1
Surveillance Strategies

OVERVIEW

This chapter includes workshop presentations that illustrate a variety of goals, approaches, and methodologies for disease surveillance in humans, animals, and plants. As noted in the chapter’s first paper by keynote speaker Patrick Kelley, director of the Institute of Medicine’s Board on Global Health, current concepts of public health surveillance, inspired by approaches to military intelligence data gathering, originated in the 1950s. Today, traditional surveillance practices of disease reporting (by physicians, veterinarians, infection control practitioners, laboratorians, and medical examiners), followed by epidemiological and laboratory investigation, constitute the mainstay of local infectious disease surveillance where such expensive methods are feasible (mainly in developed countries). However, a range of nontraditional strategies including syndromic surveillance (the topic of Kelley’s paper, and another in this chapter by Michael Stoto) and electronic surveillance (the subject of Chapter 2), may prove well suited to settings where clinicians, laboratories, and hospitals are in short supply.

Local Surveillance: New York City

Although New York City’s size, diversity, and significance to international transportation create considerable opportunities for infectious outbreaks, local approaches to surveillance resemble those of many communities around the world, according to presenter Marci Layton of the New York City Department of Health and Mental Hygiene (DOHMH). New York health codes mandate disease reporting for more than 70 infectious diseases, ranging from common



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary 1 Surveillance Strategies OVERVIEW This chapter includes workshop presentations that illustrate a variety of goals, approaches, and methodologies for disease surveillance in humans, animals, and plants. As noted in the chapter’s first paper by keynote speaker Patrick Kelley, director of the Institute of Medicine’s Board on Global Health, current concepts of public health surveillance, inspired by approaches to military intelligence data gathering, originated in the 1950s. Today, traditional surveillance practices of disease reporting (by physicians, veterinarians, infection control practitioners, laboratorians, and medical examiners), followed by epidemiological and laboratory investigation, constitute the mainstay of local infectious disease surveillance where such expensive methods are feasible (mainly in developed countries). However, a range of nontraditional strategies including syndromic surveillance (the topic of Kelley’s paper, and another in this chapter by Michael Stoto) and electronic surveillance (the subject of Chapter 2), may prove well suited to settings where clinicians, laboratories, and hospitals are in short supply. Local Surveillance: New York City Although New York City’s size, diversity, and significance to international transportation create considerable opportunities for infectious outbreaks, local approaches to surveillance resemble those of many communities around the world, according to presenter Marci Layton of the New York City Department of Health and Mental Hygiene (DOHMH). New York health codes mandate disease reporting for more than 70 infectious diseases, ranging from common

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary pathogens such as Salmonella to the potentially disastrous, such as smallpox and anthrax. The health department receives reports by traditional phone, mail, and fax and—following a significant recent investment—by electronic and web-based methods as well. Participation in an electronic clinical laboratory reporting system, a secure network that allows DOHMH to receive laboratory-confirmed diagnoses in a timely manner, is mandated for all laboratories that diagnose New York City residents. This system enables DOHMH to spot citywide and neighborhood disease trends in routinely reported data that an individual physician would not be able to recognize, Layton said. Upon receiving a report, DOHMH initiates an investigation to examine risk factors for infection in order to determine disease transmission routes, and, if appropriate, to arrange prophylaxis. “The most important thing we try to do is to make sure that every health care provider knows who and how to call to make a report,” Layton said. In the event of an apparent or actual public health emergency, New York City’s health alert system quickly disseminates information to providers on the nature of the emergency and instructions on preparing and delivering diagnostic specimens. Because New York City is at high risk for receiving imported disease, DOHMH stays attuned to global infectious disease issues via surveillance networks such as ProMED-mail (see Morse in Chapter 2) and responds to reports of significant disease activity abroad by ramping up surveillance and alerting health-care providers in New York City to look for signs of an outbreak. After an outbreak of West Nile virus in 1999, and in light of increasing concern regarding the potential use of zoonotic diseases as bioterrorism agents, animal diseases were made reportable in New York City in 2000. DOHMH has invested considerable hospital-preparedness funding to improve the ability of triage systems to recognize patients with significant risk factors for infectious disease, particularly patients with fever and respiratory illness who have traveled recently. This is crucial because, in Layton’s words, “New York City could be the next Toronto, with an unrecognized imported outbreak of severe acute respiratory syndrome (SARS)—or of bioterrorism, E. coli, or most worrisome of all, avian influenza.” The realization that many unreported, hospitalized cases of viral encephalitis (a reportable disease) manifested during the West Nile virus outbreak caused DOHMH to adopt procedures to monitor similar nonspecific clinical syndromes. In 1998, the city began syndromic surveillance based on ambulance dispatch data; the system was expanded to monitor the entire emergency department in the wake of the 2001 World Trade Center attack, then further to monitor pharmacy sales, employee health, school absenteeism, and primary care visits. One of the most challenging aspects of responding to a syndromic signal is getting specimens to a lab for diagnostic testing, Layton observed, particularly specimens from the acutely ill patients typically seen in emergency departments. Rapid diagnostic testing is performed for a variety of pathogens at a single New

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary York City hospital, but only limited information is obtained from this proof-of-concept project. To better balance time spent investigating syndromic surveillance signals versus outbreaks detected through traditional means, DOHMH is developing a protocol to reduce time wasted on false positives while ensuring the prompt investigation of real outbreaks. Syndromic surveillance systems have proven to be most useful for monitoring citywide seasonal outbreaks of infectious diseases (e.g., norovirus, influenza, respiratory syncytial virus [RSV]), Layton said, and less useful for detecting localized outbreaks. “In my view, syndromic surveillance will never replace traditional surveillance, which is where most surveillance resources should continue to be invested,” she concluded. “The real public health challenge lies in creating the necessary infrastructure to analyze surveillance data, set priorities, and conduct investigations. I am concerned that increased investment in syndromic surveillance may occur at the expense of state and local public health infrastructure. More generally, if current funding patterns continue, whereby national programs addressing emerging infections and bioterrorism receive more and public health at the state and local levels receive less, our ability to make use of surveillance information will suffer.” Toward Earlier Warning Through the use of prediagnostic data, syndromic surveillance aims to provide timelier identification of disease outbreaks than can be attained through traditional surveillance methods, Kelley writes. After reviewing the theoretical underpinnings and historical development of syndromic surveillance, he discusses its potential applications in developing countries and its promise as a vehicle for achieving global disease surveillance as mandated in recent revisions of the International Health Regulations (IHRs). Unfortunately, “hasty, opportunistic implementations of syndromic surveillance,” including some U.S. projects, “have not allowed the theoretical power of the method a fair test,” he observes. In their stead, Kelley advocates the creation of surveillance systems, including syndromic components, designed to answer clear and specific questions. He also considers how syndromic surveillance could be applied to detect serious but low-frequency threats such as bioterror attacks, SARS, or avian influenza in time to contain their further spread. Following Kelley’s paper, with its focus on the design of syndromic surveillance systems, Stoto’s essay considers their evaluation. He defines and applies a framework for gauging the usefulness of syndromic surveillance in public health practice, then uses it to identify a number of statistical and practical challenges to using such surveillance for detecting bioterrorist events. By contrast, he finds promise in using syndromic surveillance to detect natural disease outbreaks (including seasonal and pandemic influenza), and in monitoring public health

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary response to disease outbreaks. Realizing this potential will require designing systems that focus on these uses rather than being optimized for timely detection of large-scale bioterrorist attacks, Stoto concludes. The next paper, by Joseph Lombardo of the Johns Hopkins Applied Physics Laboratory, addresses another aspect of timeliness in surveillance: the implications of “real-time” versus “batch reporting” of surveillance information. Noting that confusion has arisen around the use of these terms, Lombardo carefully defines them and provides illustrative examples. He concludes by describing the possible combination of both modes in surveillance systems that use efficient “batched” surveillance processes for the routine monitoring of public health, and more resource-intensive “real-time” processes to examine specific threats as they arise. Surveillance of Animal and Plant Diseases Recognizing that “the health of people, animals, plants, and the environment in which we all live are inextricably linked,” in the words of workshop presenter William Karesh, surveillance must encompass far more than human diseases. Karesh’s contribution to this chapter describes initial efforts toward this goal, focusing on projects undertaken by his own organization, the Wildlife Conservation Society (WCS). He describes the threat spectrum, origins, risk factors, and consequences of infectious disease in wild animals, and he observes that “the immediate effects of the diseases themselves are often the least of the worries. Infectious diseases of people and animals are drivers of poverty and associated civil unrest, disrupt ‘free’ ecosystem services such as drinking water and plant pollination, and can ruin otherwise well-planned and sustainable economic development efforts.” In two papers that conclude the chapter, plant pathologists Jacqueline Fletcher of Oklahoma State University and James Stack of Kansas State University define threats (both natural and intentional) to U.S. crops and provide examples of high-consequence plant diseases. The first paper outlines components of a strong plant biosecurity strategy, discusses progress toward its achievement, and notes opportunities for further improvement. In the second paper, the authors evaluate each component of the biosecurity strategy (prevention, surveillance, detection, diagnosis, response, and recovery) and suggest specific actions the United States could take to support each area.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary SYNDROMIC SURVEILLANCE: MOVING FROM THEORY TO PRACTICE Patrick W. Kelley, M.D., Dr.P.H.1 The National Academies Assessing the health of a community has similarities to assessing the health of a person. A variety of detectors of ill health can be brought to bear in ways that range from passive monitoring that depends on those affected to raise a concern to active and aggressive monitoring of those apparently without complaint to identify the earliest manifestations of a problem. The desire for earlier detection of acute health problems at either the individual or community level has in recent years stimulated the search for better “detector” mechanisms. Syndromic surveillance is one of these now in vogue as a solution to the growing challenge of early disease detection in communities and management of consequent public health interventions. Though infectious disease reporting started in Europe and the United States in the late 1800s, it was not until 1925 that all U.S. states participated in national morbidity reporting. Only after Alex Langmuir went to the Centers for Disease Control and Prevention (CDC) in 1950 did the term “surveillance” become conceptualized beyond the monitoring contacts of persons with contagious diseases. At CDC Langmuir developed a concept of surveillance inspired by military intelligence data gathering and incorporated the approach into daily public health practice. Soon CDC had national systems for malaria, polio, and influenza. In more recent times, advances in laboratory and mathematical methods and technologies have pushed horizons farther and stretched academic definitions. These cutting-edge approaches to disease detection at the community level encompass networks for surveillance using molecular fingerprinting and exciting, web-based methods of information capture and assessment such as the Program for Monitoring Emerging Diseases (ProMED) and the Canadian-World Health Organization (WHO) Global Public Health Intelligence Network (GPHIN). In this more demanding context, we now have the evolution of automated syndromic surveillance. The elaboration of more sophisticated approaches to surveillance has been stimulated by the recognition over the past 30 years of at least 30 “new” emerging infectious diseases. These encompass infections of plants, animals, and human beings. Of course, an acute concern is the threat of bioterrorism but many naturally occurring emerging disease outbreaks have highlighted the need for rapid detection and characterization. Perhaps the greatest concern now is the need to promptly recognize the syndromic pattern of an H5N1 influenza outbreak, here 1 Director, Board on Global Health and Director, Board on African Science Academy Development, Institute of Medicine.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary or in remote parts of Asia or Africa, so that aggressive attempts to eliminate it can be instituted before it becomes uncontainable. Similar urgency arose during the 2003 severe acute respiratory syndrome (SARS) epidemic. For some of these emerging infections, it was months before an agent was isolated, and thus timely and sensitive public health surveillance and response was syndromic to a great degree. The tragedies of HIV in Africa and the slow recognition of SARS in China are reminders of the consequences of slow responses and motivate the question of what surveillance system designs could have made a difference. With bioterrorism a rapid assessment and response is even more critical. “Syndromic surveillance” is defined by CDC as the collection and analysis of “health-related data that precede diagnosis and signal with sufficient probability of a case or an outbreak to warrant further public health response” (CDC, 2006a). This differs from more traditional surveillance in several ways but primarily the objective is that by using prediagnostic data, syndromic surveillance aims to be timelier in identifying emerging problems. The phenomena of emerging infections and all the associated aspects of globalization that accompany them, as well as the specter of bioterrorism, drive the need to be more cognizant of public health events and to act despite limited information. Timeliness is not the only advantage of the method, though. An additional goal is that syndromic surveillance should be more sensitive at detecting aberrations in normal patterns because it does not depend on confirmed diagnoses, something that can be an expensive proposition, especially in developing countries. Some advocates have great enthusiasm for transitioning syndromic surveillance from the epidemiologic laboratory into routine practice, but others are skeptical, preferring to put their confidence in traditional approaches and the “astute clinicians” who have risen to the occasion so often in this country. Unfortunately, while developed countries have a fair number of clinicians who are astute at least much of the time, the developing world, where so many disease problems emerge, is a different case. A system of complementary systems—including clinicians, traditional methods, and well-designed syndromic surveillance tailored to the setting of a particular community—may ultimately yield the wide range of perspectives needed to meet the demanding public health challenges of emerging infections and globalization. The best mix of surveillance interventions will vary from community to community. A challenge now is to do the operations research to adapt academic surveillance concepts to unique community circumstances. This is important not only in communities with strong health systems, but also in developing countries, where nontraditional approaches may be more essential and affordable than in places with a relative abundance of astute clinicians, laboratories, and hospitals, such as the United States. Some observers seem frustrated by syndromic surveillance because it has detected few outbreaks, as implemented in the United States over the past few years. Many doubt that it will perform better than alternative mechanisms to alert the public health community to a problem. Perhaps though hasty, opportunistic

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary implementations of syndromic surveillance have not allowed the theoretical power of the method a fair test. Also, the purposes of syndromic surveillance go beyond earlier detection and provide situational awareness across a community, something that individual clinicians can rarely provide. Though other mechanisms, to include astute clinicians, may help recognize a problem, an effective surveillance system, syndromic or otherwise, should also rapidly characterize a problem epidemiologically because this is essential to efficiently target what are invariably limited response assets. A system should enable civic leaders to establish the boundaries of the problem and allay some unjustified fears through more credible risk communication. In tabletop exercises of public health crises, the value of information for management has been highlighted both as being in short supply and as being something that a properly constructed syndromic surveillance system should help develop. In one important biodefense tabletop simulation exercise, “Dark Winter,” Frank Keating, former governor of Oklahoma, said: You can’t respond and make decisions unless you have the crispest, most current, and best information. And that’s what strikes me as a civil leader … that is … clearly missing (O’Toole et al., 2002). Central to effective surveillance is beginning with a clear appreciation for the capabilities sought. Precisely what phenomena need detection, in precisely what populations is the detection needed, and what data would be most effective for that purpose? Much work has been accomplished in developing syndromic definitions and analytic algorithms but before syndromic surveillance is seen as the solution, the full range of scenarios that need to be detected must be considered as well as how best to build epidemiologic “detectors” for demographically different communities in both rich and poor countries. Although in the United States there is a tendency to associate syndromic surveillance with the specter of bioterrorism, WHO has come to recognize that the protection of global health against emerging infections was poorly served by the last version of the International Health Regulations (IHRs), which mandated reporting to WHO only three specific diseases: yellow fever, plague, and cholera. Realizing that some of the most critical recent global public health threats—such as AIDS, SARS, Ebola, pandemic influenza, and Nipah virus—initially were ill-defined syndromes, a new version of the IHRs has been adopted by member states and is set to go into effect in 2007. This document calls on countries to maintain, at the local level, capabilities to detect and assess not only well-defined diseases and established causes of death, but also to report any significant levels of morbidity of potential international public health importance. So, the mandate for general global public health surveillance is moving beyond defined diseases to encompassing a global responsibility to detect and report, in a timely manner, internationally important disease events whether they are well or ill defined and

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary whether they are individual cases or clusters. A capability for syndromic detection seems central to the new paradigm, especially in countries that lack the resources for extensive use of more specific approaches. Although the term “syndromic surveillance” has only been in vogue for about a decade and is thought to represent somewhat of a frontier in surveillance, the potential contributions of “prediagnostic surveillance” have been long established. In tracking down the last cases of smallpox and polio in developing countries, syndromic monitoring has been central. For decades, the military has also used syndromic approaches to monitor unit health on deployments and in training because it was the most cost-effective, rapid, and reliable way to monitor the health of the force, especially in austere conditions. The military often operates in settings with limited laboratory support, but with a critical need to detect health threats in a timely manner. For example, Figure 1-1 illustrates the tracking of diarrheal syndromes in a U.S. Marine force during the first Gulf War of 1990–1991. With regular syndromic tracking of morbidity seen in sick call, outbreaks were routinely recognized quickly by competent epidemiologists against normal background rates. Investigations were launched rapidly to contain problems that could debilitate unit combat effectiveness. In U.S. military basic training camps, where respiratory syndromes are particularly devastating, for decades there has been well-developed, centrally monitored syndromic surveillance for acute respiratory syndromes (Gray, 2005; Gunzenhauser, 2003). Syndromic surveillance in the basic training setting has been used routinely to guide the use of mass antibiotic prophylaxis to prevent outbreaks of rheumatic fever when syndromically associated thresholds are crossed. FIGURE 1-1 Syndromic surveillance of U.S. marines for treated diarrheal syndromes during the lead-up to the Persian Gulf War, 1990–1991. SOURCE: Hanson (2005).

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary All of these practical implementations of syndromic surveillance reflect movement from theory and simple systems to complex systems. Moving from theory to practice involves a larger context where pieces must be made to work together and adapted to the locality. Reflecting all the elements to be integrated, one might define a surveillance system, as distinct from surveillance, as follows: A system for public health surveillance is a group of integrated and quality-assured, cost-effective, and legally and professionally acceptable processes, designed for the purpose of identifying in an ongoing, flexible, standardized, timely, simple, sensitive, and predictive manner the emergence of meaningful epidemiologic phenomena and their specific associations. These processes include human, laboratory, and informatics activities to skillfully manage information derived from an entire defined community (or a subgroup thereof that is sufficiently representative and large) and to disseminate that information in a timely and useful manner to those able to implement appropriate public health interventions. As shown in Figure 1-2, a surveillance system needs to be seen in the context in which it works and as reflecting a hierarchy of elements that depend on each other. One needs a clear and specific idea of what questions the system should address. Who should be under surveillance and for what are most critical. Developers of syndromic surveillance systems often start to conceptualize FIGURE 1-2 Conceptual steps in development and implementation of a syndromic surveillance system in a community. SOURCE: Kelley (2006).

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary a system with opportunistically available data rather than a clear definition of the range of scenarios that their surveillance system must be able to recognize as priorities. Typical “opportunistic” data might be routinely collected for other purposes during an emergency room consultation or from “convenient” sources such as government clinics regardless of how well they sample the community of interest. Opportunistic datasets are rarely the strongest cornerstone on which to build and can handicap an otherwise rigorous implementation. Different epidemiologic scenarios will affect populations in different ways. Key though is that if one wants to detect any epidemiologic scenario, the population under surveillance should include the one likely affected. If space and time separate these populations, as may be the case with the most easily available “opportunistic” datasets, little signal will be generated. If demographic misclassification affects the description with respect to person, place, and time, associations may be missed. If one lets the surveillance question drive the development of the database used, there is a better chance that the population under surveillance will generate a strong signal because it will include a substantial fraction of those exposed. Resources should be invested into negotiating for and developing data with the richest “veins of ore” rather than focusing it proportionately on the mining of poorly conceived data sources with ever more complex analytic methods. An example of this became obvious in looking at convenient outpatient data in the Department of Defense (DoD) Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE), developed in the late 1990s for use for surveillance in the National Capital Region. Like syndromic surveillance systems, the datasets initially available to ESSENCE routinely classified patients experiencing morbidity by the ZIP code of residence. The problem is that one could reasonably assume that most exposures, natural or manmade, would occur away from home in places such as the Pentagon, the Capitol, a sports venue, or the subway. As became evident in a geographic analysis, the bulk of military health-care beneficiaries tracked through ESSENCE did not live where many exposures would most likely occur, in the District of Columbia, but rather had homes scattered over a hundred ZIP codes throughout the region. This residence-based misclassification, stemming from the use of “opportunistic data” easily at hand, would have greatly diluted syndromic signals arising from exposures at the workplace. This misclassification produces what might be termed the “donut-hole effect” (Figure 1-3). As exposed persons migrate from a center city worksite of exposure, where they might be classified most effectively as an “exposed” population, they disperse into the suburbs, where they blend with unexposed populations so completely that any signal is greatly damped out. Overcoming this depends on not settling for datasets of convenience. Populations in which those under medical surveillance have limited geographic mobility can help correct for the donut-hole effect. Students at universities might be one example. Residents of nursing homes and prisons may be other populations where there is less risk that place of

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary FIGURE 1-3 The donut-hole effect. SOURCE: Kelley (2006). exposure and place of residence differ. Another setting is military basic training. However, a limitation of many of these populations is that they may not be near the locations where surveillance is most critically needed, making their ability to serve as sentinels less than ideal. With the DoD ESSENCE, some of the most impressive syndromic signals have come from basic training outbreaks, where the exposed population lived and worked in the same location. This meant there was no problem with the migration phenomena causing people exposed in one place to be classified geographically in another. The strength of the signal and its rapid detection was also greatly facilitated by the ability to attribute morbidity to a well-defined denominator population that included most cases. For populations on the move, if they work in high-value targets such as centers of government, it may be a high-yield investment to develop a way to ensure that they can be classified by both their primary residence and primary workplace. In moving from syndromic surveillance theory to practice, the first step is appreciating not what data are at hand, but what are the “who, what, and when” questions that need to be answered. The most effective surveillance systems will likely be systems of systems because the questions to be answered will reflect

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary education. One conceptual approach to the development of plant biosecurity infrastructure is based on a simple outbreak model. In its simplest form, this model includes the following components: the source of the outbreak agent; the introduction of the agent into some new environment; the detection of that agent at some point after the introduction event; the accurate diagnosis of the new agent at some point after the detection event; the response to the outbreak; and the resolution of the outbreak. Each component requires a unique strategy for preparedness: potential introductions require a prevention strategy; detection requires a surveillance strategy; diagnosis requires a technology strategy; response requires a communications and mitigation strategy; and resolution requires a recovery strategy. Prevention The U.S. Departments of Agriculture (USDA) and Homeland Security (DHS) share responsibility for preventing the introduction of new plant pathogens and insect pests that threaten our plant systems. This is accomplished through the activities and programs of Customs and Border Protection (CBP) and USDA’s Animal and Plant Health Inspection Service Plant Protection and Quarantine (USDA-APHIS-PPQ). Due to the extremely large and increasing volume of imports of plants and plant products, port and border inspections can never be 100 percent effective in preventing the accidental or intentional introduction of new agents. The increase in Internet-based commerce further adds to this challenge by providing a means to circumvent the inspection and quarantine process associated with interstate and international trade. Consequently, we must anticipate the introduction of agents that threaten our plant systems, whether accidental due to global trade, intentional due to terrorism or crime, or natural due to weather events (e.g., hurricanes). A prevention strategy should include the capability to intercept those agents with a high probability of introduction and establishment. Several lists of high-consequence pathogens and pests have been generated by government agencies and scientific societies. One such list identified more than 500 plant pathogens and nematodes and over 700 insects and mites that pose threats to U.S. plant systems (Huber, 2002). We lack the resources necessary to develop specific plans for over 1,200 organisms. Because there is no defining set of characteristics to determine which threat agent will become established and cause significant damage, a prioritization process is needed to identify those high consequence agents with the greatest potential to cause persistent, wide-scale damage such that specific interception protocols are required. For example, if a new race of a pathogen emerged with the potential to destroy over 50 percent of the U.S. wheat crop, its characteristics indicate that the pathogen will establish and spread, there are no effective management tools, and pathways for pathogen introduction exist, then a comprehensive preparedness, response, and recovery strategy should be developed for that specific pathogen.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary Surveillance, Detection, and Diagnosis An Institute of Medicine study identified six critical elements necessary to a food safety system (IOM, 1998). These same six elements would provide the framework for biodefense against threats to national food security (King, 1999). Among those elements was a comprehensive surveillance and monitoring system. This element is as important for plant-based systems as it is for human and animal systems. For the purposes of this paper, surveillance is the process of searching, detection is the process of finding, and diagnosis is the process of determining and/or verifying what is found. The National Plant Diagnostic Network (NPDN) was established by USDA in 2002 to provide the necessary critical infrastructure to facilitate early detection and rapid diagnosis of disease and pest outbreaks in natural and agricultural plant systems (Stack et al., 2006). This is accomplished through the primary mission areas of building infrastructure for diagnostics and communications and through training and education programs that target first detectors and diagnosticians. Surveillance and detection We should assume that introductions will continue to occur as a result of global trade and the increasing threats of intentional introductions due to bioterrorism and biocrime. If the projections for increased trade and climate change are accurate, it is quite possible that the frequency and severity of introductions will increase. Our current surveillance and detection systems vary significantly according to plant system, target pathogen or pest, and geographic region. Funding for surveillance of plant systems is most often allocated for specific target agents; consequently, those programs are executed only in areas at risk. Because of limited funding, general surveillance at the field level is minimal. For some plant systems, industry has implemented very effective surveillance programs, and the data are provided to APHIS. Mechanisms to share data are being explored. Among the major limitations to an effective surveillance system is not having enough trained personnel in the field. Unlike human and animal systems, in which doctors and veterinarians are distributed throughout rural and agricultural areas, few plant doctors with diagnostic expertise operate at the local level with plant-based systems. NPDN, in collaboration with Cooperative State Research, Education, and Extension Service (CSREES), APHIS, the Extension Disaster Education Network, and the Regional Integrated Pest Management (IPM) Centers, has developed a training and education program targeting first detectors at the local level. Its registry of trained first detectors may serve as a resource for outbreak management. Diagnosis NPDN was established to provide a triage system for the rapid and accurate diagnosis of introduced plant pathogens and insect pests. Because of a decline in national and local support for plant diagnostics over many years, state labs varied tremendously in diagnostic infrastructure and experience. With

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary funding from USDA, NPDN has rebuilt and enhanced much of that infrastructure and implemented programs to train diagnosticians in the latest diagnostic technologies (Stack et al., 2006). Morse identified three elements for an effective early warning system; clinical recognition, epidemiological investigation capability, and laboratory capacity (Morse, 2002). NPDN has become an integral component for early warning and NPDN labs provide surge diagnostic support during outbreaks. NPDN has created a national database for the diagnostic data collected at the network labs. An NPDN epidemiology group is developing data analysis tools that include syndromic analysis. Many of the issues and challenges associated with syndromic surveillance in human systems (Stoto, 2005; Stoto et al., 2004) also apply to plant systems. Because there are many natural introductions in plant systems, syndromic surveillance might prove to be a useful approach. Coordination and communication among all the disciplines will be important. Response Response to plant disease outbreaks resulting from new pathogen introductions is a responsibility of USDA APHIS. For most introductions, APHIS provides the leadership for a coordinated response that often includes APHIS-led rapid deployment teams, state departments of agriculture, industry, and in some cases, land grant university diagnostic labs. An elaborate structure exists within APHIS for the development of response plans to high-consequence pathogens and pests. NPDN, in partnership with APHIS and state departments of agriculture, has developed and implemented a training exercise program to facilitate preparedness for outbreak response. All 50 states have participated in at least one exercise involving local, state, and federal governments, as well as state, regional, and national diagnostic labs. The exercise scenario makes clear the roles and responsibilities of all participants. After the exercise scenario, action reports are analyzed to identify areas in need of improvement. Recovery (A Superficial Treatment) Recovery, which follows response, is the strategy by which to return a system to the preevent mean or to a new, but stable, mean. An effective recovery strategy will be comprehensive in nature and include short-term plans that address the transition from response to the new system mean, while long-term plans will need to address prevention and recovery from subsequent introductions. The scope of recovery plans vary as a function of the scale of the outbreak and the ripple effects throughout the national and global economies. While response revolves around outbreak delineation, containment, eradication, and management, recovery is focused on local and system-level issues, including ecological impacts,

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary production shortfalls, effects on transportation systems, impacts on trade agreements, market reentry strategies, and replacement markets or systems. Mandated by Homeland Security Presidential Directive 9 (HSPD-9), the National Plant Disease Recovery System (NPDRS) was established within the USDA Agricultural Research Service. NPDRS has involved other federal agencies (e.g., APHIS and CSREES), state departments of agriculture, scientific societies, and universities in the development of national response plans for the Select Agents and other high-consequence pathogens. Among the challenges of an effective plant disease recovery strategy will be to find cost-effective solutions for low profit margin systems. Deriving a cost–benefit premium that achieves sustainable plant systems without significantly raising the percentage of the U.S. income spent on food or without causing irreversible ecosystem damage will be challenging. One goal for such a strategy would be establishing mechanisms for national cooperation among public and private sectors and international cooperation that facilitates collaboration without compromising trade. The true cost of risk reduction is not known. More effective predictive models for invasiveness, impacts, and recovery outcomes will be needed. To date, NPDRS has focused on response plans. The challenge for NPDRS will be to transition into the development of recovery strategies in the face of increasing introductions that call for more response plans. Challenges The Select Agent Paradox The Select Agent program includes a requirement for the identification of high-consequence plant pathogens and toxins having a reasonable potential to cause significant ecological or economic damage and the potential for deliberate introduction. Once a pathogen is designated as a Select Agent, strict laws regulate its possession, handling, and dissemination. Responsibility for managing a plant disease outbreak caused by a Select Agent resides with APHIS. If it is suspected or determined that the introduction was intentional, then the Federal Bureau of Investigation would share primary responsibility. The original Select Agent list for plant pathogens included 10 pathogens (see Fletcher and Stack earlier in this chapter). Since its adoption, at least four of these agents have been introduced into the United States either accidentally as a result of trade (Ralstonia solanacearum, Liberobacter asiaticus, Plum pox virus) or naturally as a result of a weather event (Phakopsora polysora) (Stokstad, 2004). Two of those agents are now considered to be endemic and were removed from the Select Agent list. Once removed from the list, the management of the threat agent shifted from primarily a federal responsibility to primarily a state and local responsibility.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary The utility and effectiveness of the Select Agent program should be reviewed. At best, it reduces the potential for an accidental escape from a domestic lab and impedes the illicit acquisition of a viable culture or toxin preparation from a domestic lab or commercial culture collection. At worst, it precludes achieving a state of preparedness at the state and local levels. Pathway analyses indicate that for most of the Select Agents, there is an equal or greater probability of being introduced accidentally or naturally than intentionally. If these agents are truly the organisms of greatest concern, we should be encouraging many of our scientists to conduct the research necessary to ensure that we can detect them quickly, diagnose them correctly, and respond effectively to minimize the potential negative impact. If working with these agents is too difficult for U.S. scientists then we will not be building the necessary expertise for the organisms that pose the greatest threat to the country. A reevaluation of the goals and effectiveness of the Select Agent Rule should be executed with specific reference to the unintended consequences that impair preparedness and response. Animal and Plant Health Inspection Service The authority for regulating high-consequence plant pathogens and insect pests resides within APHIS. Responsibilities include providing emergency response to outbreaks; issuing permits for interstate transport and international importation of pathogens and pests; coordinating national and regional pest surveys; providing training programs; and developing and validating diagnostic protocols. Most of these tasks are time sensitive and resource intensive, sometimes with significant legal ramifications. Yet, among the USDA agencies, APHIS has historically received the least funding. Its level of support seems disproportionate to its responsibility. If we are to develop and maintain a national state of preparedness in the face of increasing plant pathogen and pest introductions, increased support within USDA for APHIS and increased support within APHIS for plant programs will be necessary. Sampling Sampling underpins the successful implementation of every strategy on which a successful biosecurity program depends. A sampling protocol depends on the characteristics of the target agent, the environment in which it exists, and the matrix from which it is to be sampled. Consequently, much effort should be applied to the development and validation of the methods deployed. However, the extremely large number of potential threat agents in plant systems precludes implementation of a comprehensive sampling strategy for each agent. Therefore, more general sampling strategies are needed that increase the probability of interception for a wide array of agents.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary Formulating and implementing a national strategy for recovery from single or multiple introductions to plant systems is a challenge beyond the mission of any single agency or department. It will require the coordination of several government departments at the local, state, and federal levels; public and private educational institutions; and the many industries that support plant systems in the United States. As has been identified for zoonotic disease surveillance (Dudley, 2004), a central body with responsibility for plant disease health that would develop a national strategy does not exist. Summary There are many challenges to achieving plant biosecurity within the United States and across the world. The success of U.S. agriculture has made possible a high standard of living with a safe, inexpensive, and dependable food supply system. But it has also left us complacent with respect to food production. Educational programs are needed to increase awareness among the general population and among policy makers regarding the interdependence of plant, animal, and human systems. Appropriately, human systems have the greatest value in society and require the greatest investment of our time and resources. Sustenance of healthy human and animal systems requires healthy plant systems. Having less value does not mean having little value. The world at the beginning of the 21st century is vastly different than it was at the beginning of the 20th century. Among the challenges to sustainable living systems are globalization, climate change, population growth, and bioterrorism/biocrime. There is neither a single strategy nor a single technology that will ensure the security of our living systems. The benefits of globalization are tremendous, but so too are the risks if we do not prepare for the consequences with respect to emerging diseases of humans, animals, and plants. Consequently, all nations must be secure if any nation is to be secure. Through modern transportation systems and international commerce, some of the natural barriers (e.g., oceans) to the dispersal of pathogens have been circumvented or eliminated. Most plant pathogens once took decades to disperse naturally around the world. Through normal commerce it may now take only a few days to a few weeks. Two introductions of the Select Agent Ralstonia solanacearum r3b2 in 2003 and 2004 from Kenya and Guatemala, respectively, are good examples. The threat of intentional introduction could reduce that dispersal interval to one day. Historically, pathogens have moved naturally and accidentally among nations around the world. However, the rate of their border crossings has increased dramatically, resulting in drastically reduced time to prepare for an introduction. International cooperation is essential to achieve plant biosecurity. The importance of global management of disease outbreaks to minimize large-scale impacts was justified effectively for animal and human diseases (Karesh and Cook, 2005).

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary The same case can be made for plant diseases. Many of the plant pathogens that have caused epidemics in North America over the past 150 years were introduced from Africa, Asia, Europe, and South America. Intuitively, the health and stability of plant production systems in the United States depends on good plant surveillance systems in other parts of the world. Improved cooperation among nations is required for prevention and rapid outbreak intervention. REFERENCES Adam, G.2006. Significant ways to spread plant virus diseases in agricultural ecosystems: Is agroterrorism possible? In Virus diseases and crop biosecurity, edited by J. I. Cooper, T. Kuene, and V. P. Polischuk. New York: Springer. Pp. 45-54. American Phytopathological Society Public Policy Board. 2002. First line of defense, http://www.apsnet.org (accessed May 1, 2007). APHIS (Animal and Plant Health Inspection Service). 2007. Citrus greening, http://www.aphis.usda.gov/plant_health/plant_pest_info/citrus_greening/index.shtml (accessed July 23, 2007). Banner Engineering Corp. 2007. PresencePLUS glossary, http://www.baneng.com/literature_resources/reference/glossary_pplus.html (accessed April 30, 2007). Brown, K. 2001. Florida fights to stop citrus canker. Science 292(5525):2275-2276. Buckeridge, D. L., D. K. Owens, P. Switzer, J. Frank, and M. A. Musen. 2006. Evaluating detection of an inhalational anthrax outbreak. Emerging Infectious Diseases 12(12):1942-1949. Budowle, B., J. Burans, R. G. Breeze, M. R. Wilson, and R. Chakraborty. 2005a. Microbial forensics. In Microbial forensics, edited by R. Breeze, B. Budowle, and S. Shutzer. Burlington, MA: Elsevier Academic Press. Pp. 1-26. Budowle, B., M. D. Johnson, C. M. Fraser, T. J. Leighton, R. S. Murch, and R. Chakraborty. 2005b. Genetic analysis and attribution of microbial forensics evidence. Critical Reviews in Microbiology 31(4):233-254. Budowle, B., S. E. Schutzer, M. S. Ascher, R. M. Atlas, J. P. Burans, R. Chakraborty, J. J. Dunn, C. M. Fraser, D. R. Franz, T. L. Leighton, S. A. Morse, R. S. Murch, J. Ravel, D. L. Rock, T. R. Slezak, S. P. Velsko, A. C. Walsh, and R. A. Walters. 2005c. Toward a system of microbial forensics: From sample collection to interpretation of evidence. Applied and Environmental Microbiology 71(5):2209-2213. Buehler, J. W., R. L. Berkelman, D. M. Hartley, and C. J. Peters. 2003. Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases 9(10):1197-1204. Carefoot, G. L., and E. R. Sprott. 1969. Famine on the wind; plant disease and human history. London, England: Angus and Robertson. Casagrande, R. 2000 (Fall/Winter). Biological terrorism targeted at agriculture: The threat to U.S. national security. The Nonproliferation Review: 92-105, http://cns.miis.edu/pubs/npr/vol07/73/73casa.pdf (accessed May 1, 2007). CDC (Centers for Disease Control and Prevention). 2003. Estimated sensitivity of West Nile virus surveillance methods, http://www.cdc.gov/ncidod/dvbid/westnile/misc/slides/roehrig/slide27.htm (accessed May 31, 2007). CDC. 2006a. Syndromic surveillance: An applied approach to outbreak detection, http://www.cdc.gov/epo/dphsi/syndromic.htm (accessed April 26, 2007). CDC. 2006b. E. coli O157:H7 outbreak case counts by state, http://www.cdc.gov/foodborne/ecolispinach/case_count_us_map.htm (accessed May 10, 2007). CDC. 2006c. Timeline for reporting of E. coli cases, http://www.cdc.gov/ecoli/reportingtimeline.htm (accessed April 26, 2007).

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary CDC. 2006d. Multistate outbreak of E. coli O157 infections linked to Taco Bell, http://www.cdc.gov/ecoli/2006/december/index.htm (accessed April 19, 2007). CDC. 2007. Overview of influenza surveillance in the United States, http://www.cdc.gov/flu/weekly/pdf/flu-surveillance-overview.pdf (accessed April 19, 2007). CIDRAP (Center for Infectious Disease Research and Policy). 2003. Overview of agricultural biosecurity, http://www.cidrap.umn.edu/cidrap/content/biosecurity/ag-biosec/biofacts/agbiooview.html (accessed May 31, 2007). Diamond, J. 2005. Collapse: How societies choose to succeed or fail. New York: Viking Penguin. Dudley, J. P. 2004. Global zoonotic disease surveillance: An emerging public health and biosecurity imperative. BioScience 54(11):982-983. FDA (Food and Drug Administration). 2001. Survey of domestic fresh produce: Interim results, http://www.cfsan.fda.gov/~dms/prodsur9.html (accessed May 1, 2007). FDA. 2006. Nationwide E. coli O157:H7 outbreak: Questions and answers, http://www.cfsan.fda.gov/~dms/spinacqa.html (accessed April 26, 2007). FDA. 2007. FDA finalizes report on 2006 spinach outbreak, http://www.fda.gov/bbs/topics/NEWS/2007/NEW01593.html (accessed May 1, 2007). Feng, G., E. Bailes, D. L. Robertson, Y. Chen, C. M. Rodenburg, S. F. Michael, L. B. Cummins, L. O. Arthur, M. Peeters, G. M. Shaw, P. M. Sharp, and B. H. Hahn. 1999. Origin of HIV-1 in the chimpanzee Pan troglodytes troglodytes. Nature 397(6718):436-441. Fletcher, J. 2006. Plant disease surveillance and detection. Paper presented at the Institute of Medicine Forum on Microbial Threats, Washington, DC, December 12-13. Fletcher, J., C. L. Bender, W. T. Cobb, S. E. Gold, C. A. Ishimaru, D. G. Luster, U. K. Melcher, R. L. Murch, H. Scherm, R. C. Seem, J. L. Sherwood, B. Sobral, and S. A. Tolin. 2006. Plant pathogen forensics: Capabilities, needs and recommendations. Microbiology and Molecular Biology Reviews 70(2):450-471, http://mmbr.asm.org/cgi/reprint/70/2/450/ (accessed May 1, 2007). Gottwald, T. R., J. H. Graham, and T. S. Schubert. 2002. Citrus canker: The pathogen and its impact. Plant Health Progress, http://www.apsnet.org/online/feature/citruscanker/ (accessed May 30, 2007). Gray, G. C., B. Feighner, D. H. Trump, S. W. Berg, M. J. Zajdowicz, and T. R. Zajdowicz. 2005. Diseases spread by close personal contact. In Military preventive medicine: Mobilization and deployment Vol. 2, edited by P. W. Kelley. Washington, DC: Office of the Surgeon General, U.S. Army. Pp. 1117-1211. Gunzenhauser, J. D. 2003. Communicable disease control in basic training: Programmatic aspects. In Military preventive medicine: Mobilization and deployment Vol. 1, edited by P. W. Kelley. Washington, DC: Office of the Surgeon General, U.S. Army. Pp. 173-194. Hanson, K. 2005. Disease and nonbattle injury surveillance: Outcome measure for force health protection. In Military preventive medicine: Mobilization and deployment Vol. 2, edited by P. W. Kelley. Washington, DC: Office of the Surgeon General, U.S. Army. P. 719. Health Data Standards: The Players. 2007. http://faculty.washington.edu/ocarroll/infrmatc/database/data/players.htm (accessed April 30, 2007). Homeland Security Council. 2005. National strategy for pandemic influenza. Washington, DC: Department of Health and Human Services, http://www.pandemicflu.gov/plan/federal/index.html (accessed April 19, 2007). Huber, D. M. 2002 (March). Invasive pest species: Impacts on agricultural production, natural resources, and the environment. Council for Agricultural Science and Technology Issue Paper 20, http://downloads.heartland.org/04664i.pdf (accessed May 25, 2007). IEEE-TCRTS (Institute of Electrical and Electronics Engineers, Inc. Technical Committee on Real-Time Systems). 2007. About IEEE-TCRTS, http://cs-mailman.bu.edu/mailman/listinfo/ieee-tcrts (accessed April 30, 2007). IOM (Institute of Medicine). 1998. Ensuring safe food from production to consumption. Washington, DC: National Academy Press.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary IOM. 2003. Microbial threats to health: Emergence, detection, and response. Washington, DC: The National Academies Press. IOM/NRC (National Research Council). 2006. Globalization, biosecurity and the future of the life sciences. Washington, DC: The National Academies Press. Pp. 15-138. Jackson, M. L., A. Baer, I. Painter, and J. Duchin. 2006. Systematic comparison of algorithms used in syndromic surveillance. Advances in Disease Surveillance 1:35. Karesh, W. B., and R. A. Cook. 2005 (July/August). The human–animal link. Foreign Affairs: 38-50. 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, http://www.cdc.gov/ncidod/EID/vol11no07/pdfs/05-0194.pdf (accessed May 25, 2007). Kelley, P. 2006. Syndromic surveillance: Moving from theory to practice. Keynote address at the Institute of Medicine Forum on Microbial Threats, Washington, DC, December 12-13. King, L. 1999. A domestic legislative agenda for improving food safety and safeguards from terrorist attacks on the U.S. food supplies and U.S. agricultural interests. Annals of the New York Academy of Sciences 894:228-232. Labus, B. 2005. Practical applications of syndromic surveillance: 2003–2004 influenza season. Emergency Preparedness E-newsletter, http://bt.naccho.org/E-newsletter-archive/SS-Influenza.htm (accessed April 19, 2007). Large, E. C. 1940. The advance of the fungi. New York: Dover Publications. Leroy, E. M., P. Rouquet, P. Formenty, S. Souquière, A. Kilbourne, J.-M. Froment, M. Bermejo, S. Smit, W. Karesh, R. Swanepoel, S. R. Saki, and P. E. Rollin. 2004. Multiple Ebola virus transmission events and rapid decline of Central African wildlife. Science 303(5656):387-390, http://www.sciencemag.org/cgi/content/abstract/303/5656/387?etoc/ (accessed May 25, 2007). Lindley, C., and T. Ward. 2007. Experience with clinician-based syndromic surveillance in West Texas. Advances in Disease Surveillance 2:108, http://www.isdsjournal.org/article/view/862/745 (accessed April 19, 2007). Lombardo, J. S. 2006. Implications of “real time” versus “batch reporting” for surveillance. Presentation at the Institute of Medicine Forum on Microbial Threats, Washington, DC, December 12-13. Lombardo, J. S., and D. L. Buckeridge. 2007. Disease surveillance: A public health informatics approach. Hoboken, NJ: John Wiley & Sons. Lu, J., K. Konty, F. Mostashari, and K. Metzger. 2006. Could outpatient visits enhance our ability of early detecting influenza-like illness outbreaks? Advances in Disease Surveillance 1:44. MacKenzie, W., N. Hoxie, M. Proctor, M. Gradus, K. A. Blair, D. E. Peterson, J. J. Kazmierczak, D. G. Addiss, K. R. Fox, and J. B. Rose. 1994. A massive outbreak in Milwaukee of cryptosporidium infection transmitted through the public water supply. New England Journal of Medicine 331(3):161-167. Madden, L., and M. Wheelis. 2003. The threat of plant pathogens as weapons against U.S. crops. Annual Reviews of Phytopathology 41:155-176. Mandl, K. D., J. M. Overhage, M. M. Wagner, W. B. Lober, P. Sebastiani, F. Mostashari, J. A. Pavlin, P. H. Gesteland, T. Treadwell, E. Koski, L. Hutwagner, D. L. Buckeridge, R. D. Aller, and S. Grannis. 2004. Syndromic surveillance: A guide informed by the early experience. Journal of the American Medical Informatics Association 11(2):141-150. Maslanka, S. E., J. Sobel, and B. Swaminathan. 2002. Reducing the risk: Foodborne pathogen and toxin diagnostics. In Biological threats and terrorism: Assessing the science and response capabilities. Institute of Medicine. 2002. Washington, DC: The National Academies Press. Microsoft Encarta. 2007. http://encarta.msn.com/encnet/refpages/search.aspx?q=batch&Submit2=Go (accessed April 30, 2007). Morse, S. S. 2002. The vigilance defense. Scientific American 287(4):88-89.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary Murch, R. S. 2003. Microbial forensics: Building a national capacity to investigate bioterrorism. Biosecurity and Bioterrorism: Biodefence Strategy, Practice, and Science 1(2):117-122. Newcomb, J. 2003. Biology and borders: SARS and the new economics of bio-security. Cambridge, MA: Bio-Economics Research Associates. Oerke, E. C., H. W. Dehne, F. Schonbeck, and A. Weber. 1994. Crop production and crop protection: Estimated losses in major food and cash crops. Amsterdam, The Netherlands: Elsevier Science BV. OIE (Office International des Epizooties). 2004. Avian influenza—Belgium ex Thailand: Smuggled birds (02): OIE. ProMED http://www.promedmail.org, archive number: 20041027.2907 (accessed May 25, 2007). Olson, D. R., R. T. Heffernan, and F. Mostashari. 2005. Age matters: Emergency department syndromic surveillance for epidemic influenza. Paper presented at the National Syndromic Surveillance Conference, Seattle, Washington, September 14-15, 2005. Osofsky, S. A., S. Cleaveland, W. B. Karesh, M. D. Kock, P. J. Nyhus, L. Starr, and A. Yang, eds. 2005a. Conservation and development interventions at the wildlife/livestock interface: Implications for wildlife, livestock and human health. Gland, Switzerland and Cambridge, United Kingdom: IUCN. Pp. xxxiii and 220. Osofsky, S. A., R. A. Kock, M. D. Kock, G. Kalema-Zikusoka, R. Grahn, T. Leyland, and W. B. Karesh. 2005b. Building support for protected areas using a ‘one health’ perspective. In Friends for life: New partners in support of protected areas, edited by J. A. McNeely. Gland, Switzerland and Cambridge, United Kingdom: IUCN. Pp. 65-79. O’Toole, T., M. Mair, and T. Inglesby. 2002. Shining light on “Dark Winter.” Clinical Infectious Diseases 34(7):972-983. Peres, C. A. 2000. Effects of subsistence hunting on vertebrate community structure in Amazonian forests. In Hunting for sustainability in tropical forests, edited by J. G. Robinson and E. L. Bennett. New York: Columbia University Press. Pp. 168-198. Pimentel, D., L. Lach, R. Zuniga, and D. Morrison. 2000. Environmental and economic costs of nonindigenous species in the United States. Bioscience 50(1):53-65. Pinstrup-Andersen, P. 2001. The future world food situation and the role of plant diseases. Plant Health Instructor, http://www.ifpri.org/pubs/articles/2001/pinstrup01_01.pdf (accessed May 1, 2007). Pivonia, S., and X. B. Yang. 2004. Assessment of the potential year-round establishment of soybean rust throughout the world. Plant Disease 88(5):523-529. Potter, P. 2004. “One medicine” for animal and human health [about the cover]. Emerging Infectious Diseases 10(12), http://www.cdc.gov/ncidod/EID/vol10no12/about_cover.htm (accessed May 2, 2007). Rogers, P., S. Whitby, and M. Dando. 1999. Biological warfare against crops. Scientific American 280(6):70-75. Schneider, R. W., C. A. Hollier, H. K. Whitam, M. E. Palm, J. M. McKemy, J. R. Hernández, L. Levy, and R. DeVries-Paterson. 2005. First report of soybean rust caused by Phakopsora pachyrhizi in the continental United States. Plant Disease 89:774. Schumann, G. L. 1991. Plant diseases: Their biology and social impact. St. Paul, MN: APS Press. Sebastiani, P., K. Mandl, P. Szolovits, I. S. Kohane, and M. F. Ramoni. 2006. A Bayesian dynamic model for influenza surveillance. Statistics in Medicine 25(11):1823-1825. Sosin, D. M., and J. DeThomasis. 2004. Evaluation challenges for syndromic surveillance—making incremental progress. Morbidity and Mortality Weekly Report 53(Suppl):125-129, http://www.cdc.gov/mmwr/preview/mmwrhtml/su5301a25.htm (accessed May 9, 2007). Stack, J., K. Cardwell, R. Hammerschmidt, J. Byrne, R. Loria, K. Snover-Clift, W. Baldwin, G. Wisler, H. Beck, R. Bostock, C. Thomas, and E. Luke. 2006. The National Plant Diagnostic Network. Plant Disease 90:128-136.

OCR for page 45
Global Infectious Disease Surveillance and Detection: Assessing the Challenges—Finding Solutions: Workshop Summary Stokstad, E. 2004. Plant pathologists gear up for battle with dread fungus. Science 306(5702): 1672-1673. Stoto, M. A. 2005 (Spring). Syndromic surveillance. Issues in Science and Technology:49-56. Stoto, M. A., M. Schonlau, and L. T. Mariano. 2004. Syndromic surveillance: Is it worth the effort? Chance 17(1):19-24. Stoto, M. A., R. D. Fricker, A. J. Jain, A. Diamond, J. O. Davies-Cole, C. Glymph, G. Kidane, G. Lum, L. Jones, K. Dehan, and C. Yuan. 2006. Evaluating statistical methods for syndromic surveillance. In Statistical methods in counter-terrorism, edited by D. Olwell, A. G. Wilson, and G. Wilson. New York: Springer. Pp. 141-172. Stoto, M. A., B. A. Griffin, A. Jain, J. O. Davies-Cole, G. Lum, G. Kidane, S. C. Washington. 2007. Fine-tuning and evaluation of detection algorithms for syndromic surveillance. Advances in Disease Surveillance 2:213. Takahashi, H., P. Keim, A. F. Kaufmann, C. Keys, K. L. Smith, K. Taniguchi, S. Inouye, and T. Kurata. 1994. Bacillus anthracis incident, Kameido, Tokyo, 1993. Emerging Infectious Diseases 10(1):117-120, http://www.cdc.gov/ncidod/EID/vol10no1/pdfs/03-0238.pdf (accessed April 26, 2007). 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. Series B, Biological Sciences 356(1411):983-989. Tu, C., G. Crameri, X. Kong, J. Chen, Y. Sun, M. Yu, H. Xiang, X. Xia, S. Liu, T. Ren, Y. Yu, B. T. Eaton, H. Xuan, and L. F. Wang. 2004. Antibodies to SARS coronavirus in civets. Emerging Infectious Diseases 10(12):2244-2248, http://www.cdc.gov/ncidod/EID/vol10no12/04-0520.htm (accessed May 25, 2007). USDA-ERS (U.S. Department of Agriculture, Economic Research Service). 2007. Soybeans and oil crops, http://www.ers.usda.gov/Briefing/SoybeansOilCrops/ (accessed May 1, 2007). Wagner, M., F. C. Tsui, J. U. Espino, V. M. Dato, D. F. Sittig, R. A. Caruana, L. F. McGinnis, D. W. Deerfield, M. J. Druzdzel, and D. B. Fridsma. 2001. The emerging science of very early detection of disease outbreaks. Journal of Public Health Management and Practice 7(6):50-58. Wheelis, M., R. Casagrande, and L. V. Madden. 2002. Biological attack on agriculture: Low-tech, high impact bioterrorism. Bioscience 52(7):569-576. Whitby, S. M. 2001. The potential use of plant pathogens against crops. Microbes and Infection 3(1):73-80. Whitby, S. M. 2002. Biological warfare against crops. Basingstoke, UK: Palgrave Macmillan. Wilkie, D. S., and J. F. Carpenter. 1999. Bushmeat and hunting in the Congo Basin: An assessment of impacts and options for mitigation. Biodiversity and Conservation 8(7):927-955.