inland waterways by 1825.

Food preservation, important to both storage and transport of food, also changed over time. Drying was one of the early food preservation methods, certainly known in ancient times. Fermentation also was an early method of food preservation, with pasteurization applied to wine in China as early as 1117. Salting of food has been used for at least 500 years, beginning when the fishing fleets from Europe used drying and salting to store fish caught in Newfoundland and the Grand Banks in order to get them back to consumers in Europe.

Two preservation methods, canning and freezing, allowed food to be stored and transported in an almost-fresh state. Canning grew out of military research in 1810. Ice storage was developed in northern climates where ice could be cut from lakes in the winter for use later in the year. Commercial refrigeration followed in the 1800s. The first refrigerated ship, the SS Dunedin in 1882, revolutionized the meat and dairy industries in Australia and New Zealand. Refrigerated and frozen food products now could be traded globally.

The 20th century saw intensification of agricultural production with mechanization of planting and harvesting, selective breeding of animals and plants, and more attention to animal nutrition and feed input costs. Increased scale of production drove down the per-unit cost of products and fostered greater specialization in food systems. Advances in plant and animal disease control also helped, such as the movement of pigs and poultry indoors to decrease disease exposure and to enhance efficiency by controlling the environment.

Colonization and war have been important political influences on food systems, the first creating distributed ownership of food systems and the second highlighting a need for global agreements. Colonialism allowed for population growth of the industrialized countries when there were limited domestic opportunities to create employment or to grow food. Settler colonies captured market opportunities for the colonizing country’s exports and provided import sources for raw materials, including food and food ingredients.

Trade underwent dramatic changes in the 20th century as a result of the two world wars. The war-associated food shortages, economic crises, and disease spread set the stage for global trade agreements and organizations designed to address global public good issues. The 1947 General Agreement on Tariffs and Trade was created to reduce tariff-based trade barriers and to prevent the downward spiral of world trade seen in the Great Depression from 1929 to 1933. Monthly trade dropped from $3.0 billion in January 1929 to $0.9 billion in March 1933 as protectionist measures reduced trade worldwide (Personal communication, Christiane Wolff, World Trade Organization, March 2012).

Supply-driven to demand-driven Until the 20th century many countries had supply-driven economies, where policies favored increased agricultural production to ensure adequate domestic supplies of basic feedstuffs. Increasing the supply and reducing the costs of food were politically popular national priorities. Food self-sufficiency was a powerful motivation, especially for countries that had experienced food shortages in the past. Countries that exceeded domestic demand used export markets and food aid programs to deal with the excess.

Rising discretionary incomes in Europe and North America in the 20th century impacted food demand and global food trade. Rising consumer demand for chicken drove the development of the broiler industry, but, as marketing moved from whole birds to parts such as leg quarters or breasts, demand disequilibrium resulted. For example, many Americans prefer white meat and do not eat chicken feet, while in other parts of the world people prefer dark meat and consider chicken feet a delicacy. Global food trade provided an opportunity to sell the parts of animals for which there is little or no domestic demand. One reason that the developed world enjoys relatively inexpensive food is the ability to market commodities and specialized products worldwide.

Food systems are dynamic and ever changing in response to natural forces (e.g., weather), demographics (e.g., emergence of megacities), economics (e.g., currency values), technological advances in processing (e.g., high pressure pasteurization), entrepreneurism (e.g., development and marketing of new products), and consumer preferences (e.g., locavores). Every country in the world produces some of its own food and trades food. As a result of these constant changes, food systems are increasingly complex, as adding to the challenge of assuring global food safety.

The Complexity of Current Global Food Systems
and Implications for Food Safety

Today’s food systems are diverse and complex, involving everything from subsistence farming to multinational food companies. Everyone eats; therefore, everyone relies on food systems, local and global. The movement of food and food ingredients in food systems includes animals and animal products, plants and plant products, minerals, and vitamins. The classic cheeseburger provides an excellent example of the complexity of today’s supply chain. Researchers at the University of Minnesota mapped the global supply chain of the cheeseburger working with a large quick-service restaurant chain, Figures A5-1, A5-2, and A5-3 tell the story. Figure A5-1 demonstrates graphically the movement of different commodities from the farm through processing to the restaurant. Figure A5-2 lists all the ingredients found in this company’s cheeseburgers and Figure A5-3 provides an idea of the variety of companies supplying key ingredients like vinegar, garlic powder, tomatoes, beef, and wheat gluten. Each cheeseburger includes more than 50 ingredients sourced from countries in every continent of the world except the Arctic.

FIGURE A5-1 Global supply chain complexity. Movement of commodities.

SOURCE: Shaun Kennedy, Director, National Center for Food Protection and Defense, University of Minnesota.

FIGURE A5-2 Global supply chain complexity. Ingredient list.

SOURCE: Shaun Kennedy, Director, National Center for Food Protection and Defense, University of Minnesota.

Food processing supplies also move globally and include processing equipment, packaging, and chemicals such as disinfectants and preservatives. Agricultural inputs move too, from feed to fertilizer, to vaccines and pharmaceuticals, to planting and harvesting equipment. As agricultural commodities are combined with other food ingredients to create processed foods, individual food items commonly include ingredients from multiple countries. The increasing consumer demand for “ready-to-eat” foods has fueled the growth of quick service restaurants and fully cooked, frozen dishes that only require reheating, further expanding supply chains. Government regulatory systems and private-sector initiatives are part of food systems, as are educational efforts and consumer actions.

Food systems are integrally related to food safety. Contamination can occur at any point in the food system, and prevention and control strategies can be implemented at any point. The scale and complexities of today’s food systems contribute to the likelihood and magnitude of food-borne illness (Ercsey-Ravasz et al., 2012). The more complex, the more opportunities for things to go wrong; the larger the scale, the more people are potentially affected.

Complex food systems each involve interconnected subsystems that, taken together, exhibit properties that are not predictable by the properties of the indi-

FIGURE A5-3 Globalizing the cheeseburger.

SOURCE: Shaun Kennedy, Director, National Center for Food Protection and Defense, University of Minnesota.

vidual subsystems or their parts. Food systems can be called complex adaptive systems. These have no boundaries; individual actions affect the food systems by what individuals produce and what they purchase. Complex adaptive systems have a memory. While food systems change over time, present behavior is affected by prior behavior. Food systems are nonlinear. A small perturbation in some part of the system may have a large effect, a proportional effect, or no effect. And the relationships of this system of systems have feedback loops. The adaptiveness and nonlinearity of food systems mean that food safety problems are also nonlinear; they can be anticipated but are hard to predict with accuracy or precision.

Feeding the world requires a multitude of systems. Each system is dynamic and the food systems are interdependent; there is no one best system that meets all needs. However, every success in improving the food system perturbs the whole system of systems and changes the nature of the food safety problems.

Lessons for the Future

Looking at existing global food systems and predicated demands for food, we can reasonably speculate the following over the next 10 to 20 years:

1. Food systems will continue to change, although with additional drivers. The drivers of urbanization, production and processing technology, transport technology, and political forces that have played a large part in shaping current food systems will continue to be relevant. Newer drivers playing an increasingly important part are a real prospect of a global population of 10 billion, aging populations changing the production and consumption base, climate change leading to constraints on water supplies, severe constraints on nonrenewable energy, and communication technology.

2. Food systems will continue to shift from being supply driven to being demand driven. The global quick service restaurant chains like McDonalds and big-box retailers like Walmart have had an enormous impact on food systems. Consumer groups demanding safety, fair trade, “green” production, and animal welfare-related changes in production practices put pressure on policy makers and retailers. The large processors are putting pressure on the primary producers of plants and animals for assurances on source, on identity preservation, on means of production, and on characteristics like animal welfare and labor standards.

3. Increasing prominence of private standards. Successful completion of the Uruguay Round of the multinational trade negotions under the framework of the General Agreement on Tariffs and Trade included approval of the Sanitary and Phytosanitary Agreement (SPS) in 1995 under a new organization, the World Trade Organization (WTO). The SPS established a framework for international standards for trade in animals, plants, and the products derived from them including food. More recently, coalitions of companies are forming to standardize specifications for food products, basically saying, “we can’t wait for the slow process of international standards organizations.” An example is the Global Food Safety Initiative, a nonprofit organization that benchmarks guidelines established by food processors, retail, and food service against the international standards recognized by WTO. Food safety standards used by the large companies who target premium market niches are often above and ahead of the minimum demanded by legislation.

4. Panarchy. The term “panarchy” is used in systems theory to describe systems interlinked in continual adaptive cycles of growth, restructuring, and renewal (Gunderson and Holling, 2001). The increased growth in connectedness and efficiency results in a lack of redundancy and at the same time makes individual food systems less resilient, more sensitive to stress, and therefore more susceptible to collapse. If subsystems within complex food systems collapse, the result is systems with greater resiliency that have fewer connections and less efficiency. And the cycle starts again.
     Food systems have demonstrated adaptive cycles as they have evolved. Many current food systems have evolved to a point where they are both

complex and sensitive to stress, and the results of a collapse in a subsystem can be wide-reaching. For example, the concentration of production of an ingredient like a vitamin in a single company or country may be the most efficient approach, but if a production problem ensues or a disaster disrupts this supply chain, then all food processors using this vitamin as a food ingredient are affected. They must either remove the vitamin from their recipes or stop production because of lack of supply. Another example is the proliferation of “just-in-time” supply chains. Instead of stockpiling food supplies in warehouses, many large food retailers and food services have worked with food manufacturers to establish these supply chains. Real-time data on usage and inventories are provided directly to the supplier on a regular basis to allow for customized shipments of only those food products needed. If the supply chain is disrupted, there is very little food in reserve. Many cities have less than 2 days’ supply of perishable food like milk and eggs on the shelves at retail outlets. People in countries where systems regularly collapse have coping strategies: they store food, water, and alternative energy at home. Many of those in large modern cities do not. The urban poor have neither the finances nor the storage facilities to store reserves of food.

5. Culture clash. Disconnects exist between origination and destination countries because of differences in their cultures and differing levels of economic development. While developed countries have emphasized the importance of food safety and quality, less-developed countries may focus on the opportunity for exports to generate foreign currency reserves. The recent melamine incidents demonstrate economic adulteration in order to achieve greater profit in domestic and international markets.

What Do One Health Approaches Have to Offer Food
Safety in the Context of Food Systems?

Food safety is a “wicked problem.” We cannot completely understand the challenge; it is too complex. And yet food safety is compelling: people are getting sick and dying every day as a result of unsafe food and water. We must take action, and we recognize that every action we take perturbs the very food systems we are working to improve. The so-called wicked problem reflects the condition of a complex adaptive system.

If One Health is taken to imply holistic and multidisciplinary approaches to complex challenges (e.g., wicked problems), then a One Health approach offers the possibility of new perspectives on safety in food systems and new ways of working. It implies systems thinking, shared leadership, a holistic view, and a multifaceted approach.

Is this back to the future? The World Health Organization (WHO) definition of health in 1948 was quite broad: “Health is a state of complete physical,

social, and mental well-being, and not merely the absence of disease or infirmity.” However, the public health implementation of food safety focus often is limited to prevention and response to infectious diseases rather than a more holistic approach to food safety as an element of food security (availability, access, and nutrition as well as safety). More recently, the Food and Agriculture Organization and the WHO have developed a much broader definition of food safety: “All the conditions and measures necessary during production, processing, storage, distribution, and preparation of food to ensure that it is safe, sound, wholesome, and fit for human consumption.”

Successfully applying One Health approaches to food safety requires a sound understanding of the dynamics of food systems. Food safety must be addressed in a systemic manner rather than an ad hoc approach driven by reaction to crises. These One Health approaches have implications for what we record, measure, and analyze in food systems and how we share information about potential food safety problems as well as existing crises.

One Health approaches also require a new leadership model that is adaptive and shared, matching the adaptive nature of food systems and the many ways they are controlled and influenced. Five skill sets for adaptive leaders were identified by a small international working group at a session in Bellagio, Italy, sponsored by the Rockefeller Foundation: communications; getting things done and accomplishing change; working across boundaries, whether disciplinary, sectoral, or political; influence; and vision and strategy.

Applying these skills sets encourages a move from finger-pointing to shared leadership. It provides space to accept the fact that food-borne disease happens and will happen. Food safety programs are not always somebody’s fault. After all, “safe food” is an oxymoron. All food has risks and yet “safe” implies the absence of risk. Food systems can either contribute to the risks or be designed to help manage the risks. The very complexity of food systems also means that an infinite number of risk-management strategies are available, if we are only creative enough.

Incremental progress on complex food safety problems may also require a new model of partnership that engages producers and the food industry along with government. We do not have an ideal model for partnership or shared leadership, but several initiatives in fisheries and foods are trying to find or build models, and so are others outside of the food sector. A new partnership model would include a value proposition to engage industry (examples are beginning to emerge around agriculture and environment, where there is no alternative but for government and the private sector to work together) and a more flexible and realistic regulatory system. The idea of zero tolerance makes no scientific sense (zero risk is unachievable) and contributes to the very high levels of waste in U.S. food supply chains (e.g., supermarkets in the United Kingdom are moving to changes in the “use by” label to provide more flexibility in home-freezing, which is anticipated to reduce waste in kitchens with no reduction in food safety).

What Comes Next?

We have proposed a One Health approach that would match the complex, adaptive problems of food safety with shared, adaptive, and holistic problem solving that considers the entire food system. However, an approach is of little use while it remains on paper. The next challenge is to find a complex, subtle, pervasive, and wide-ranging food safety problem that will require adaptive leadership, partnerships, and a wide scope of action—the problem of mycotoxins is excellent example—and put the food systems community to work on it.

References

Ercsey-Ravasz, M., Z. Toroczkai, Z. Lakner, and J. Baranyi. 2012. Complexity of the International Agro-Food Trade Network and Its Impact on Food Safety. PLoSONE 7(5):e37810.

Gunderson, L., and C. S. Holling. 2001. Panarchy: Understanding transformations in systems of humans and nature. Washington, DC: Island Press.

A6

THE AUSTRALIAN PERSPECTIVE, THE BIOSECURITY CONTINUUM FROM PREBORDER, TO BORDER AND POSTBORDER

Martyn Jeggo¹²

Executive Summary

Biosecurity is of considerable importance to Australia and managing biosecurity risks through a One Health approach offers many attractive advantages. To date most of the international effort has been focused on adopting a One Health approach from the perspective of infectious diseases and the need to bring together multidisciplinary teams to most effectively understand and mitigate the risks. Central to understanding the skills and knowledge that are required is an appreciation that many recent outbreaks of infectious diseases arise in wildlife, create disease in livestock, and subsequently go on to cause infection in humans. While the drivers for this emergence are still not fully elucidated, a number of key factors play a part, including climate change.

While there are clear differences between the approaches to food safety versus infectious disease management, there is still the basic gain to be made by attacking the risks through reducing likelihood rather than addressing the consequences. This key concept underpins the approach undertaken in Australia,

_______________

¹² Director, Australian Animal Health Laboratory, Geelong, Australia.

where biosecurity activities, preborder, at the border, and postborder, focus on early detection and rapid response. While the approach recognizes the continuum from pre- to postborder, resource allocation is currently being reviewed to ensure an appropriate balance for effective risk mitigation.

Underpinning the Australian biosecurity strategy is the recognition of the value of a One Health, multidisciplinary approach. There is a current awareness that much needs to be done to ensure that the maximum value is achieved from this approach and that a “business-as-usual” mentality does not prevail. Fortunately for Australia, the recent management of Hendra outbreaks in Queensland and New South Wales has provided an excellent example of the gains that can be made through a One Health approach. Similar examples need to be developed in the food safety arena.

Introduction

Biosecurity is the protection of the economy, the environment, social amenity, or human health from the negative impacts associated with the entry, establishment, or spread of animal or plant, pests and diseases, or invasive plant and animal species (Beale et al., 2008). Australia has an enviable biosecurity position having been free of many of the infectious diseases that infect livestock in most other parts of the world. Built on the “island status,” Australia has for many years maintained a stringent import policy around plants, livestock, and agricultural products to ensure the protection of this status. Australia has consistently adopted a precautionary policy, although international trade regulations (OIE, 2011) attempt to ensure that fair trading practices exist in the international agricultural marketplace. Notwithstanding this, the risks continue to increase and disease outbreaks are an unfortunate regular event. Recognizing this, the focus remains on early detection linked to a rapid and effective response. Eradication is the preferred option but not always achievable, particularly in the plant sector. Here a policy of containment is adopted that seeks to limit spread and reduce the impact on both productivity and the environment.

A number of frameworks have been developed to better enable the Australian biosecurity strategy. These include not-for-profit companies providing a framework for industry and government to work in partnership, such as Animal Health Australia (AHA, 2011a) and Plant Health Australia, agreed on plans for how to deal with outbreaks and agreed on processes for who will pay for what in the face of a major disease incursion (AHA, 2011b). Mostly developed for the livestock sector, this approach is now being applied to both the plant and environmental sectors.

There is a growing appreciation that the risks being addressed now encompass environment and human health as well as animals and plants. In order to effectively manage these risks, a One Health approach has much to offer.

The One Health Concept

One Health as a concept emerged some 10 years ago and has gained increasing acceptance as a process for addressing a range of issues involving environmental, animal, and human health (Leboeuf, 2011). Although there are many definitions of One Health, the current focus remains around emerging infectious disease (EID) and recognizes that 75 percent of EID in humans arise from animals, and in large part, from wildlife, often spilling over first into domestic livestock and then infecting humans (Woolhouse and Gowtage-Sequeria, 2005). This also includes the emergence of diseases affecting food safety and food security. A full understanding of these processes and the development of mitigating strategies to reduce the threats from EIDs will require input and engagements from people with a diverse set of skills and a range of disciplines (Vallet, 2009).

The emergence of disease requires an interaction between the pathogen, the host, and the environment. Understanding these interactions and developing effective mitigation strategies requires a complex of One Health disciplines. In the case of pathogen influences these involve such areas as quasispecies variation, genetic recombination, host/vector adaptation, tissue tropism, virulence determinants, and latency or persistence. For host influences it is necessary to understand reservoir host spillover, the range of intermediary hosts, various aspects of vector competence, the susceptible host range, the pathogenesis of the disease in different hosts, and the potential range of immune responses. In looking at the impact of anthropogenic influences it is important to appreciate the broader issues of globalization, urbanization, land-use changes, cultural changes, and regional and global conflicts. Finally in terms of geophysical influences, climate change and variability link to extreme weather events are critical (Cutler et al., 2010; Rushton, 2009; Wolfe et al., 2007).

The One Health approach strives to bring these many sciences and disciplines together to provide the best possible solution to health risk management. Presently much is being done at both the national and international levels to create effective One Health partnerships with the first One Health International Congress being held in 2011 in Melbourne, Australia (Ecohealth, 2011). Despite these efforts, few examples exist of real success, and it may require more drastic organizational changes to achieve the cultural changes needed to deliver the anticipated value and impact from a One Health approach.

Infectious Diseases Versus Food Safety

Ensuring the safety and quality of Australian foods within an integrated national biosecurity system is a current challenge for Australia. Although much has been done on characterization of food-borne hazards, on analysis of through-chain risks and the continual development of innovative risk management strategies, the approach is principally post-farm gate. In Australia these differences in infectious disease management versus food safety (Table A6-1) highlight areas

TABLE A6-1 Major Differences to Risk Management of Infectious Diseases Versus Those Associated with Food Safety Issues

for a rethink and to consider how these two sectors can learn from each other. Central to this will be the application of the One Health principles.

Biosecurity Risk Management and the Biosecurity Continuum

The process of risk management for infectious diseases is concisely documented by the World Animal Health Organization (OIE) (Williberg, 2011) but can be simply considered in terms of the likelihood of a hazard occurring and the consequences if such an event did happen. In considering the likelihood, how the disease spreads and the survival of the pathogen are major components, but for the newer emerging infectious diseases understanding emergence and host switching are critical issues. Indeed, as an appreciation is gained of the emergence of pathogens from a wildlife reservoir into a livestock species and the subsequent potential to cause disease in humans, it becomes crucial to better understand those drivers that lead to a host switch.

On the consequence side of the risk profile, it is important to not only understand the process of disease in the affected host but also to appreciate this in terms of production and trade losses and the potential risks to humans and the environment. This expanded perception of the impact of disease lends even further credence to the concept of a multidisciplinary or One Health approach in managing effectively these consequences.

Australia has studied carefully the most effective approach to managing the risks from infectious disease and has come to the clear conclusion that the greatest return on investment lies in prevention and eradication rather than containment and allowing endemicity (see Figure A6-1).

It thus concludes that it is necessary to understand the risks for emergence and to tackle these directly to reduce or eliminate these risks. This approach, however, will never be 100 percent effective, and thus some resources will need

FIGURE A6-1 When to act: Generalized invasion curve showing actions appropriate to each stage.

SOURCE: © State of Victoria Department of Primary Industries, 2009, and reproduced with their kind permission.

to be allocated to consequence management but at a level that appreciates the lower risk if likelihood is significantly reduced.

In considering emerging risks, the movement of people to urbanized areas and the intensification of agriculture, often in close proximity to these urban areas, have clearly changed the risk profile in terms of both opportunities for the pathogen as well as the likely outcome of an infection. This risk is then exacerbated by the significant increased movement of people and products between these urbanized areas both nationally and internationally. There is little doubt that, overlying these issues, climate change has the potential to have a significant impact both directly through a change, for example, in available diseases carrying vectors and survival of the pathogen, but also in terms of change patterns of habitat and feeding by reservoir hosts (Rosenthal, 2009).

Australia has focused efforts for many years at the border and preborder areas in order to best manage the likelihood risks, to ensure detection as early as possible and thus a response that has the best chance to enable eradication. More recently and following a significant review of national biosecurity, an enhancement of postborder activities and the concept of the biosecurity continuum have emerged. To best manage this continuum it has been agreed between the Australian governments (Commonwealth, states, and territories), that the Common wealth government will focus and take responsibilities for preborder and border activities, with states and territories managing the majority of postborder activities. In recent times, the concept of a significant contribution from industry has emerged and, while government will retain primary responsibility for policy and standard setting, operational activities will in the future likely involve both government and industry working together in implementation of biosecurity activities.

Preborder Activities

It should be recognized from the outset, that although Australia is an island and this has been a significant advantage in maintaining a disease-free status, neighboring countries are in close proximity to Australia (via the Torres Strait) and the huge increase in international travel and trade considerably reduce the “safety factor” of being an island. It is therefore necessary to continually assess the threats from “abroad” and consider these threats in terms of market access and trade. There is a permanent pressure to broaden the trade in agricultural products, with an increase in demand to import from areas with a very different disease status to Australia. Managing these risks requires not only understanding the disease status of trading partners but also influencing the international regulations that govern such trade. Although continual risk analysis is a prerequisite for pre-border activities, threat reduction through a range of activities is also a major component. This starts with building trust and partnerships and has to grow into on-the-ground capacity-building support programs that

assist many countries, particularly in the Asian region, to better manage their own biosecurity programs.

A clear example of the need to reduce risk is that of the support by Australia to countries in the region to control foot and mouth disease (FMD). FMD represents the biggest risk to the Australian livestock industries, and for many years FMD was endemic in most countries in the region. Assistance to initially Indonesia and subsequently to the Southeast Asia FMD control program has considerably reduced this risk through both eradication and effective control in many countries in this region. Building an increased capacity in the region for countries to better manage their own biosecurity leads to a clear reduction of the likelihood risk of disease occurring in Australia. Various programs of the Australian Agency for International Development and the Australian Centre for International Agricultural Research focus in this area.

Border Activities

Australia’s Biosecurity Quarantine Operations Division manages those activities at the border that provide quarantine controls to minimize the risks of exotic pests and diseases entering the country. A further activity is the inspection of import and export certification to help retain Australia’s highly favorable health status and wide access to overseas markets. These inspections are targeted at activities involving aircraft, ships, and cargo and include the management of the National Australian Quarantine Strategy (NAQS).

Given the nature of the coastline of Australia, a large number of maritime programs are undertaken to ensure the effectiveness of these border operations. These include the management of unauthorized maritime arrivals, marine pollution, illegal activities in protected areas, issue around piracy, robbery or violence at sea, the illegal exploitation of natural marine resources, and maritime terrorism. Linked to this is the availability of a range of response assets including military naval vessels.

NAQS supports the government’s broader biosecurity objectives through conducting the monitoring and surveillance for exotic plants and animal disease across the north of Australia from Cairns to Broome and including the Torres Strait. These activities recognize the remote location of this region, the low human population, and the close proximity of neighboring countries and extend to collaborative surveillance and capacity building in Papua New Guinea, Indonesia, and Timor Leste, along with other neighboring countries. The overall strategy is clearly focused on early detection in a high-risk area, linked to an ability to mount an early response.

Postborder Activities

A wide range of activities are conducted postborder, principally through the governments of the states and territories. These aim for the early detection

of an emerging or exotic disease or disease-causing agent; the demonstration of freedom from a disease or disease-causing agent for trade purposes; the detection of changes in the distribution, prevalence, and incidence of a disease or disease-causing agent; and finally the detection of changes in factors or events that influence the risk of disease.

Increasingly a range of sophisticated geographical information systems and genetic-based tools have been used to better understand host and population structures with molecular epidemiology being used to understand the distribution of pathogens.

For the most part these activities have been targeted (or active) in nature with clear resource allocations and deliverables. Background (or passive) surveillance has been a lower priority for some time. The recent formation of a National Animal Health Surveillance System has recognized the critical component of passive surveillance in the overall approach, and increased activities in this area will be part of the future.

Conclusions and Discussions

• A One Health approach is essential to effectively managing the risks associated with both food safety and infectious diseases. Bringing together two necessary disciplines, skills and knowledge, is a real challenge given the current separation of management of environment, human, animal, and plant health. This may require real organizational change at the national level to achieve a genuine multidisciplinary and One Health approach.

• There are many similarities but some important differences between the management of food safety versus infectious disease. Having a whole systems approach (from farm to fork) has much to offer, and there are now real examples of success (e.g., control of salmonellosis in poultry in Denmark).

• Biosecurity (in the Australian concept) looks after both areas but remains somewhat fragmented. Currently biosecurity encompasses agricultural health (plants and animals) and environmental health; human health management remains outside of these activities except in exceptional cases (e.g., influenza management). A true One Health approach is perhaps some way off. The recent management of Hendra virus outbreaks, however, has clearly demonstrated the value of a One Health approach.

• Biosecurity is managed as a continuum from preborder to border and postborder activities.

• In managing biosecurity risks, investments in likelihood considerably out-weigh consequence management (but the latter cannot be ignored). Within this framework resource allocation across the preborder, border, and post-border need to be continually reassessed and currently in Australia there is an agreed-upon need to greater invest in postborder activities.

• Much still needs to be done to achieve a genuine One Health approach. Although progress is being made, real gain may require some fundamental changes in thinking and even reorganization at both the national and international levels with the creation of departments and divisions of One Health.

• Training and education in One Health is currently crucial in driving the longer-term cultures necessary to sustain a One Health approach. This needs to be linked to clear examples of success and the added value of a One Health approach.

Acknowledgments

Much of the material contained in this report was provided from the Australian Commonwealth Government’s Department of Agriculture, Forestry and Fisheries, State Departments of Primary Industries, and a number of agricultural institutes and universities in Australia. The author is indebted to the many staff of these government departments for these contributions.

References

AHA (Animal Health Australia). 2011a. Annual report 2010-2011. Canberra, Australia: Animal Health Australia.

———. 2011b. AUSVET Plans. http://www.animalhealthaustralia.com.au/programs/emergency-animal-disease-preperedness/ausvetplan/ (accessed January 11, 2012).

Beale, R., I. Fairbrother, R. Inglis, and W. Trebuk. 2008. Report to the Australian government.

Cutler, S. J., A. R. Fook, and W. H. van der Poel. 2010. Public health threat of new, reemerging, and neglected zoonoses in the industrialized world. Emerging Infectious Diseases 16(1):1-7.

Ecohealth. 2011. 7(Suppl. 1).

Leboeuf, A. 2011. Making sense of One Health: Cooperating at the human-animal-ecosystem health interface. Health and Environment Report No. 7. Paris: Institut Français des Relations Internationals.

OIE (World Organization for Animal Health). 2011. Terrestrial Animal Health Code I and II. Paris: World Organization for Animal Health.

Rosenthal, J. 2009. Climate change and the geographic distribution of infectious disease. Ecohealth 6(4):489-495.

Rushton, J. 2009. Economics of animal health and production. Wallingford, UK: CABI.

Vallet, B. 2009. Editorial. OIE Bulletin 2.

Willeberg, P. 2011. Models in the management of animal diseases. OIE Scientific and Technical Review 30(2).

Wolfe, N. D., C. Panosian Dunavan, and J. Diamond. 2007. Origins of major human infectious diseases. Nature 447:279-283.

Woolhouse, M. E., and S. Gowtage-Sequeria. 2005. Host range and emerging and reemerging pathogens. Emerging Infectious Diseases 11(12):1842-1847.

A7

FOOD SAFETY: A VIEW FROM THE WILD SIDE

William B. Karesh, Elizabeth Loh, Catherine Machalaba¹³

Food-borne illnesses pose a serious threat to public health with growing economic and international trade ramifications. Past outbreaks of food-borne diseases have largely been viewed only through the lens of public health; yet food-borne illnesses are closely associated with the link between human and animal populations, and with the surrounding environment. For example, in 2006, approximately 200 people in 26 states were diagnosed with a particularly virulent strain of E.coli O157:H7 found in spinach. Viewed only from a human health perspective, our knowledge of this outbreak would have extended only to morbidity, mortality, outbreak investigation, laboratory diagnosis, and clinical treatment. However, once viewed through the lens of animal health and ecology, the E. coli O157:H7 isolates that caused the human deaths and serious illnesses related to spinach were also found in wild pig feces, the feces of several cows, and in a stream on one of the four spinach farms in the area (Warnert, 2007). Thus, a One Health perspective integrating our knowledge of the environment and ecology, in addition to human and animal health, was required to fully investigate and understand this outbreak and has great utility in the food-borne illness discussion.

Food-borne pathogens from wildlife span the taxonomic spectrum from helminthes to viruses (Figure A7-1). While the number of food-borne transmitted emerging disease events due to viruses is fewer than the number due to other groups of pathogens, some such as severe acute respiratory syndrome (SARS) have resulted in devastating consequences. As noted by Tauxe, the vast majority of food-borne illnesses in the United States due to known pathogens have emerged in the past two decades and an even larger percentage are due to yet-to-be-identified pathogens (Tauxe, 2002). Many of the known food-borne pathogens are zoonotic (Figure A7-2), and many may be linked to wildlife. As seen more generally with emerging infectious diseases (Jones et al., 2008), it is rational to assume that future outbreaks of new food-borne illnesses may be linked to wildlife.

From our review of the peer-reviewed literature, the main drivers of wildlife-related zoonotic disease emergence include land-use change and food industry changes. For food-borne disease, food industry changes, human susceptibility (reduced immune function), travel, and antimicrobial resistance were the primary drivers of past emergence events (Figure A7-3).

With more than 70 percent of food-borne EID events being zoonotic in nature (Figure A7-2), contact with or contamination of food or food ingredients

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¹³ EcoHealth Alliance, 340 West 34th Street, New York, NY 10001.

FIGURE A7-1 The number of infectious disease events that emerged from wildlife between 1940 and 2004 as published by Jones et al. (2008). These events (n = 96) are broken down by pathogen type, and each event is defined as the first emergence of a given pathogen. The colored areas within each bar depict the different transmission pathways as a percentage of the total number of emerging infectious disease (EID) events. For example, between 1940 and 2004, 52 zoonotic EIDs from wildlife were viruses. Of these events, 34.5 percent of these pathogens are transmitted by direct contact, 32.7 percent are vector-borne, 23.6 percent are air-borne, 5.5 percent are transmitted through contact with a contaminated environment or fomite, and 3.7 percent are food-borne.

by wild animals creates a serious potential for disease transmission. Commonly, both wild and domestic animals are implicated as sources of food contamination (Beuchat and Ryu, 1997; Cima, 2012; Doyle and Erickson, 2008; Gorski et al., 2011; Newell et al., 2010). Yet, definitive identification of a specific source animal or species is rare, particularly with wild species because they are typically no longer present at the time food-borne illness is detected in humans and investigations leading back to farms or processing plants are initiated. Despite the rarity of finding the “smoking gun,” we can operate on the fact that a large number of

FIGURE A7-2 All food-borne EID events from 1940-2004 (n = 100), broken down by zoonotic versus nonzoonotic origin.

FIGURE A7-3 All food-borne emerging infectious diseases from 1940 to 2004 (n = 100) with their respective “drivers of emergence” as published by Jones et al. (2008).

food-borne illnesses are caused by pathogens frequently associated with wild species such as rodents, deer, feral pigs, reptiles, and birds (Figure A7-4).

Wild animals can provide the original source of pathogen contamination or serve to move pathogens from other infected sources. Similarly, insect reservoirs have been shown to introduce diseases into food processing systems (i.e., Chagas disease; Pereira et al., 2009) and have the potential for serving as mechanical vectors. Research by Wayadande et al. (2011) has identified filth flies as mechanical vectors that acquire and carry bacteria from their development stage environment (i.e., feces, carcasses, or decaying matter) including Salmonella typhii, Mycobacterium tuberculosis, and Rotavirus. The bacteria can also be carried in the excreta of blow flies, presenting risks of spread to external surfaces. Sela et al. (2005) reported similar findings for fruit flies.

In some cases, it may be feasible to limit contact or contamination of food during the production stage from larger wild mammals. Eliminating small-animal access to farm fields is impractical, although reducing exposure could be facilitated by a number of pest management techniques such as waste management and sanitation, eliminating hiding areas, etc. Postharvest contamination of food from small mammals and birds is more easily controlled by good pest management practices.

More directly, wildlife provides a substantial portion of our food globally, with nearly half of all seafood coming from wild sources. In some regions of the world, wild meat from terrestrial animals represents a primary source of protein on which populations are dependent. The volume of wild meat (“bush meat”) harvested from Central Africa alone totals more than 1 billion kg per year (Wilkie and Carpenter, 1999). This volume of meat, almost all of which is processed and distributed to consumers with few if any modern hygiene practices, provides a constant opportunity for human exposure to common food-borne pathogens (Karesh et al., 2005; Smith et al., 2012). Additionally, wild animals are sought after as delicacies based on cultural and consumer preferences. This demand for wildlife, which is both legally and illegally supplied, has global dimensions. Although there is a “not in my backyard” mentality that limits our concern for what diseases are circulating across the world, this is a problem in which the United States is deeply involved, as the United States is the main importer of wildlife (Asmüssen et al., 2011). What is present across the world can be in our backyard—and then on our plate—in a matter of days through our importation of tens of millions of legal and illegal animals (Jones et al., 2008; Smith et al., 2009). The United States also contributes to the potential spread of disease to other countries through its export of turtles destined for the food trade in Asia.

The emergence and transmission of food-borne zoonotic diseases from dietary habits and pressures are increasingly being documented. In simplest terms, we are seeing that the consumption of wild animals translates to “you get what you eat.” Hepatitis E (Vasickova et al., 2007), brucellosis (CDC, 2009), and trichinellosis (Roy et al., 2003) are examples of hunter-acquired food-borne illness. The origin

FIGURE A7-4 Routes of contamination resulting in food-borne illness linked to wildlife.

SOURCE: Illustrated by Amanda Price.

of HIV/AIDS through the transmission of nonhuman primate simian immunodeficiency viruses to humans via bush meat hunting represents a major example of how anthropogenic behaviors can lead to massive and pervasive public health threats, and newer evidence shows that the transmission of non human retroviruses to humans happens on a regular basis (Betsem et al., 2011; Calattini et al., 2011; Peeters et al., 2002). SARS is another well-known example of food-borne illness from animals, spreading to humans after the mixing of live reservoir hosts (e.g., bats) and intermediate hosts (e.g., civets) (Guan et al., 2003; Li et al., 2005).

Food-borne illnesses and the interactions that increase their presence in our food supply are not new. However, we are seeing increased detection of zoonotic food-borne illness as we engage more and more in the practices that drive disease emergence. There are challenges ahead, including climate change and its associated changes in animal migration, water supply demands, and possibly pathogen distribution and abundance. For the latter, Vezzulli et al. reported that, during the past half century, ubiquitous marine bacteria of the Vibrio genus, including V. cholerae, increased in occurrence within the plankton-associated bacterial community of the North Sea, where an unprecedented increase in bathing infections associated with these bacteria was recently reported. Among environmental variables, increased sea surface temperature explained 45 percent of the variance in Vibrio data, supporting the hypothesis that ocean warming is facilitating the spread of vibrios and may be the cause of the globally increasing trend in associated diseases (Vezzulli et al., 2012).

Opportunities for Food-Borne Disease Surveillance

Humans have commonly served as the sentinel species for food-borne illnesses, and as a result early detection and response systems such as PulseNet, FoodNet, the National Electronic Norovirus Outbreak Network (CalciNet), and the National Notifiable Diseases Surveillance System are based on human outbreak (or case) surveillance. There are new approaches in emerging disease surveillance that could possibly be adapted to food-borne disease surveillance to contribute to targeting surveillance efforts, early detection, control, and prevention. Some of these approaches are being developed and tested with the support of the U.S. Agency for International Development’s Emerging Pandemic Threats PREDICT program in an attempt to create more upstream focus for early detection of emerging diseases with pandemic potential.

PREDICT’s SMART (strategic, measurable adaptive, responsive, and targeted) surveillance method uses continuously refined predictive models, literature reviews and analyses, digital news surveillance, and input from front-line information by field personnel and the public. Predictive models can identify areas of greatest risk for outbreaks of food-borne illness (food-borne illness “hotspots”) by generating geospatial information on various human—animal interfaces, behaviors, activities, and presence of additional risk factors. These analyses

can be spatially explicit to account for host and pathogen niches and known distributions, as well as differing drivers of disease emergence in different regions of the world. For food-borne illnesses, these interfaces might include areas where food-production farms overlap with habitat used by wildlife (to include species and common pathogens), areas of hunting, wildlife—livestock conflict, natural resource extraction and land-use change, markets, and regions with high levels of global transportation.

Closely linked, and in some ways underpinning the predictive modeling, analyses of peer-reviewed publications can be conducted for food-borne diseases related to wildlife to determine species and human activities that present the highest risks. Databases on outbreaks or cases of wildlife-related food-borne illnesses could also be queried to identify products with high potential for food-borne diseases, drivers of disease emergence, and risky areas where surveillance and control efforts can be focused. Analysis of the individual drivers of disease emergence can help parse out the most likely routes of transmission in a given area, helping to set control measures in place. For the PREDICT program, these analyses are used to target surveillance to key taxonomic groups and key human activities and “interfaces” with wildlife. Similar approaches have been used in the food industry for years in determining the most effective “control points” or monitoring steps for known, common pathogens. Analyses of drivers might contribute to current approaches by revealing additional key points for surveillance and interventions preceding human infection with novel pathogens. Some of this information could be derived from the Foodborne Outbreak Online Database produced by the U.S. National Outbreak Reporting System, which reports annual outbreaks by year, month, state, etiology, location interface, total cases, hospitalizations, deaths, food vehicle, and contaminated ingredient. It currently contains data from 1998-2009. Wildlife-related food-borne illnesses present some additional challenges and opportunities that may require nonconventional approaches and include targeting surveillance outside of the normal farm-to-table production chain. For example, analyses may indicate that sampling by hunters or pest control operators could yield valuable surveillance data (both for pathogen and host species abundance) in a cost-effective manner.

Digital surveillance, the practice of seeking disease news and tracking disease trends via the Internet such as provided by HealthMap, could also help to deter mine where to target surveillance, control, and capacity-building efforts. Both HealthMap and ProMED-Mail are expanding their coverage of wildlife disease events with the support of the PREDICT program, providing easier access to that information for health workers and the public around the world. While historic, macro-level data can be useful for risk modeling and mapping, it is important to maintain on-the-ground approaches to continually update and target the specific and real-time events and factors driving food-borne disease risk.

Food-borne disease diagnostics. The increase in technological capabilities over the past decade has aided our ability to garner far more information from

surveillance efforts. These technologies can support rapid detection, diagnosis, and control of food-borne illness, as well as preventive measures around potential food-borne illness emergence. Expanded efforts in surveillance for pathogens in wildlife have created a need for simple, inexpensive broad-ranging tests that can be used locally for rapid screening, coupled with networks of labs that can follow up with more detailed, confirmatory testing. For food-borne illness, pathogen-specific and -sensitive tests will always play an important role, but as we expand our concern to wildlife-related and novel pathogens in food, there could be a growing need for some broad-level screening tests for family-, order-, or genus-level testing.

Intervention Strategies

Once a source or a transmission pathway has been established, the use of existing control mechanisms for food-borne illnesses will likely be effective. There is currently no evidence to suggest that wildlife-related food-borne illnesses are inherently different from other sources of contamination; in the case of consumption of wildlife itself, similar risk reduction practices for the safe handling and consumption of poultry, beef, or seafood should suffice. As with traditional food safety surveillance and interventions, stakeholder engagement is crucial for success. For diseases related to wildlife, this concept is the same, but the stakeholders may not be the traditional food safety partners that industry and public health agencies work with. Hunters, conservation organizations, and wildlife management authorities need to be engaged to most effectively develop and implement both surveillance systems and control strategies. As we are learning in most areas of public health, collaboration among multiple disciplines is key in the success of disease risk reduction interventions, and this is especially true as we try to reduce food-borne illnesses linked to wildlife in a variety of ways.

Agency Partnerships and Regulation

There is great potential to learn more about wildlife-related food-borne illnesses through collaboration with surveillance and regulatory agencies. Initial sampling efforts of confiscated wildlife through the Centers for Disease Control and Prevention (CDC) have begun to find pathogens (Smith et al., 2012), but there needs to be dedicated funding and sustained efforts to conduct sufficient inspections and pathogen testing across all agencies that regulate wildlife. This is especially relevant to the Food and Drug Administration, which has regulatory authority for food safety in meat or other animal-derived products from wildlife in interstate commerce not otherwise covered by U.S. Department of Agriculture authority. Greater understanding of wildlife trade risks can inform risk reduction regulations and practices. For example, short-term enforcement of traded animals

in Asian markets following the 2003 SARS outbreak shed light on the scale and composition of wildlife trade in the region (Karesh et al., 2005). In addition to protecting consumers, strong enforcement and surveillance of food-bound wildlife products can help the health, pet, and food industries proactively mitigate risks from potential food-borne threats.

The Convention on the International Trade of Endangered Species (CITES) regulates the trade of endangered wildlife in its 175 member countries. However, illegal wildlife trade is still widespread, with 87 percent of CITES member countries reporting illegal trade activity. Thus, trade regulations must be implemented and enforced at the individual country level as well. There are opportunities to use regulation to directly protect the public from wildlife diseases. The U.S. ban on small turtles resulted in a major decline in Salmonella transmission in children, leading to a 77 percent reduction of cases (Cohen et al., 1980). Food-borne disease surveillance can inform targeted regulations to reduce illness spread from high-risk sources.

Collaboration

Food-borne illness is a complex challenge that cannot merely be solved by an “expert solution” and demands diverse stakeholder participation. The public health sector and food industry should not be isolated in addressing food-borne illness concerns involving wildlife. There are ample opportunities for collaboration and mutual benefits among a wide array of stakeholder disciplines. The capture of endangered wildlife and detrimental impacts to wildlife habitats through land-use change—a major driver of emerging infectious diseases (Jones et al., 2008; Patz et al., 2004)—pose serious threats to the sustainability of biodiversity, bringing conservationists into the equation. Hunters and indigenous populations have a vested interest in both the food security and the health of their communities, and their direct involvement and ownership of disease reduction efforts is crucial for creating long-term success.

At the same time, although food-borne illness is a global concern, individual risks can be addressed at a microcosm level. Large-level suppliers can support the health of local communities where their products are sourced. This involves both reducing reliance on wildlife for food (e.g., in logging settlements) and taking measures to educate communities about safe and healthy practices (i.e., in hunting and animal butchering). These approaches have had marked success. For example, Northern Congo has not seen a human case of Ebola since 2005, despite its continuing presence in wildlife. The joint approach of education of village hunters on risk reduction (i.e., high-risk species, hand washing, and cooking techniques) and the assumption of responsibility taken on by hunters for protecting themselves and their families is credited with the prevention of new cases.

Going Forward

Without effective action, the world is slated for an increasing trend of negative health and economic consequences from food-borne illnesses. Fortunately, at present there are opportunities for intervention. Addressing food security issues will decrease reliance on high-risk food sources such as wildlife. Additionally, overall progress around disease surveillance, control, and prevention has allowed us to establish feasible disease monitoring systems and learn important lessons that can be applied to the risk reduction of food-borne illnesses. Integral to these lessons has been the necessity and value of One Health collaborations. The synergies formed by integrating environment, health, and wildlife sectors, in concert with local populations, can provide the perspectives and actions to reduce food-borne illnesses and provide appropriate intervention and prevention strategies before further outbreaks occur.

References

Asmüssen, M. V., J. R. Ferrer-Paris, et al. 2011 (accepted). Estimates and trends of illegal wildlife trade in the world. PLoS Biology.

Betsem, E., R. Rua, P. Tortevoye, A. Froment, and A. Gessain. 2011. Frequent and recent human acquisition of simian foamy viruses through apes’ bites in central Africa. PLoS Pathogens 7(10):e1002306.

Beuchat, L. R., and J. H. Ryu. 1997. Produce handling and processing practices. Emerging Infectious Diseases 3(4):459-465.

Calattini, S., E. Betsem, S. Bassot, S. A. Chevalier, P. Tortevoye, R. Njouom, R. Mahieux, A. Froment, and A. Gessain. 2011. Multiple retroviral infection by HTLV type 1, 2, 3 and simian foamy virus in a family of Pygmies from Cameroon. Virology 410(1):48-55.

CDC (Centers for Disease Control and Prevention). 2009. Brucella suis infection associated with feral swine hunting—three states, 2007-2008. Morbidity and Mortality Weekly Report 58(22):618-621.

Cima, G. 2012. Wildlife, trade, susceptibility amplify food risks. Journal of the American Veterinary Medical Association 240(4):352-355.

Cohen, M. L., M. Potter, R. Pollard, and R. A. Feldman. 1980. Turtle-associated salmonellosis in the United States. Effect of public health action, 1970 to 1976. Journal of the American Medical Association 243(12):1247-1249.

Doyle, M. P., and M. C. Erickson. 2008. Summer meeting 2007—the problems with fresh produce: An overview. Journal of Applied Microbiology 105(2):317-330.

Gorski, L., C. T. Parker, A. Liang, M. B. Cooley, M. T. Jay-Russell, A. G. Gordus, E. R. Atwill, and R. E. Mandrell. 2011. Prevalence, distribution, and diversity of Salmonella enterica in a major produce region of California. Applied and Environmental Microbiology 77(8):2734-2748.

Guan, Y., B. J. Zheng, Y. Q. He, X. L. Liu, Z. X. Zhuang, C. L. Cheung, S. W. Luo, P. H. Li, L. J. Zhang, Y. J. Guan, K. M. Butt, K. L. Wong, K. W. Chan, W. Lim, K. F. Shortridge, K. Y. Yuen, J. S. Peiris, and L. L. Poon. 2003. Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China. Science 302(5643):276-278.

Jones, K. E., N. G. Patel, M. A. Levy, A. Storeygard, D. Balk, J. L. Gittleman, and P. Daszak. 2008. Global trends in emerging infectious diseases. Nature 451:990-994.

Karesh, W. B., R. A. Cook, E. L. Bennett, and J. Newcomb. 2005. Wildlife trade and global disease emergence. Emerging Infectious Diseases 11(7):1000-1002.

Li, W., Z. Shi, M. Yu, W. Ren, C. Smith, J. H. Epstein, H. Wang, G. Crameri, Z. Hu, H. Zhang, J. Zhang, J. McEachern, H. Field, P. Daszak, B. T. Eaton, S. Zhang, and L. F. Wang. 2005. Bats are natural reservoirs of SARS-like coronaviruses. Science 310(5748):676-679.

Newell, D. G., M. Koopmans, L. Verhoef, E. Duizer, A. Aidara-Kane, H. Sprong, M. Opsteegh, M. Langelaar, J. Threfall, F. Scheutz, J. van der Giessen, and H. Kruse. 2010. Food-borne diseases—the challenges of 200 years ago still persist while new ones continue to emerge. International Journal of Food Microbiology 139(Suppl.):S3-S15.

Patz, J. A., P. Daszak, G. M. Tabor, A. A. Aguirre, M. Pearl, J. Epstein, N. D. Wolfe, A. M. Kilpatrick, J. Foufopoulos, D. Molyneux, and D. J. Bradley; Working Group on Land Use Change and Disease Emergence. 2004. Unhealthy landscapes: Policy recommendations on land use change and infectious disease emergence. Environmental Health Perspectives 112(10):1092-1098.

Peeters, M., V. Courgnaud, B. Abela, P. Auzel, X. Pourrut, F. Bibollet-Ruche, S. Loul, F. Liegeois, C. Butel, D. Koulagna, E. Mpoudi-Ngole, G. M. Shaw, B. H. Hahn, and E. Delaporte. 2002. Risk to human health from a plethora of simian immunodeficiency viruses in primate bushmeat. Emerging Infectious Diseases 8(5):451-457.

Pereira, K. S., F. L. Schmidt, A. M. Guaraldo, R. M. Franco, V. L. Dias, and L. A. Passos. 2009. Chagas’ disease as a foodborne illness. Journal of Food Protection 72(2):441-446.

Roy, S. L., A. S. Lopez, and P. M. Schantz. 2003. Trichinellosis surveillance—United States, 1997-2001. Morbidity and Mortality Weekly Report: Surveillance Summaries 52(6):1-8.

Sela, S., D. Nestel, R. Pinto, E. Nemny-Lavy, and M. Bar-Joseph. 2005. Mediterranean fruit fly as a p otential vector of bacterial pathogens. Applied and Environmental Microbiology 71(7):4052-4056.

Smith, K. F., M. Behrens, L. M. Schloegel, N. Marano, S. Burgiel, and P. Daszak. 2009. Ecology: Reducing the risks of the wildlife trade. Science 324(5927):594-595.

Smith, K. M., S. J. Anthony, W. M. Switzer, J. H. Epstein, T. Seimon, H. Jia, M. D. Sanchez, T. T. Huynh, G. G. Galland, S. E. Shapiro, J. M. Sleeman, D. McAloose, M. Stuchin, G. Amato, S. O. Kolokotronis, W. I. Lipkin, W. B. Karesh, P. Daszak, and N. Marano. 2012. Zoonotic viruses associated with illegally imported wildlife products. PloS One 7(1):e29505.

Tauxe, R. V. 2002. Emerging foodborne pathogens. International Journal of Food Microbiology 78(1-2):31-41.

Vasickova, P., I. Psikal, P. Chalupa, M. Holub, R. Svoboda, and I. Pavlik. 2007. Hepatitis E virus: A review. Veterinarni Medicina 52(9):365-384.

Vezzulli, L., I. Brettar, E. Pezzati, P. C. Reid, R. R. Colwell, M. G. Höfle, and C. Pruzzo. 2012. Long-term effects of ocean warming on the prokaryotic community: Evidence from the vibrios. ISME Journal 6(1):21-30.

Warnert, J. 2007. Expanded research to target E. coli outbreaks. California Agriculture 61(1):5.

Wayadande, A., J. Talley, A. Gerry, U. DeSilva, and J. Fletcher. 2011. Filth Flies as Disseminators of Human Pathogens. Chemical and Biological Defense Science and Technology Conference. Las Vegas; Presented November 15, 2011.

Wilkie, D. S., and J. F. Carpenter. 1999. Bushmeat hunting in the Congo Basin: An assessment of impacts and options for mitigation. Biodiversity and Conservation 8(7):927-955.

A8

ONE HEALTH AND FOOD SAFETY

Lonnie J. King¹⁴

Introduction

The concept of One Health is not new but it has reemerged as an important concept to both understand and help address our contemporary challenges and threats to our health.

We live in a world that is rapidly changing, complex, and progressively more interconnected. The convergence of people, animals, and our environment has created a new dynamic—one in which the health of each group is now profoundly and inextricably linked and elaborately connected.

Inherent in this new dynamic is the changing interface between people and animals, including animal products. The human—animal interface is accelerating, expanding, and becoming increasingly more consequential. Over the past three decades, approximately 75 percent of new human infectious diseases have been zoonotic. The global population has now exceeded 7 billion people, and an estimated 30 billion food animals were produced to help feed this population and meet its growing demand for protein from animal sources. The result is a phenomenal global food system that is both a major agricultural and business accomplishment and an unparalleled challenge that is creating major societal issues that, to some extent, threaten human, animal, and environmental health (FAO, 2006).

As a further consequence, the safety of our food is being increasingly scrutinized and questioned by the public, and food-borne illnesses are significant, costly, and a global problem. There continue to be differences of opinion on how to improve food safety, and we lack an integrated and holistic strategy for implementation in the United States and much of the world. While we acknowledge some success in controlling and ameliorating food-borne illnesses and food contamination, these achievements are uneven, often transitory, and especially difficult. Ensuring a safe food supply will likely demand new levels of collaboration, understanding, and thinking. The application of a One Health model where potential solutions are viewed and delivered more holistically and with an emphasis on prevention is a compelling and timely strategy.

One Health Defined

One Health is the collaborative effort of multiple disciplines—working locally, nationally, and globally to attain optimal health for people, animals, and

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¹⁴ The Ohio State University.

our environment (King et al., 2008). The scale and complexity of food safety issues demand that scientists, researchers, and others move beyond the confines of their own disciplines, professions, and mindsets and explore new organizational modes of team science, and the One Health concept embodies this declaration. The scope of One Health is impressive, broad, and growing. Much of the recent focus of One Health has been limited to emerging infectious diseases, yet the concept clearly embraces environmental and ecosystem health, social sciences, ecology, noninfectious diseases and chronic diseases, wildlife, land use, antimicrobial resistance, biodiversity, and much more. While these components are appreciated within our understanding of the broad dimensions of health, they also add to the complexity of One Health and the difficulty in implementing strategies, building effective coalitions, and mobilizing scientific communities who embrace One Health yet who have been trained and think in much narrower scope and scale. Although there may be disagreement on the exact definition of One Health there is broad consensus that a new framework for preventing food-borne diseases is essential rather than the alternative of constantly responding to them reactively.

“Wicked” Problems

We now live in a world that is complex, interconnected, and uncertain, with growing dilemmas and unprecedented societal problems. These problems have been referred to as “wicked problems” and are contrasted with “tame problems,” which can be solved with existing modes of inquiry, technological knowledge, and decision making. Wicked problems are complex, do not have yes-or-no answers, can generate unexpected consequences, may be symptomatic of other problems, and are unique in that past experiences and thinking are not helpful in addressing them. In addition, wicked problems and issues often crop up as organizations face constant change and unparalleled challenges, and they often occur in a social context with diverse opinions from numerous stakeholders who lack consensus in both identifying the total problem and how to resolve them (Brown et al., 2010).

Issues and problems connected with food safety, food security, sustainable production systems that ensure environmental protections, and the capacity to help feed more than 7 billion people collectively qualify as a societal and wicked dilemma. Ensuring safe, accessible, affordable, and nutritious food is increasingly difficult, especially in a global context. Central to this challenge is the development of a One Health strategy and a new level of thinking and acting.

The world population has a growth rate of 1.2 percent per year and the next century will represent a period of exponential growth. There is also a significant demographic fault line between the population growth in developed versus developing countries. Approximately 90 percent of the world’s population growth is occurring in the developing countries of the world. In addition almost 1 billion people live in peri-urban or slum settings in the developing world’s largest cities,

and these sites are where the most rapid growth in our human populations will continue (Smith and Kelly, 2008).

While there is also legitimate concern about the approximately 800 million people who are undernourished, we are concurrently observing a relative increase in wealth in the developing world and as per capita incomes rise; people eat more calories and consume different products, including a demand for meat and protein from animal sources. Today, 3 to 4 billion people consume very little meat but will consume more, should incomes increase. Thus, a new agricultural phenomenon is emerging: the Livestock Revolution. With relative increases in wealth and technological advances in livestock and poultry production, global increases in production and consumption of livestock products are unavoidable. The Food and Agriculture Organization (FAO) estimates that there will be a demand for a 50 percent increase for animal proteins in the next one to two decades. Thus, the entire global food system will adjust into a more intensive, specialized, and integrated system, and production systems will progressively shift to the developing world (Delgado et al., 1999).

As the Livestock Revolution ushers in a rapidly expanding animal agriculture production system in the developing world, there is real concern regarding the animal and public health infrastructures available to support this revolution. The United States now imports approximately 15 percent of its food, but it imports a much higher percentage of seasonable fruits, vegetables, and seafood (Acheson, 2010). The need for inspecting these products is growing much more quickly than the regulatory system now in place to implement such safeguards.

Concurrently, there is unprecedented immigration and movement of people worldwide. Unique diasporas have emerged, and there are large numbers of immunocompromised individuals dispersed throughout the United States and global populations who are especially susceptible to infections including food-and water-borne illnesses. In many countries, the population of seniors is one of the fastest growing cohorts.

There is also a disconnect between global commerce and the remarkable movement of food in trade channels and the commensurate emphasis and assurance of safe food. There is a significant gap between an emphasis on the rapidly growing commerce and business of global food companies and an equal emphasis and investment to address the potential health consequences generated by global food and animal commerce (Kimball, 2010). The 21st century has created a great mixing bowl of people, animals, and animal products and a group of wicked problems, including the protection and safety of our food, that demands a transformation of thought and actions to address these contemporary challenges, threats to our health and well-being, and threats to animal and environmental health that are under increasing pressure. A holistic and integrated approach considering these domains in a One Health strategy is both logical and essential to further success.