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2 Climate, Ecology, and Infectious Disease OVERVIEW As depicted in the convergence model of infectious disease emergence, illustrated in Figure SA-4, climate interacts with, and can alter, the complex ecological relationships underlying infectious disease transmission patterns. This chapter examines such interactions from several perspectives: â¢ Their consequences throughout the aquatic-marine food web, which defines ecological relationships for water-dwelling animals â¢ In patterns of distribution and transmission dynamics of individual infec- tious diseases (cholera, Rift Valley fever, chikungunya, and plague) â¢ Their effects on the dynamics of plant diseases, and their effects on agri- culture and natural ecosystems â¢ As manifested in the public health challenges posed by climate change to human populations in the Arctic Research on the effects of climate variation on infectious disease incidence and geographic range in these diverse contexts is providing the basis for devel- oping climate-based early warning systems for disease risk. Such studies also represent a necessary first step toward anticipating how climate change may alter infectious disease dynamics in various ecological frameworks. In her workshop presentation, Leslie Dierauf, director of the U.S. Geologi- cal Surveyâs National Wildlife Health Center in Madison, Wisconsin, described the apparent and predicted effects of climate on a broad cross-section of animal species that inhabit fresh- and saltwater ecosystems, as well as the intertidal 104
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 105 zones that unite aquatic and marine environments. Ecological connections among these environments are illustrated in Figure SA-8, which depicts the marine food web. Dierauf also emphasized the physical connectedness of aquatic and marine environments, which makes it possible for infectious diseases of fish and wild- life to move from freshwater sources to intertidal zones to marine environments, affecting species that may not have encountered these disease agents before. Salmon, for example, hatch in small freshwater streams, travel hundreds of kilo- meters downstream to the ocean where they live for several years, only to return to the same streams where they hatched to spawn and die shortly thereafter. Thus, she observed, âif the temperature of the streams changes or the fish themselves pick up novel disease agents, because a vector, or an intermediate host, or a disease agent thrives in the new warmer environment, infectious disease may result.â Evidence-based studies of the effects of climate change on the health of aquatic and marine wildlife are few, Dierauf reported; therefore, current under- standing of this topic derives from such sources as historical comparisons (of climatic conditions and of animal health and behaviors), long-term ecological research, correlation studies, and recognition of the physical, chemical, and biological processes governing climate change. Following the flow of water from inland streams to estuaries and into the open ocean, Dierauf considered the possible impacts of climate change in each of the three main elements of the aquatic continuum and how these changes may affect the health of their animal inhabitants. In freshwater ecosystems, extreme weather events that produce flooding can trigger overwhelming influxes of nutrients into ecosystems. Storms can cause a range of environmental disturbances; Dierauf described the release of Nile tila- pia into Mississippi streams from aquaculture facilities damaged by Hurricane Katrina. Several emerging diseases of inland aquatic animals, described and depicted in Box SA-2 in the Summary and Assessment, may also be influenced by climate change. Intertidal areas, such as salt marshes and estuaries, are essential for main- taining a delicate balance among many complex and interactive variables (such as temperature, light, salinity, wave action, sea level rise, erosion, and sediment deposition) that characterize the transition from freshwater to saltwater environ- ments, Dierauf explained. Storms, such as hurricanes, greatly affect intertidal zones. Heavy inland rainfall increases the speed and volume of the run-off that reaches estuaries, while marine storms drive saltwater and its contents past the intertidal buffer, affecting inland ecosystem health. Climate change is expected to produce a range of important effects on oceans (as well as on large, deep-water lakes such as the Great Lakes), according to Dierauf. These include increased wave intensity, increased nutrient turnover, changes in nutrients, and changes in the food web. In addition, she noted, higher
106 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS concentrations of atmospheric carbon dioxide are dramatically increasing the acidity of ocean waters, which in turn is weakening the carbonate shells and skeletons of many marine species that comprise coral reef systems. She also noted the effects of harmful algal blooms (HABs), which are thought to result from nutrient influxes to the ocean (see Summary and Assessment). HABs appear to be increasing in both frequency and size as the climate warms, she said; this could result from increased upwelling of nutrients within the ocean or changes in ocean currents, as well as from the effects of extreme weather events inland. âWhat we do know is that HABs are affecting and often killing living things in the food web, like zooplankton, shellfish, fish, birds, and marine mammals, like manatees,â she said. Ocean warming, which is reducing the availability of food and sea ice for marine mammals, may also be compromising their resistance to infectious dis- ease, Dierauf said. âAlready, climate change and thinning of sea ice has reduced the time mother polar bears have to build the fat stores they need to sustain themselves over winter and to feed their young come spring when they emerge from their dens,â she noted. Faced with shortages of food in their native waters, some marine mammals move to new territories where they both encounter and introduce novel disease agents (see Summary and Assessment). âClimate change and climate variability will affect aquatic and marine spe- cies worldwide,â Dierauf concluded. âWe must act now at personal, professional, local, and global levels to protect vulnerable ecosystems and the aquatic and marine species that depend on these habitats for survival.â In contrast to the broad perspective on the effect of climate change on aquatic ecosystems offered by Dierauf, this chapterâs first paper, by Rita Colwell of the University of Maryland, focuses on the specific and well-characterized effects of climate on cholera, a water-borne disease that affects an estimated 100,000 people per year, resulting in 10,000 deaths. The incidence and distribution of cholera are controlled by water temperature, precipitation patterns, and water salinityâall of which are influenced by global climateâand conducted through a complex web of ecological relationships. Sanitation and infrastructure also play a role in the incidence and distribution of cholera. Colwell noted, however, that âby simply educating women to filter drinking water through several layers of âsari cloth,â we were able to reduce cholera incidence by 50 percent.â Colwell described how, over the course of decades, she and coworkers deduced the circumstances under which the causal agent of cholera, the bacterium Vibrio cholerae, is transmitted to humans by the plankton species with which the bacterium associates. This knowledge led to the development of remote sensing systems capable of predict- ing the onset of cholera epidemics in the Ganges delta, known as the âhome of cholera,â because of its long history of epidemic disease. This chapterâs second paper also describes the use of remote sensing to monitor the effects of climate variation on specific infectious diseases. Speaker Jean-Paul Chretien, of the Department of Defense Global Emerging Infections
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 107 Surveillance and Response System (DOD-GEIS), and coauthors describe the use of satellite and epidemiological data to examine connections between the El NiÃ±o/Southern Oscillation (ENSO) and recent epidemics of two mosquito-borne viral diseases: Rift Valley fever (RVF) and chikungunya fever. In the first case, the association of RVF outbreaks in East Africa with periods of heavy rainfall, which occur during the El NiÃ±o phase of ENSO, led researchers to develop a model to forecast RVF risk in that region based on vegetation density (a marker for rain- fall), as measured by satellite (Linthicum et al., 1999). The authors describe the operation of this model in the El NiÃ±o season of 2006-2007, when its prediction of elevated risk of disease prompted intensified surveillance for RVF in Kenya and, ultimately, to an international effort to stem a pending epidemic. Chikungunya fever caused a series of outbreaks along the Kenyan coast in 2004, from which it apparently spread to several western Indian Ocean islands and India, resulting in the largest chikungunya fever epidemic on record (Chretien et al., 2007). At the time of the initial outbreaks in Kenya, a regional droughtâ corresponding to the La NiÃ±a phase of ENSOâhad gripped the region. Chretien and coauthors discuss several possible, nonexclusive mechanisms connecting the epidemic with the drought, some of which may have also have influenced the first appearance of chikungunya fever in Europe in 2007. In the chapterâs third paper, speaker Nils Stenseth of the University of Oslo provides a much longer view of climate variation and its effects on infectious dis- ease dynamics. Throughout recorded history, the various forms of plague, caused by the bacterium Yersinia pestis and transmitted by fleas among a wide range of hosts, are known to have caused both endemic and epidemic disease. Stenseth examines the dynamic ecology and epidemiology of plague in its ancient reser- voir in Central Asia, and compares these patterns with local climate variation over the course of decades (as recorded in regular measurements of temperature and rainfall) and centuries (as reflected in tree-ring data for the past 1,000 years). Using data collected twice annually between 1949 and 1995 in Kazakhstan, a focal region for plague where human cases are regularly reported, Stenseth and colleagues determined that Y. pestis prevalence increases dramatically in its primary host, the great gerbil (Rhombomys opimus), during warmer springs and wetter summers (Stenseth et al., 2006). Rodent populations also tend to increase under these conditions and, along with them, the possibility that plague will be transmitted to humans. Analyses of historical climate variation, as reflected in tree-ring patterns, suggest that similar warm, wet conditions existed in Central Asia during the onset of the Black Death in the fourteenth century, as well as in the years preceding a mid-nineteenth-century plague pandemic. As Earthâs climate warms, warmer springs and wetter summers are expected to become more common in Central Asia (as well as in North America) therefore raising the possibility that plague activityâand therefore the potential for epidemic diseaseâwill increase. âAlthough the number of human cases of plague is relatively low, it would
108 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS be a mistake to overlook its threat to humanity, because of the diseaseâs inherent communicability, rapid spread, rapid clinical course, and high mortality if left untreated,â Stenseth notes. Moreover, he adds, even a minor plague outbreak can result in panic, with severe economic repercussions; a 1994 plague outbreak in India that caused 50 deaths also led to a nationwide collapse in tourism and trade, costing the nation an estimated $600 million (Fritz et al., 1996). âPlague remains a fairly poorly understood threat that we cannot afford to ignore,â Stenseth concludes. âOnly by knowing more about how the eco-epidemiological plague systems in the different parts of the world will respond to given climate scenarios can we take the necessary precautionary measures to reduce the risks of human infections.â While climate-based early warning systems for human disease are in an early stage of development, plant disease forecasting systems based on variables such as temperature and precipitation have been used for many years, according to speaker Karen Garrett of Kansas State University. However, she adds, these well- established models will need to be adapted (based on sound science) to account for climate change, as will plant disease management policies that flow from climate-based forecasts. In her contribution to this chapter, Garrett establishes a framework for this critical effort. She describes standard methods for managing plant disease, reviews observed effects of climate variation on plant diseases and their implications given projected future climatic conditions, and discusses research and policy needs for plant disease management in response to climate change. In considering the consequences of climate change for plant health, Garrett emphasizes threshold effects: environmental perturbations that produce disproportionate ecological upheaval. Examples of such thresholds include longer growing seasons; pathogen introductions and range shifts; pathogen overwinter- ing; and the removal of constraints on pathogen reproduction at a critical popula- tion size. Much as it has been argued that the most effective available protective mea- sures against the adverse human health effects of climate change are basic public health interventions (see Campbell-Lendrum in Chapter 4), Garrett observes that âthe good news for formulation of strategies for plant disease management under changing climate conditions is that much of what needs to be done is the same with or without climate change.â Thus, she advocates research to advance our understanding of plantsâ adaptive capacities and mechanisms, and policies to encourage the development of âdiverse, flexible, and resilient agricultural systems that can adapt more readily to new climatic conditions.â The chapterâs final paper, by Alan Parkinson of the Centers for Disease Control and Preventionâs (CDCâs) Arctic Investigations Program in Anchor- age, Alaska, presents a panoramic view of the public health challenges faced by people living in the Arctic, where the physical effects of climate change are dramatically apparent. Temperatures in this region have increased at nearly twice the global average over the past century, causing widespread melting of land and
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 109 sea ice (see Figure SA-13; Borgerson, 2008; IPCC, 2007). These conditions are exposing the Arcticâs human inhabitants, many of whom have limited access to public health and/or sanitation services, to an increasingly broad range of infectious disease threats (among other health challenges). Parkinson describes the observed and projected effects of climate change in the Arctic environment, discusses the direct effects of higher ambient temperatures on the health of Arctic inhabitants, and catalogs the many ways in which climate change may increase the risk of infectious disease for Arctic residents. Indeed, Parkinson observes, infectious disease risks are already increasing in the Arctic through the indirect influence of climate change on the populations and ranges of disease vector species (e.g., mosquitoes, ticks) and the population den- sity and range of reservoir hosts that can transmit disease (e.g., rodents, foxes). Flooding and the loss of permafrost are also damaging the sanitation infrastruc- ture of Arctic communities, thereby increasing the risk of water-borne infectious diseases, respiratory diseases, and skin infections. Meanwhile, increasing mean ambient temperatures raise the risk of food-borne diseases, particularly for Arctic residents who rely on traditional methods of subsistence and food preservation (e.g., fermentation, air-drying, burying). In the face of these public health challenges, Parkinson recommends a range of public health responses, including monitoring of high-risk, climate-sensitive infectious diseases with potentially large public health impacts (e.g., water-borne diseases such as giardiasis), prompt investigation of infectious disease outbreaks that may be related to climate change, and research on the relationship between climate and infectious disease emergence to guide early detection and public health interventions. He also encourages the creation of infectious disease moni- toring networks to connect typically small, isolated Arctic communities and link them to regional, national, and international health organizations. Such networks would encourage the standardization of monitoring methods, the sharing of data, and the detection of infectious disease trends over a larger geographic area. THE MARINE ENVIRONMENT AND HUMAN HEALTH: THE CHOLERA MODEL Rita Colwell, Ph.D. University of Maryland Cholera, a disease I have studied for more than 30 years, is a model of the complex interactions between climate, ecology, environment, and weather related to epidemics of infectious diseases. Revealing choleraâs secrets has required inter- â Chairman, Canon U.S. Life Sciences, Inc., and Distinguished University Professor at both the ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ University of Maryland at College Park and at the Johns Hopkins University Bloomberg School of Public Health.
110 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS disciplinary research examining all of these influences, as well as a point of view that I call biocomplexity: recognizing that infectious diseases operate on a wide range of time and space scales. Thus, we employ gene probes, environmental measurements (ground truth), and other precise techniques for pathogen detec- tion, but at the same time, we take a holistic approach that integrates informa- tion from the atomic to the atmosphericâand perhaps, in some cases, even the cosmicâin order to build a predictive model for cholera outbreaks. Cholera is a significant, global public health problem, as shown in Table 2-1. Annually, it results in approximately 100,000 hospitalizations and approximately 10,000 deaths, varying from year to year. A few cases of cholera appear each year in the United States, usually associated with seafood harvested from closed beds near sewage outfalls in the Gulf of Mexico. Most of my groupâs research on cholera has focused on the Ganges delta, which feeds into the Bay of Bengal. This area is known as the home of cholera due to spring and fall epidemics, of varying but predictable intensity, that have recurred there for hundreds of years (see Figure 2-1). During the monsoon sea- son, flooding rains wash nutrients down from the Himalayas, while winds drive water from the Bay of Bengal up into the Ganges and its tributaries, creating ideal conditions (discussed later) for cholera outbreaks. The fall 2007 epidemic, which followed massive flooding, was catastrophic. The Center for Diarrheal Disease TABLE 2-1â Cholera Cases Officially Reported to WHO, 2004âSelected Countries Number Mortality Country of Cases Imported Deaths Rate (%) Benin 642 9 1.40 Burundi 819 14 1.71 Cameroon 8,005 137 1.71 Comoros 1 0 0.00 CÃ´te dâIvoire 105 9 8.57 DROC (Congo) 7,665 228 2.97 Niger 2,178 57 2.62 Nigeria 3,186 185 5.81 Somalia 4,490 26 0.58 Uganda 3,380 91 2.69 Tanzania 10,319 272 2.64 Zambia 12,149 373 3.07 Zimbabwe 119 9 7.56 India 4,695 7 0.15 Japan 66 55 0 0.00 Singapore 11 1 1 9.09 Total 57,830 56 1,418 2.45 SOURCE: WHO (2005).
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 111 FIGURE 2-1â Bangladesh border, barrier islands, and location of Dacca, Matlab, Math- baria, and Bakerganj. SOURCE: Printed with permission from Google. 2-1 Bitmapped Research in Dacca admitted about a thousand new cases per day for almost 30 days and had to use temporary space to house cholera victims. We are working to create predictive models to provide advance warning of conditions that produce severe epidemics in this region of the world. However, V. cholerae, the bacterium, is a natural inhabitant of rivers, estu- aries, and coastal waters throughout the world. Currently, we are sequencing approximately 50 different strains of Vibrio cholerae, the causative agent of cholera collected from many geographic locations to examine their genetic rela- tionships. Preliminary sequencing studies of V. cholerae collected at a depth of 2,000 m at a site located off the coast of Oregon indicate that those isolates may represent ancestral strains; interestingly, one strain studied in detail has genes in common with other Vibrio pathogens, as well, including Vibrio vulnificus and Vibrio parahaemolyticus, the latter being the most common food-borne pathogen in Asian countries, where raw seafood is consumed.
112 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS The Ecology of Cholera My laboratory accomplished the first isolation of Vibrio cholerae from the Chesapeake Bay more than two decades ago, and we now know that this bacte- rium is found in estuaries of similar salinity, (ca. 15 parts per thousand), where the water temperature rises seasonally to 15ÂºC or higher and where an influx of nutrients encourages plankton blooms (Colwell, 1996). Other species of Vibrio, including V. parahaemolyticus and V. vulnificus, also thrive under these condi- tions. One of my current graduate students, Brad Haley, has just returned from Iceland, where he was able to isolate V. cholerae at locations where geothermal effluent flows into bays. Clearly, water temperature is critical to the growth of this pathogen. Vibrio cholerae also has a dormant state, which it assumes between epi- demics and during which it cannot be cultured but can be detected with probes (fluorescent antibodies and gene signature sequences). Only during the peak of the zooplankton bloom, in the spring and the fall, is V. cholerae easily culturable. We were able to show that by adding nalidixic acid and nutrient (yeast extract) to water containing the quiescent bacterium, we can stimulate cell elongation and metabolism. Another important discovery was that cholera is transmitted by plankton. Thus, it is not enough to say that its growth correlates with sea surface tempera- ture and salinity; it is important to recognize the ecological interactions that pro- duce these correlations. There is a commensal relationshipâwhich may prove to be symbiosisâbetween Vibrio bacteria and zooplankton. Vibrios are chitinolytic (i.e., capable of breaking down chitin, the material that forms the carapaces of zooplankton and crustaceans (e.g., crabs, shrimp). V. cholerae also produces a powerful proteolytic enzyme that the bacterium apparently uses to perform an additional function for zooplankton: breaking down its egg sac, enabling the eggs to disperse into the water column. We are discovering that interactions between V. cholerae and various zooplankton species are quite intricate; for example, certain strains of the bacterium attach preferentially to certain species of zooplankton (Rawlings et al., 2007). All of this leads to the conclusion that V. cholerae is integral to marine ecosystems, and therefore cannot be eradicated. The Epidemiology of Cholera We have determined in earlier studies that between 10,000 and 50,000 Vib- rio cholerae bacteria may be attached to an individual copepod (the zooplankton favored by V. cholerae). A liter of water drawn by a villager from a pond in Bangladesh between epidemics may contain 10 copepods. However, during a zooplankton bloom, that concentration can increase a hundredfold or more per liter, carrying a dose of cholera bacteria sufficient to cause cholera. The severity of the disease is dose dependent: a low concentration of bacterial cells will pro-
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 113 duce mild diarrhea; hospitalized casesâwhich represent about 25 percent of all infectionsârequire more since one million bacteria per milliliter has been shown to be required to produce the disease. Thus, it has been estimated that only 25 percent of those with cholera end up in hospitals and many more may have been infected (Colwell and Huq, 2004). Cholera is a disease with rapid onset. Within 24 to 48 hours, the typical patient can lose up to 18 liters of fluid. If that fluid can be replenished quickly, either intravenously or through oral rehydration (using a simple mixture of bicar- bonate of soda, table salt, and sugar), recovery is fairly rapid. From years of study in Bangladesh, we have determined several factors that interact and are associated with the massive annual biennial (spring and fall) cholera epidemics, so that we can predict the onset and severity of epidemics. Our recent research focuses on the communities of Mathbaria and Bakerganj, which are located in the barrier islands region of the Ganges delta (see Figure 2-1). Mangrove-based ecosystems are abundant in copepods. Thus, the Vibrio population is also abundant, and during the zooplankton/Vibrio bloom, cholera results from drinking untreated water. In Bakerganj and Mathbaria, copepods comprise the majority of zooplankton species. We now have evidence that the severity of a given local cholera epidemic can be determined by copepod population dynamics, with intense epidemics occurring during times of abundance of those copepod species to which epidemic strains of V. cholera preferentially attach. We are currently conducting a seasonal study of zooplankton species in an attempt to determine which species carry V. cholera and to identify factors that influence population size; we will use this information, with other environmental data, to build a predictive capacity for cholera epidemics. We are also using our knowledge of cholera epidemiology to help the people of Bangladesh to avoid contracting cholera. In one study, for example, we found that by simply educating women to filter drinking water through several layers of sari cloth, we were able to reduce cholera incidence by 50 percent. This result supported our hypothesis that plankton and particulatesâto which the bacteria are attractedâtransmit cholera and when removed by simple filtration, the inci- dence of the disease is significantly reduced. Predictive Models of Cholera Currently, the spring bloom of phytoplankton in the Bay of Bengal can be measured by satellite sensors that measure chlorophyll intensity and, therefore, the phytoplankton population. Phytoplankton blooms are followed by zooplank- ton blooms, but the latter cannot yet be measured directly by satellite sensors. However, the zooplankton peak can be inferred using a series of calculations from measurements of the phytoplankton populations that precede the zooplankton
114 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS population peak. This information taken together with salinity, temperature, and other environmental factors, provides a more complete picture. We have also gathered ground truth data over the past 10 years in the Bak- erganj area, including conductivity of the water, presence of inorganic nutrients, temperature, and salinity. With these data, we are able to improve our prediction of the timing and, possibly, the severity of cholera epidemics. In our original work, we were able to use satellite imagery to measure sea surface temperature and sea surface height in the Bay of Bengal. As shown in Figure 2-2, the correlation of chlorophyll and temperature data, measured by sat- ellite sensors, provides a predictive capacity for conditions conducive to cholera outbreaks. We are currently working on a predictive model that takes into account ocean currents to monitor the movement of plankton into the Bay of Bengal estu- aries from the southern tip of India. This could provide as much as a 3-month warning prior to an impending cholera outbreak. In Latin America, the 1991-1992 El NiÃ±o event corresponded with a cholera epidemic that was initially attributed to the dumping of ballast water by a ship in the harbor of Lima, Peru (Gil et al., 2004). We were able to disprove this hypoth- esis by demonstrating that cholera outbreaks had occurred in three different cities along the coast of Peru, starting before the peak of the 1991-1992 El NiÃ±o event. The epidemic more likely resulted from the effect of increased sea surface tem- peratures on existing plankton and V. cholerae populations. Our most sophisticated predictive model for cholera incorporates chloro- phyll, sea surface height, temperature, and extensive ground truth data. Within a few years, the National Oceanic and Atmospheric Administration (NOAA) will launch a satellite that may provide salinity data. We are also refining our model, based on the 40 years of data accumulated on cholera in Bangladesh and in India, which we are presently analyzing. Nevertheless, with the analyses we have performed to dateâsea surface temperature and sea surface height from satellite sensors; measurements of chlorophyll intensity (corrected for the time lag from chlorophyll-phytoplankton bloom to the zooplankton bloom that feeds on the phytoplankton); and measurements of vibrio dispersion in the waterâwe are able to determine significant correlations and, thus, a foundation from which to predict cholera epidemics. Conclusion Climate change is likely to increase the burden of cholera in Bangladesh, but even greater suffering will occur if sea levels rise to predicted levels, displacing millions of people. However, our interdisciplinary, international (as demonstrated by our large number of collaborators from many countries), and biocomplex- ity approach to studying cholera extends well beyond Bangladesh and even beyond the disease itself. By gaining an understanding of the complex interac- tions between infectious disease, ecology, and the physical environment, we can
FIGURE 2-2â Environmental parameters (top) and predicted versus actual cholera incidence rate (bottom). SOURCE: Printed with permission from John Calkins, ESRI User Conference (2004). 115
116 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS develop predictive models of infectious diseases that in turn will allow us to develop a preemptive medicine: that is, to mitigate the impact of infectious dis- ease, if not to prevent it by having an early warning system to initiate appropriate and responsive public health measures. EXTREME WEATHER AND EPIDEMICS: RIFT VALLEY FEVER AND CHIKUNGUNYA FEVER Jean-Paul Chretien, M.D., Ph.D. Department of Defense Assaf Anyamba, Ph.D. NASA Goddard Space Flight Center Jennifer Small, M.A.4 NASA Goddard Space Flight Center Compton J. Tucker, Ph.D.4 NASA Goddard Space Flight Center Seth C. Britch, Ph.D. U.S. Department of Agriculture Kenneth J. Linthicum, Ph.D.5 U.S. Department of Agriculture As Earthâs climate changes, the frequency and intensity of heat waves, droughts, floods, and other extreme weather events are expected to increase over large regions (IPCC, 2007b). Trends already are apparent, with regions affected by drought and the frequency of heavy precipitation that leads to flooding increas- ing since the 1950s (IPCC, 2007a). Besides obvious, direct effects on human health, extreme events can facilitate infectious disease epidemicsâfor example, through effects on disease vector ecology, infrastructure, and human behavior. Satellite observations and modeling allow prediction of some extreme weather events and consequent infectious disease activity. In this paper, we use â The views expressed in this paper are the private views of the authors and are not to be construed as official or representing the true views of the Department of Defense. â Coordinator, Overseas Laboratories, Global Emerging Infections Surveillance & Response Sys- tem, 2900 Linden Lane, Silver Spring, MD 20910; Phone: 301-319-9418; Fax: 301-319-9213; E-mail: Jean-Paul.Chretien@us.army.mil. â Biospheric Sciences Branch, Greenbelt, MD. â Agricultural Research Service, Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, FL.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 117 satellite and epidemiological data to examine connections between the El NiÃ±o/ Southern Oscillation (ENSO) phenomenon and two recent mosquito-borne epi- demics in Africa: Rift Valley fever (RVF) and chikungunya fever, which followed heavy rains and drought, respectively. These case studies suggest considerations in developing early warning systems for extreme weather-associated epidemics. El NiÃ±o/Southern Oscillation and Rift Valley Fever Prediction The ENSO is an irregular, but natural, feature of the global climate system. It results from interactions between the oceans and the atmosphere across the Indo-Pacific region and affects the weather around the world. In the warm, or El NiÃ±o, phase of the cycle, sea surface temperatures are warmer than usual in the eastern-central equatorial Pacific Ocean. El NiÃ±o sometimes is followed by a cool, or La NiÃ±a, phase with colder-than-usual temperatures in the eastern-central equatorial Pacific. The warm and cool phases cycle over irregular intervals of several years but have characteristic effects on precipitation and temperature throughout much of the tropics. In areas where it influences climate, El NiÃ±o is associated with increased risk of some infectious diseases (Kovats et al., 2003). For example, in East Africa, El NiÃ±o is associated with flooding and RVF activity (Linthicum et al., 1999)âÂepizootics among economically important livestock, with humans infected incidentally by the mosquito vectors or by handling or consuming infected animal products. Out- breaks begin near natural depressions (âdambosâ) that harbor Aedes mosquito eggs infected directly by the parent during development. The eggs hatch with dambo flooding, producing an initial wave of RVF vectors; other species that transmit the virus emerge over subsequent weeks (Linthicum et al., 1984) and propagate the outbreak. The largest recorded RVF outbreak, in 1997-1998, Âcoincided with a strong El NiÃ±o. There were an estimated 89,000 human infections and hundreds of deaths in northeastern Kenya and southern Somalia (CDC, 1998). Following the 1997-1998 outbreak, scientists at the U.S. National Aero- nautics and Space Administration Goddard Space Flight Center (NASA-GSFC) and the Department of Defense Global Emerging Infections Surveillance and Response System (DOD-GEIS) initiated a partnership to forecast conditions favorable for RVF activity in Africa by monitoring ENSO and other climatic phenomena. The program uses satellite data from ongoing NASA and NOAA climate and environmental observation programs to provide predictions of areas at elevated RVF risk. The primary data sets are sea surface temperature (SST), rainfall, outgoing longwave radiation (OLR; which is correlated with cloud cover and rainfall), and Normalized Difference Vegetation Index (NDVI; a key measure for identifying risk areas). NDVI is correlated with rainfall but integrates effects of other climatic parameters, responds most to sustained rather than intermittent rains, and is available globally since 1981, while ground-based rain gauge cover- age is limited in Africa.
118 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Updated forecasts are available monthly, or more frequently if conditions warrant, on the DOD-GEIS public website. Forecasts and alerts also are com- municated to public health agencies that can act on them to enhance surveillance or community preparedness in at-risk areas. Important partners in responding to forecasts and alerts include the World Health Organization (WHO), Food and Agriculture Organization of the United Nations (FAO), the U.S. Centers for Disease Control and Preventionâs (CDCâs) International Emerging Infections Program in Kenya, and two members of the DOD-GEIS network: the U.S. Army Medical Research Unit-Kenya (USAMRU-K) in Nairobi and the U.S. Naval Medical Research Unit-3 (NAMRU-3) in Cairo. Rift Valley Fever Outbreaks in East Africa, 2006-2007 In September 2006, the NASA-GSFC/DOD-GEIS monitoring program iden- tified indications of an impending El NiÃ±o episode, with SSTs anomalously elevated in the central-eastern Pacific Ocean (+2ÂºC) and the western Indian Ocean (+1ÂºC) (see Figure 2-3). These conditions enhanced precipitation over these areas and the Horn of Africa through November (see Figure 2-4). Rainfall increased through December, with vegetation response (see Figure 2-5A) and conditions favorable for RVF activity in large areas of northeastern Kenya and nearby areas in Somalia and Ethiopia, as well as in southern Kenya and northern Tanzania (see Figure 2-5B). The NASA-GSFC/DOD-GEIS program released a series of epidemic warnings based on these observations. In September 2006, it issued a global, regional-scale forecast covering late 2006-early 2007 for possible El NiÃ±o-linked outbreaks, including RVF in East Africa, to the DOD-GEIS network (these fore- casts were published online in the International Journal of Health Geographics, an open access journal, in December; Anyamba et al., 2006). As rainfall increased in the Horn of Africa, the FAO Emergency Prevention System for Transboundary Animal Diseases issued an RVF alert for the Horn in November, identifying areas flagged as conducive to RVF activity (FAO, 2006). NASA-GSFC/DOD-GEIS also communicated with the WHO, which transmitted alerts to the countries at risk for RVF activity and called for enhanced surveillance and community awareness. USAMRU-K, in coordination with Kenya Medical Research Institute (KEMRI) and CDCâs International Emerging Infections Program (IEIP), deployed a field team in early December to assess high-risk areas in the Garissa district of northeastern Kenya (which was experiencing severe flooding). USAMRU-K tested mosquitoes collected by the team in Garissa and from established collec- tion sites in other areas (see Figure 2-6), identifying RVF virus-infected mos- quitoes from Garissa. The field team also investigated local reports of possible â See http://www.geis.fhp.osd.mil.
FIGURE 2-3â Global SST anomalies, September 2006. 2-3 color 119 Broadside
120 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS 20 15 10 5 0 -5 -10 25 30 35 40 45 50 55 -15 Rainfall Anomaly, mm -400 -300 -200 -150 -100 -50 -25 25 50 100 150 200 300 400 FIGURE 2-4â Seasonal rainfall anomalies in the Horn of Africa, September 2006ââ January 2007. animal RVF cases and traveled with Ministry of Health staff to hospitals that recently had admitted patients with suspected RVF, obtaining specimens for test- ing at KEMRI. On December 21, KEMRI confirmed RVF virus infection in specimens taken from several patients in the Garissa district (WHO, 2007a). The Kenya Ministry
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 121 20 20 15 15 10 10 5 5 0 0 -5 -5 -10 -10 30 35 40 45 50 55 25 30 35 40 45 50 55 -15 -15 A Anomaly (%) B RVF risk areas RVF potential epizootic areas -100 -80 -60 -40 -20 0 20 40 60 80 100 FIGURE 2-5 NDVI anomalies (A) and RVF calculated risk (B) in the Horn of Africa, January 2007. In (B), green identiï¬es areas included in the NDVI-based RVF risk assess- ment (based on permissive permanent environmental features) and red indicates areas currently at elevated risk, based on persistence of positive NDVI anomalies over at least 3 months. of Health initiated a response with international partners, including WHO, CDC, USAMRU-K, NAMRU-3, and the U.S. Department of Agriculture. An intensive social mobilization campaign began in northeastern Kenya in late December, along with a locally enforced ban on animal slaughtering over most of Eastern and North Eastern Provinces (animal vaccination began in January, but by then the epidemic was waning). NASA-GSFC/DOD-GEIS provided frequent, high- spatial-resolution risk assessment updates to facilitate targeted surveillance dur- ing the epidemic response. Between November 30, 2006, retrospectively identiï¬ed as the date of onset for the index case, and March 9, 2007, when the last case was identiï¬ed, 684 cases with 155 deaths were reported in Kenya. North Eastern province, which includes the Garissa district, reported the most cases of affected provinces (N = 333). Smaller RVF epidemics in Somalia and Tanzania followed the Kenya outbreaks: in Somalia, 114 cases with 51 deaths were reported between late December 2006 and February 2007; in Tanzania, 264 cases with 109 deaths were reported between mid-January and early May.
122 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS FIGURE 2-6â USAMRU-K mosquito collection sites (blue dots) and RVF risk assess- ment, December 2006. 2-6 color Chikungunya Fever Outbreaks in Kenya and Other Regions, 2004-2008 In July 2004, while East Africa experienced a severe drought, a public hos- pital in Lamu, a coastal island city of Kenya, noted a sharp increase in cases of acute febrile illness. Many patients reported joint pain and had negative malaria blood smears (Bedno et al., 2006). The Ministry of Health launched an outbreak
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 123 investigation, which was supported by USAMRU-K and the CDCâs IEIP. Labo- ratory testing of outbreak specimens identified chikungunya virus as the cause. After the outbreak, a population-based serological study led by the Kenya Field Epidemiology Training Program estimated that 13,500 people, or 75 percent of the Lamu population, were infected (Sergon et al., 2008). In November, a chi- kungunya outbreak was reported in Mombasa, around 200 miles south of Lamu on the Kenya coast. Though rarely fatal, chikungunya virus infection may cause prolonged and debilitating joint pain. The disease is endemic throughout much of tropical Africa, maintained by transmission cycles involving forest-dwelling Aedes mosquitoes and wild primates in which humans are infected incidentally. Urban Aedes aegypti and Aedes albopictus cause epidemics in tropical Asia without nonhuman hosts. The vectors in urban Lamu and Mombasa were thought to be peridomestic Aedes aegypti, which were found in unprotected domestic water sources that were not changed frequently because of water shortages during the drought. The outbreaks marked the first confirmation of chikungunya fever transmission in coastal Kenya. Retrospective analysis of climate data preceding the Lamu outbreak (assumed to have begun in June 2004) showed anomalously warm, dry conditions over much of East Africa, but especially coastal Kenya, during May 2004 (Chretien et al., 2007). NDVI anomalies in Lamu were the most negative in the available record (1998-2003), reflecting substantially reduced rainfall. When the outbreaks occurred in Lamu and Mombasa, each city had experienced a cumulative rainfall deficit of approximately 100 mm compared to the average (see Figure 2-7). The warm, dry conditions may have enabled the epidemic in two ways: unsafe domestic water storage practices, along with infrequent changes of water stores because of the drought, may have increased peridomestic Aedes vector abundance; and the warm, dry conditions may have enhanced Aedes vectorial capacity by decreasing the extrinsic incubation period (Watts et al., 1987). Following the Kenya chikungunya fever outbreaks, the epidemics spread to other areas with susceptible human populations and competent vectors: to western Indian Ocean islands, including Reunion, where viral mutation may have facilitated adaptation to the highly efficient Aedes albopictus vector (Tsetsarkin et al., 2007) and more than 200,000 people likely were infected (WHO, 2006), and to India, which reported well over 1 million cases (Mavalankar et al., 2007). Also, for the first time ever, chikungunya fever reached Europe. In a north- eastern Italian province, public health authorities identified 205 cases during July-September 2007 (Rezza et al., 2007). The presumed index case devel- oped symptoms after visiting relatives in an affected area of India. Local Aedes Â lbopictus mosquitoes, an invasive species introduced into Italy around 1990 (tire a importation is suspected as the mechanism), then propagated the epidemic. While the role of climatic conditions in the Italian outbreak is unclear, much of southern Europe had experienced an anomalously warm, dry summer (see Figure 2-8)
124 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Lamu Mombasa 800 800 700 700 Cumulative Rainfall (mm): May - April Cumulative Rainfall (mm): May - April 600 600 500 500 400 400 300 300 200 200 100 100 0 0 0 04 05 04 05 Year Year Cumulative Monthly Rainfall Cumulative Longterm Mean Monthly Rainfall Approximate Start of CHIK Activity FIGURE 2-7â Cumulative monthly rainfall (dotted line) and long-term mean cumulative monthly rainfall (solid line) in Lamu and Mombasa. Vertical dashed line indicates approxi- mate starting dates for the outbreaks (Lamu, June 2004; Mombasa, November 2004). that, along with historically poor vector control, may have contributed to the Figure 2-7 abundance of mosquitoes in the affected area at the time of the outbreak (reported anecdotally; Rezza et al., 2007). Developing Early Warning Systems for Extreme Weather-Linked Infections In both the RVF and the chikungunya fever examples, climate appears to have interacted with other factors to facilitate the outbreaks (see Table 2-2), con- sistent with the âConvergence Modelâ of infectious disease emergence proposed by the Institute of Medicineâs (IOMâs) Committee on Microbial Threats to Health in the Twenty-First Century (Figure 2-9; IOM, 2003). For example, besides flood- ing of mosquito habitats, animal sacrificing and preparation practices may have
-15 0 15 30 45 30 W/m2 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 FIGURE 2-8â Outgoing longwave radiation (OLR) anomalies, July 2007, for the Mediterranean region. Positive anomalies (> +10 W/m2) are indicative of severe drought conditions that persisted during the summer color across the region. Such severe drought conditions also 2-8 of 2007 prevailed during the Chikungunya outbreak in coastal East Africa and the Indian Ocean island during the 2004-2005 period. 125
126 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS TABLE 2-2â Factors in Emergence and Spread of Rift Valley Fever and Chikungunya Fever Rift Valley Fever Chikungunya Fever Climatic factors â¢ Flooding â¢ Warm, dry conditions Biological factors â¢ Broad host and vector â¢ Genetic adaptation to Aedes species range albopictus â¢ Abundant livestock hosts â¢ Association of Aedes albopictus and Aedes aegypti to humans Physical environment â¢ Dambos, other ground â¢ Vector breeding sites factors pools Social, political, and â¢ Livestock trade â¢ Travel economic factors â¢ Herder and religious â¢ Delayed notification and control practices â¢ Previous introduction of Aedes albopictus to Indian Ocean islands and Italy by trade SOURCE: Adapted from Chretien and Linthicum (2007), IOM (2003), and Peters and Linthicum (1994). contributed to the RVF epidemic in East Africa in 2006. In coastal Kenya in 2004, the availability of vector breeding sites (i.e., unprotected domestic water stores) appears to have facilitated the emergence of chikungunya fever. In developing early warning systems for outbreaks linked to extreme weather, consideration of the nonclimatic facilitating factors may enable more precise identification of populations at risk, with better targeting of risk communication. The RVF and chikungunya fever outbreaks also suggest the need for infec- tious disease early warning systems to integrate with other natural disaster pre- diction and response programs. In both of these epidemics, climatic conditions facilitating disease emergence and transmission had other public health effects as well. Flooding in the Horn of Africa during late 2006-early 2007 affected more than 1 million people (WHO, 2007b), destroying homes, livestock, and crops; displacing families; causing hygiene breakdown and water-borne disease epidemics; and obstructing delivery of aid (Save the Children, 2007). Drought in Kenya during 2004 contributed to massive crop failure and food shortages. Coastal areas (where the chikungunya fever epidemics occurred) were particu- larly affected, since rainfall was well below normal during 2003 and the areas lacked community-based mechanisms for emergency intervention because they had not recently experienced severe drought (UN, 2004). There are few operational early warning systems for climate-linked epidem- ics (WHO, 2004). But there is potential for developing such systemsâWHO
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 127 P HYSICAL E NVIRONMENTAL G ENETIC AND BIOLOGICAL F ACTORS F ACTORS Microbe Human S OCIAL, E COLOGICAL FACTORS P OLITICAL AND ECONOMIC FACTORS FIGURE 2-9â The Convergence Model. SOURCE: IOM (2003). has assessed climate-infectious disease links and recommended development of climate-based predictive models for cholera, malaria, and several other infec- tious diseases (WHO, 2004); and many countries maintain or are developing early warning systems for natural hazards. Citing the Indian Ocean tsunami of SA-4 December 26, 2004, as a âwake-up callâ about the role that early warning systems could play in reducing the human and physical impacts of natural hazards, United Nations (UN) Secretary General Kofi Annan called for the development of a global early warning system for all natural hazards (UN, 2006). The UN Platform for the Promotion of Early Warning, initiated in 2004, is leading early warning â See http://www.unisdr.org/ppew.
128 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS actors toward this goal. Integration of epidemic prediction with such related efforts could speed the development of epidemic prediction systems and facilitate more comprehensive risk communication to communities facing extreme weather events and other natural hazards. PLAGUE AND CLIMATE Nils Chr. Stenseth, Dr.philos. University of Oslo Plague, caused by the bacterium Yersinia pestis, is found on all continents except Antarctica and Australia (Figure 2-10). The plague bacillus causes a rap- idly progressing, serious illness that, in its bubonic form, is likely to lead to death by septicemia (40 to 70 percent mortality). Without prompt antibiotic treatment, pneumonic and bubonic plagues are nearly always fatal. For these reasons the plague bacterium Y. pestis is considered one of the most pathogenic bacteria for humans (Gage and Kosoy, 2005). Throughout history, it has played a dramatic role, and it continues to be a threat worldwide (Figure 2-10), particularly in Africa (Figure 2-11). Plague is currently recognized as a reemerging disease increasing in fre- quency throughout the world (Duplantier et al., 2005; Schrag and Wiener, 1995; Stenseth et al., 2008; WHO, 2003, 2005) as well as being a potential agent of bioterrorism (Inglesby et al., 2000; Koirala, 2006). Throughout its geographic dis- tribution, its main reservoir is composed of a variety of wild (and in some cases commensal) rodents and the bacterium is transmitted between individual hosts primarily by flea vectors (see âThe (Full) Plague Eco-Epidemiological Systemâ below). Understanding what determines the dynamics of plague necessitates an understanding of the dynamic rodent-flea-bacterium system in the wild. The dynamics of the reservoir species are known to be profoundly influ- enced by climate variation (see Stenseth, 1999; Stenseth et al., 2002, 2006). Here, I summarize our findings from the analysis of long-term data monitoring in Kazakhstan. I both address what might happen should the climate change as expected (IPCC, 2007) and assess whether there has been a climate component underpinning the past plague pandemics. The Three Big Historical Plague Pandemics Plague has given rise to at least three major pandemics. The first (âthe J Â ustinian plagueâ) spread around the Mediterranean Sea in the sixth century A.D., the second (âthe Black Deathâ) started in Europe in the fourteenth century and â Founding Chair of the Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, PO Box 1066 Blindern, N-0316 Oslo, Norway.
FIGURE 2-10â The global distribution of plague. The map shows countries with a known presence of plague in wild reservoir species (black) (after WHO, 2005). For the United States, only the mainland below 50ÂºN is shown. 2-10 SOURCE: Stenseth et al. (2008). Broadside Bitmapped 129
130 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS A 45 Asia Number of Countries Reporting Plague Cases 40 Africa 35 America 30 TOTAL 25 20 15 10 5 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Time B 6000 Asia 2-11A color Africa 5000 America Human Cases 4000 TOTAL 3000 2000 1000 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Time FIGURE 2-11â The global distribution of plague: (A) cumulative number of countries that 2-11 B color reported Countries reporting plague from continent (1954-1998)--in distribution of plague to WHO per continent, per 1954-1998; (B) the temporal caption? plague cases by continent, from 1954-1998, also from WHO. (Panel B is corrected relative to a similar one given in Stenseth et al. (2008): for 1997 and 1998 the numbers have, in dialogue with WHO, been corrected for Madagascar.) SOURCE: Modified from Stenseth et al. (2008). recurred intermittently for more than 300 years, and the third started in China during the middle of the nineteenth century and spread throughout the world. Purportedly, each pandemic was caused by a different biovar of Yersinia pestis, respectively Antiqua (still found in Africa and central Asia), Medievalis (currently limited to central Asia), and Orientalis (nearly worldwide; Guiyoule et al., 1994; Twigg, 1984; see Figure 2-12). Plague on all continents (1954-1998) The Black Death decimated medieval Europe, and as a result, had a major impact on the continentâs socioeconomic development, culture, art, religion, and
FIGURE 2-12â Routes followed by the three plague pandemic waves (labeled 1, 2, and 3). Circled numbers indicated the regions thought to be the origin of each of the three pandemics: the Justinian plague (541 A.D. to 767 A.D.); the Black Death and subsequent epidemics from 1346 to the early nineteenth century; and the Third Pandemic, in the mid-nineteenth century in the Yunnan region of China, started in 1855. SOURCE: Achtman et al. (1999). 131 Figure 2-12 (landscape) bitmapped
132 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS politics (Twigg, 1984; Ziegler, 1969). Although some have questioned whether the Black Death (as well as the first pandemics) was caused by Y. pestis (Cohn, 2002; Scott and Duncan, 2001), it seems settled today (Stenseth et al., 2008). It is generally accepted that the epidemiology of the Black Death plague, as reflected in historical records, does not always match the âclassicalâ rat-flea-human plague cycle, but the reported medical symptoms were very similar during each historical pandemic. It should be appreciated, however, that âclassicalâ plague epidemiology is only one of several possibilities to explain the Black Death and may not even be the most typical of the different plague ecology systems (Drancourt et al., 2006). The discovery of Y. pestis genetic material in those who died from the Black Death and are buried in medieval graves (Raoult and Aboudharam, 2000) further supports the view that Y. pestis was the causative agent of the Black Death. The (Full) Plague Eco-Epidemiological System Soon after Yersinâs discovery of the plague bacillus (Yersin, 1894), it became clear that urban outbreaks were linked to transmission among commensal rats and their fleas. In this classic urban plague scenario, infected rats (transported, for example, by ships) arrive in a new city and transmit the infection to local house rats and their fleas, which then serve as sources of human infection. Occasionally, humans develop a pneumonic form of plague, which is then directly transmitted from human to human through respiratory droplets. The epidemiology of plague, however, is much more complicated than this urban plague scenario suggests, involving several other pathways of transmission. This complicated epidemiology necessitates reconsidering plague ecology within its full ecological web (Figure 2-13). Maintenance of plague foci depends on a whole suite of rodent hosts and their associated fleas. Under favorable conditions, the plague bacillus might survive in the environment, essentially in rodent burrows (Baltazard et al., 1963). When an infected flea happens to feed on a commensal rodent, the cycle continues in the latter. As commensal rodents die, their fleas are forced to move to alternate hosts (e.g., humans). If humans develop pneumonic plague, the infection may trans- mit from person to person through exposures to respiratory droplets spread by coughing. Humans may also become infected through handling infected animals (or meat), including rodents, camels, or cats. Cats may also develop pneumonic plague, passing their infection to their owners through coughing. Finally, there is evidence that the human flea, Pulex irritans, can be involved in human-to-human transmission (Blanc, 1956; Laudisoit et al., 2007). Mammalian predators, birds of prey, and other birds that use rodent burrows for nesting may move over larger areas than the rodents themselves, spreading the infection over longer distances. Infected commensal rats or humans may also travel over long distances. Because of its widespread occurrence in wildlife rodent reservoir species one must recognize that plague cannot be eradicated. There is a critical need,
FIGURE 2-13â Possible transmission pathways for the plague bacterium, Yersinia pestis. Thick arrows indicate pathways to people. SOURCE: Adapted from Chamberlain (2004) and printed with permission from Neal R. Chamberlain, Ph.D., A.T. Still University of Health Sciences. 133 Figure 2-13 most type is bitmapped
134 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS therefore, to understand how human risks are affected by the dynamics of these reservoirs and how people interact with them. The capacity of the plague bacillus to form permanent foci under highly diverse ecological conditions attests to its extraordinary adaptability. During its emergence in central Asia, Y. pestis accumulated copies of insertion sequences rendering its genome highly plastic (Parkhill et al., 2001). The capacity to undergo genomic rearrangements may thus be an efficient means for the plague bacillus to adapt to new ecological niches. Y. pestis was recently shown to be able to acquire antibiotic resistance plasmids under natural conditions (Galimand et al., 1997; Guiyoule et al., 2001), probably during its transit in the flea midgut (Hinnebusch et al., 2002). Obviously, the emergence and spread of multidrug-resistant strains of Y. pestis would represent a major threat to human health. Although the number of human cases of plague is relatively low, it would be a mistake to overlook its threat to humanity because of the diseaseâs inherent communicability, rapid spread, rapid clinical course, and high mortality if left untreated. A plague outbreak may also cause widespread panic, as occurred in 1994, when a relatively small outbreak, with 50 deaths, was reported in the city of Surat, India (Mudur, 1995), which led to a nationwide collapse in tourism and trade, with an estimated cost of $600 million U.S. dollars (Fritz et al., 1996). Studying the Plague Dynamics of Central Asia: The Effect of Climate Variation Together with colleagues, I have been studying the dynamics of the plague ecological system based on long-term monitoring data from the former Soviet Union (specifically from Kazakhstan), some of which have been published (Davis et al., 2004, 2007; Frigessi et al., 2005; Kausrud et al., 2007; Park et al., 2007; Samia et al., 2007; Stenseth et al., 2006) but much more is to come, including information on human plague cases. Currently, we are expanding our geographic area of interest to include China, India, Madagascar, and the United States. Our core set of monitoring data comes from southeastern Kazakhstan (74-78Â°E and 44-47Â°N; see Figure 2-14). Each spring and autumn, between 1949 and 1995, a proportion of inhabited burrows and site-count observations were done at different locations within the PreBalkhash area (see Figure 2-14; for details, see Stenseth et al., 2006). For monitoring purposes, the area was divided into 10 Ã 10 km2 sectors. Four sectors constitute a 20 Ã 20 km2 primary square (PSQ), and four PSQs constitute a large square (LSQ; Figure 2-14). At a given site, the great gerbil population densities were estimated at most twice per year. On approximately 85 percent of these occasions, up to 8,576 gerbils (median = 604) were trapped per LSQ, based on independent plague prevalence data (see Stenseth et al., 2006) and season, and tested for Y. pestis infection. The LSQs chosen had the longest regular and continuous time-series data required by our analysis. We also have access to
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 135 FIGURE 2-14â The field data used in Stenseth et al. (2006) were collected in a natural plague focus in Kazakhstan. The data are plague prevalence in great gerbils, counts of fleas collected from trapped gerbils, and meteorological observations. Left Upper: Kazakhstan Figure 2-14 on a map of Central Asia with the PreBalkhash focus (between 74 and 78Â°E and 44 and color, bitpmapped 47Â°N) marked as a square. The historic climate (tree-ring)from pdf alternate version taken measurement sites are circles marked K (Karakorum) and T (Tien Shan). These sites are located approximately 1,000 and 600 km from the research area, respectively. Lower Right: The LSQ in the PreBalkhash focus from which we have prevalence. The four LSQs (40 Ã 40 km) circled in red, namely LSQs 78, 83, 91, and 105, represent key sites where collection of samples for testing the presence of plague was more regular and continuous. The Bakanas meteorological station is located in LSQ 117, marked by a red triangle. Upper Right: The time-series plots of the observed prevalence per LSQ. Open and filled circles denote the observed prevalence during the spring and fall, respectively. The time series of the prevalence fitted by using the model defined by the model is shown in red. Using the same model but without any climatic covariates gives the time series shown in gray. Note that owing to the presence of missing values in some covariates (occupancy) and prevalence data, the curves of the fitted values are discontinuous. The fitted values from the model provide a closer fit and reproduce the peaks in prevalence far better than the model without the climatic variables. Lower Left: Time-series plots of the climate variables, spring rainfall, spring temperature, and summer rainfall (from left to right). SOURCE: Stenseth et al. (2006).
136 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS plague prevalence data: gerbils caught were tested for plague through isolation of Y. pestis from blood, spleen, or liver smears. Spring climatic variables used were the average monthly temperature dur- ing the spring (i.e., March and April) and the log average of the spring rainfall. The fall climatic variable used is the log average of summer rainfall over June, July, and August. Incorporating the climatic effects in the model resulted in fitted values that track the peak occurrences in prevalence more closely than the model without the climatic variables. Climate variability over the past millennium was estimated by using a large data set of 203 Juniperus turkestanica tree-ring width series to reconstruct tem- perature variations in the Tien Shan Mountains (Kirghizia) (Esper et al., 2003) and a total of 40 stable oxygen isotope (Î´18O) series to reconstruct precipitation variations in the Karakorum Mountains (Pakistan) (Treydte et al., 2006). Climatic variations at these sites are found to be correlated with those in the study area. We also used the NDVI (Hall et al., 2005; Los et al., 2000; see also Pettorelli et al., 2005), which is based on the difference between near-infrared and visible light reflected from the ground, thereby giving an index of light absorbed by chlorophyll on the ground, an index we also extended through proxy data back in time (see Kausrud et al., 2007). The following discussion summarizes our findings to date. Davis et al. (2004) demonstrated that plague within an area invades, fades out, and reinvades in response to fluctuations in the abundance of its main reservoir host, the great gerbil. Broadly speaking, they found that infection spreads and persists when total abundance is above a single threshold value and fades out when it is below (see Figure 2-15). Stenseth et al. (2006) reported that a 1Â°C increase in spring temperatures is predicted to lead to a >50 percent increase in prevalence (see also Samia et al., 2007). Changes in spring temperature were found to be the most important environmental variable determining the prevalence level, leading to the follow- ing scenario: Warmer spring conditions result in an elevated vector-host ratio, which leads to a higher prevalence level in the gerbil host population. Moreover, the climatic conditions that support increased prevalence among gerbils, given unchanged gerbil abundance, also favor increased gerbil abundance (see Kausrud et al., 2007), implying that the threshold density (as found by Davis et al., 2004) condition for plague will be reached more often, thereby increasing the frequency with which plague can occur. Kausrud et al. (2007), focusing on rodent-host dynamics, drew the following five main conclusions from their analyses: 1. Density fluctuations of the great gerbil, the main host, are highly cor- related over large areas, suggesting that climate may be a synchronizing agent. This is probably an important factor causing large-scale plague epizootics in the region.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 137 1.0 Bakanas Plain 0.8 Akdala Plain probability that plague will be detected Plague occurrence 0.6 0.4 0.2 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Past abundance ( 0.59 occupancyt-1 + 0.87 occupancyt-2 ) FIGURE 2-15â Relationship between the likelihood of detecting plague (solid line) in gerbils and past burrow occupancy rates together with data on presence or absence of plague at two sites: Bakanas plain (open circles) and Akdala plain (filled circles); see Davis et al. (2004) for details. The likelihood of detecting Y. pestis is 0 below a threshold value of 0.476 (95 percent confidence interval: 0.355, 0.572) but rises rapidly once the Figure 2-15 threshold is attained and continues to increase for even higher values. The seasonal data on abundance and presence of infection are pooled such that presence in a particular year means the disease was detected in either spring or autumn (or both seasons) of that year. Occupancy data represent averages of spring and autumn estimates. SOURCE: Reprinted from Davis et al. (2004) with permission from AAAS. 2. Great gerbil population densities at large spatial scales can be well pre- dicted 6 to 12 months in advance when combining spatial environmental effects and intrinsic dynamics. This insight is certainly important for predicting plague dynamics. 3. While great gerbil population growth rates exhibit greater variability in areas with low April NDVI index, average population density is not strongly correlated to average vegetation productivity. This suggests that the gerbils will be capable of maintaining population densities where plague can persist over most of their range even if, as predicted, the climate in central Asia becomes increasingly arid.
138 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS 4. While the presence of plague infection in an area is associated with popu- lation decrease over the following months, plague seems unlikely to be the main driving force behind great gerbil density fluctuations. 5. The magnitude of plague epizootics associated with the great gerbil may be expected to increase under predicted effects of ongoing climate change, a confirmation of the conclusion previously drawn by Stenseth et al. (2006). Altogether, the model reported by Stenseth et al. (2006) suggests that warmer springs (and wetter summers) can trigger a cascading effect on the occurrence and level of plague prevalence, in years with above-threshold great gerbil abundance during the fall 2 calendar-years earlier and in a region that is itself dry and con- tinental (hot summers, cold winters; see IPCC, 2007). Our analyses, moreover, favor the suggestion that enhanced flea survival and reproduction are critical to this effect. Given the multiple routes of plague transmission (flea-borne, direct via several pathways, transfer from other reservoirs), climatic influences on other epidemiological processes cannot be precluded. More generally, it is widely accepted that the distribution and dynamics of vector-borne infections are particu- larly sensitive to climatic conditions, by virtue of the sensitivity of the (arthropod) vectors themselves to variations in temperature, humidity, and often, quantities of standing water used as breeding sites. The model reported by Stenseth et al. (2006) may also shed light on the emergence of the Black Death and the plagueâs Third Pandemic, thought to have spread from an outbreak âcore regionâ in central Asia. Analyses of tree-ring proxy climate data demonstrated that conditions during the period of the Black Death (1280-1350) were both warmer and increasingly wet. The same was true during the origin of the Third Pandemic (1855-1870), when the climate was wetter and underwent an increasingly warm trend. Our analyses are thus in agreement with the hypothesis that the medieval Black Death and the mid-nineteenth-century plague pandemic may have been triggered by favorable climatic conditions in central Asia. Figure 2-16 summarizes the link between climate and the two last plague pandemics. Such climatic conditions have recently become more common (IPCC, 2007), and whereas regional scenarios suggest a decrease in annual precipitation with increasing variance, mean spring temperatures are predicted to continue increas- ing (Huntington, 2006). Indeed, during the period from the 1940s, plague preva- lence has been high in its host-reservoir in Kazakhstan (see Stenseth et al., 2006). Effective surveillance and control during the Soviet period resulted in few human cases. However, recent changes in the public health systems, coupled with a period of political transition in central Asia and an increased prevalence of plague in its natural reservoir in the region, shadow a future of increased risk of human infections. In a yet-to-be-published study, Kausrud et al. (2008), using the same sur- veillance data from 1950 to 1995, together with regional climate indices, have
1949 Year FIGURE 2-16â Tree-ring data suggesting that conditions during the Black Death and the Third Pandemic were similar. The two circles high- light the start of the Black Death and the Third Pandemic; the horizontal line is inserted for the purpose of baseline reference; the vertical gray line indicates the very start of the Third Pandemic (1855); 1949 is the year for which the monitoring and intervention program started in Kazakhstan. SOURCE: Based on data in Stenseth et al. (2006). Figure 2-16, landscape 139 bitmapped, except red lines
140 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS found that climate influences plague dynamics through the rodent-host and flea- vector relationship. Simulating backwards, Kausrud et al. (2008) successfully predicted human plague patterns in Kazakhstan from 1904 to 1950. Using tree- ring data extending back in time to 1000 A.D., this model allows us to compare model predictions with historical plague epidemiology. Analysis suggests an eco-epidemiological basis for considering the Black Death epidemic as having originated in central Asia during climatically favorable conditions (for the plague system). The same model, used for prediction forward, suggests that expected cli- mate change will sustain and possibly increase plague activity in central Asia. Effect of Climate on Plague Dynamics in Other Regions of the World Based upon our work on the Kazakh data, we are now extending our inter- est to other parts of the world. Together with Zhang et al. (2007), I have been involved in some preliminary analysis of data on human plague cases from China. These show a clear effect of large-scale climate influence. Unpublished work that I have done in cooperation with a student of mine (Ben Ari et al., 2008) similarly shows that the number of human plague cases in the western United States is strongly influenced by the Pacific Decadal Oscillation (PDO) and the number of days with above-normal temperatures. In short, a warmer and wetter climate is associated with increased prevalence level of the plague bacterium in the rodent reservoir, which subsequently might lead to an increased number of human cases. These results match up nicely with the previously published cascade model by Parmenter et al. (1999) emphasizing that the climate connection works partly through the rodent-host dynamics and the flea-vector dynamics (see Figure 2-17) in the same region. Additional Reasons for Being Concerned: Bioterror As indicated in the introduction, we should not overlook the fact that plague has been weaponized throughout historyâfrom catapulting diseased corpses over city walls, to dropping infected fleas from airplanes, to refined modern aerosol formulations (Inglesby et al., 2000; Koirala, 2006). The weaponization research carried out on plague from the 1930s through the 1990s fueled biological warfare fears that may actually have stimulated research on infectious disease surveillance and response strategies. More recently, however, the fears of small-scale bioter- rorism and a desire by government authorities to more fully control all access to plague materials increase the danger of stifling basic research on plague ecol- ogy, epidemiology, and pathophysiology that is required to improve its clinical management in endemic areas. Terrorist use of an aerosol released in a confined space could result in significant mortality and widespread panic (Inglesby et al., 2000; Koirala, 2006), and no one would want the knowledge and materials for weaponizing plague to fall into the hands of non-state actors. However, the
Increased rodent Increased soil moisture and Effects of Increased Precipitation food sources available hosts February - March (Major effect) July - August (Minor effect) February - March (Minor effect) In cr al ea Cool summer iv se d an n d r (15 â 18 months after first wet winter) s io a re od ct fle pr en (Major effect) odu urv ed od ts pr u as uc re rv re tio c d iv n In al an Widespread epizootics High rodent densities Cool temperatures favor favor epizootic spread survival of infected fleas Increased human plague risks FIGURE 2-17â The modified trophic cascade model of Parmenter et al. (1999). SOURCE: Adapted from Parmenter et al. (1999) with permission from the American Journal of Tropical Medicine and Hygiene. 141 Figure 2-17 may be b&w
142 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS need for scientifically sound studies of the dynamics of infection, transmission, outbreak management, and improved surveillance and monitoring systems has never been greater. Conclusion: It Is Unwise to Neglect Plague In conclusion, it should be noted that although plague may not match the so-called big three diseases (malaria, HIV/AIDS, and tuberculosis; see Hotez et al., 2006) in numbers of human cases, it by far exceeds these diseases in pathogenicity and rapid spread under the right environmental conditions. Plague should be seen not only as a historical curiosity but as a reemerging disease of the twenty-first century. Plague should not continue to be neglected and relegated to the sidelines; it is a disease which should concern us today. Plague remains a fairly poorly understood threat that we cannot afford to ignore. Nevertheless, much progress has recently been made toward understand- ing the dynamics of the full plague eco-epidemiological system, and not the least how it responds to climate variation and change. We know that climate does affect the dynamics (and indeed the level) of plague. However, it is difficult at present to say what that effect will be. For example, in central Asia there might be higher levels of plague in the rodent reservoir populations, if current climate prognoses for the region materialize. Also, higher levels in the wildlife reservoir will automati- cally lead to a greater chance of people being infected by the plague bacillus. In other places of the world there might be lower plague levels in the Âreservoirsâwe simply do not know, but we ought to know if we are to be maximally prepared for what happens should climate change. It is certain, though, that the picture regarding plague might be much more serious than conveyed by ÂAnyamba et al. (2006). Only by knowing more about how the eco-epidemiological plague sys- tems in different parts of the world will respond to given climate scenarios can we take the necessary precautionary measures to reduce the risks associated with human infections. Indeed, knowing how climate is affecting the components of the eco-epidemiological system depicted in Figure 2-13, and subsequently how these climate drivers might change the dynamics of the system, will put us in a greatly improved position for predicting where and under what environmental conditions the risk of human plague infections might increase and where and under what con- ditions it might decrease (or remain unchanged). Much of the insight derived from studying particular plague systems will be general and applicable to other plague systemsâand indeed to other vector-borne infectious disease systems. However, since the involved host and vector species are different from one part of the world to another (indeed, the plague eco-epidemiological system is characterized by a whole suite of rodent host species and their associated fleas, differing from one place to another), studies similar to those that I have summarized for central Asia are greatly needed. Such additional studies may help us to understand which insights derived from the central-Asian studies may or may not be generalized to other places where
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 143 plague occurs. Such additional studies will further help us develop more region- specific prediction regarding what might happen should climate change in some specific way. Acknowledgments I thank Tamara Ben Ari for having read and commented on an earlier version of this paper; furthermore, I thank her and Kyrre LinnÃ© Kausrud for allowing me to summarize yet unpublished work. Over the years working on plague dynam- ics, I have benefited enormously from collaboration with several colleagues, most importantly Herwig Leirs, Hildegunn Viljugrein, Mike Begon, Kung-Sik Chan, Noelle I. Samia, Stephen Davis, Kyrre LinnÃ© Kausrud, Tamara Ben Ari, Lise Heier, Elisabeth Carniel, Mark Achtman, Kenneth L. Gage, Vladimir S. Ageyev, Nikolay L. Klassovskiy, and Sergey B. Pole. I have learned a lot from themâany misunderstandings of what they have tried to teach me is due solely to my own shortcomings. On a more administrative side, I would like to thank Dr. M. Pletschette for his stimulating encouragement, which made me start work- ing on plague in the first case. My work on plague has been generously funded over the years through the European Union Projects (ISTC K-159, STEPICA [INCO-COPERNICUS, ICA 2-CT2000-10046], as well as Marie Curie Early Stage Training grant to CEES), the Norwegian Research Council, and my own university and center. Last, but not least, I extend my thanks to the many hundreds of Kazakh plague zoologists who collected so many data over all these years. CLIMATE CHANGE AND PLANT DISEASE RISK Karen A. Garrett, Ph.D. Kansas State University Plant Disease and Ecosystem Services One of the most important effects of plant disease is its impact on crop plant productivity. Oerke et al. (1994) estimated that damage by disease and insect pests resulted in a 42 percent loss in the eight most important food and cash crops. Pimentel et al. (2000) estimated that 65 percent of U.S. crop losses, $137 billion, were due to introduced pathogens. The effects of plant disease can also be considered within the broader context of ecosystem services, defined as the benefits provided to humans by ecosystems, including services provided by plants and their pathogens (Daily, 1997). Ecosystem services include the following: (1) provisioning services, such as the more obvious provisioning of food, fiber, fuel, and also the provisioning of genetic resources; (2) supporting services, such as â Associate Professor, Department of Plant Pathology.
144 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS soil formation, nutrient cycling, and primary productivity by plants, all of which have great economic value but tend to be appreciated only when there are break- downs, such as the loss of soil during the U.S. dust bowl; (3) regulating services, such as regulation of climate, disease, and insect herbivory, and water purifica- tion; and (4) cultural services, such as opportunities for education, recreation, tourism, and inspiration. The Millennium Ecosystem Assessment10 provides an example of system evaluation based on ecosystem services. Cheatham et al. (in revision) have synthesized perspectives on plant disease and its management in the context of ecosystem services. In addition to the direct effects of disease on crop production, disease and its management by increased tillage, pesticide use, and other methods may reduce services provided by plants such as soil formation and climate and water regulation. Disease may also remove plants that provide important cultural services in addition to the range of other potential services. Some examples among the many notorious plant diseases illustrate the issues for disease management and the potential impact when diseases cannot be man- aged effectively. Chestnut blight has had one of the most definitive effects, essentially removing the once common American chestnut from the landscape of eastern North America (Anagnostakis, 2000). Potato late blight is infamous as the proximate cause of the Irish potato famine and continues as a major con- straint to potato production, making the use of pesticides a typical part of potato management in many areas (Hijmans et al., 2000). Karnal bunt of wheat offers an example of a disease that does not cause major yield loss, but has an impor- tant economic impact on regions where it is present through limits on trade with Europe and other parts of the world where the pathogen has not been detected (Rush et al., 2005). Sudden oak death has changed the structure of some western U.S. forests and threatens to impact forests throughout a much wider area (Rizzo et al., 2005). Soybean rust is a new pathogen to the United States, with the poten- tial to become established throughout much of the U.S. soybean production areas (Pivonia and Yang, 2004). Wheat stem rust was an important pathogen in the United States in the 1900s, motivating the removal of barberry plants that served as an alternate host and supported sexual reproduction of the pathogen. Disease resistance in U.S. wheat has been effective against this pathogen, but now new pathogen types for which this resistance is not useful have arisen in Africa and are likely to arrive in the United States in the near future (Stokstad, 2007). The effects of climate on plant disease have been a direct object of study for decades. In contrast to many human diseases, the pathogens causing impor- tant plant diseases are often present on and around plants, ready to infect when environmental conditions become conducive. This has motivated the develop- ment of plant disease forecasting systems based on climatic variables such as 10â The Millennium Ecosystem Assessment is an evaluation of the effects of ecosystem change on human well-being assembled from the work of more than 1,360 scientists (see http://www. millenniumassessment.org).
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 145 temperature and precipitation (De Wolf and Isard, 2007). Although such models are not new, the need to address climate change has placed new demands on these models, the research underpinning them, and policy drawing upon them. This paper begins with a brief introduction to the typical methods for managing disease. The observed and potential effects of climate change on plant disease are then reviewed, with an emphasis on biological thresholds and interactions that may lead to particularly large impacts from climate shifts. The paper concludes with a discussion of research and policy needs for plant disease management in response to climate change. The Usual Challenges for Managing Plant Disease Pesticides are a common tool for managing plant disease. For some plant diseases such as potato late blight, crop production without pesticides is cur- rently impractical in many systems. In regions where education about pesticide safety is lacking, some farmers and their families experience chronic pesticide exposure. There are estimated to be between 1 and 5 million cases of pesticide poisoning each year, including many thousands of fatalities (UNEP, 2004). Shifts in pesticide use may thus result in shifts in unmanaged pesticide exposure, so that changes in demand for pesticides due to climate or other factors may have unexpected impacts on human health as well. Other disease management methods may be useful for specific diseases, such as removal of infected plant materials, introduction of biocontrol agents, management for disease-suppressive soils, or use of certified seed to avoid introduction of pathogens. Deployment of disease resistance genes is often the most attractive option for disease management in agricultural systems. For some diseases, resistance offers completely effective management, whereas for others, effective resistance is not known although partial resistance may still be a useful management component. There is little cost from use of resistance genes to growers or consumers, except that in some cases it may be challenging for plant breeders to combine desired resistance genes with other desirable plant characteristics. Breeding crops for disease resistance also offers challenges in terms of identifying resistance that is durable. The deployment of resistance genes is much more efficient if the genes are useful against pathogen populations for long periods of time even if exposed to large pathogen populations under disease-conducive environmental conditions. Pathogen adaptation to overcome disease resistance is an ongoing problem for the management of many diseases (McDonald and Linde, 2002). The use of cultivar mixtures is one method of resistance gene deployment that may increase the useful life of resistance genes in some cases. The manage- ment of rice blast in China offers a particularly dramatic example of the utility of mixtures for disease management, applied to over a million hectares. Higher- value susceptible rice varieties were grown in strips mixed with strips of lower- value resistant varieties. Both resistant and susceptible varieties experienced a
146 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS decrease in disease pressure compared to test plots where single varieties were grown for comparison (Zhu et al., 2000). In this case, it seems that microclimate was an important factor, such that the taller susceptible varieties experience rela- tively drier conditions when surrounded by the shorter resistant varieties (Zhu et al., 2005). The fact that agriculturalists have the ability to manipulate crop plant genet- ics makes plant disease management in agriculture much easier, in some respects, than human disease management. Problems can also arise from this ability, however, as particularly successful crop varieties become widespread. Thus, a common challenge for plant disease management is the general homogeneity of cropping systems in the United States and trends toward greater crop homoge- neity in most regions of the world. This homogeneity makes it easier for plant pathogens adapted to the common crop varieties to spread rapidly throughout crop plant populations. Margosian et al. (in revision) have evaluated the con- nectivity of the four major crop plants in the United States in terms of avail- ability of the crop host species. The connectivity of a landscape for a particular organism, in this case a plant pathogen, is a measure of the ease with which the organism can move through the landscape. Maize and soybean are strongly con- nected throughout much of their range. Wheat and cotton production are more fragmented, so that pathogen populations cannot move as readily through all production areas. Conversion to biofuel production has the potential to increase crop homogeneity. Maps of disease risk based on climate can be generated for diseases with reliable and widely applicable forecasting models. For example, Hijmans et al. (2000) mapped the risk of potato late blight based on climate parameters. Using updated forecasting models for potato late blight risk, Villanueva et al. (in preparation) estimated disease risk in the Altiplano region around Lake Titicaca (Figure 2-18). Such models are available for only very well-studied diseases, but Magarey et al. (2007) have developed a general model of infection risk for appli- cation in mapping the risk of new pathogens for which detailed models are not yet available. The combination of maps of current and future climatic conditions with models of pathogen risk can be adapted to evaluate changes in global risk in response to climate change. For example, Bergot et al. (2004) predicted the spread of the host-generalist pathogen Phytophthora cinnamomi in Europe. Implications of Climate Change Climate change will impact the productivity of agricultural and wildland plant populations through many mechanisms. One method for studying climate change effects on crop productivity is to study the correlation between climate variables and yield to date. Yield is the product of a number of factors, includ- ing losses to plant disease; partitioning the effects of these different factors will be necessary to develop a full understanding of the impacts of climate change.
*Year: 2001-2004 *Type of Cultivation: Clean Number of Fungicidal *First Planting Date: October 15 Applications *Cultivation Period: 180 days (Clean Cultivation) *Emergency: 35 days Late Blight Incidence in Zones of Potato Cultivation within the Bolivian- LEGEND Peruvian Antiplano (High Plains) International Border No Late Blight Antiplano Border Low Incidence Lakes Medium Incidence Regular Incidence High Incidence Source: Developed using the SIMCAST disease forecast model. FIGURE 2-18â Estimated potato late blight severity in the Altiplano area of Peru and Bolivia based on weather measures during 2001-2004 used in a late blight forecasting model. The comparable estimates for disease severity in 1995-1998 were for no late blight occurrence in the Figure 2-18 color region. As temperatures increase in the region, the risk of potato late blight may be expected to increase at higher altitudes. Color indicates the level of estimated disease, ranging from green = low to red = high, with a in boxes is overlaid in the number of fungicide applications partially bitmapped, though most type corresponding range needed for successful potato production. This figure was translated into English from the original (in Spanish) by Mila Gonzalez. SOURCE: Map courtesy of H. Villanueva, R. Raymundo, H. Juarez, W. Perez, and G. Forbes, International Potato Center. 147
148 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS The general trend toward warmer temperatures in recent years in many regions has facilitated study of the correlation between climate variables and yield. For example, rice productivity in the Philippines has shown a negative correlation with night temperature from 1979 to 2003 (Peng et al., 2004). Of course a chal- lenge for such analyses is to account well for all of the other potential causal factors of the system that may vary along with climatic parameters. Lobell et al. (2008) have analyzed which regions of the world are most likely to be confronted with food security issues resulting from climate change, concluding that south Asia and southern Africa are particularly at risk. In another analysis of global agriculture, Cline (2007) points out that potential benefits to agriculture in some areas in the first decades of global temperature change may give the public a false sense of security and make it more difficult to put policies in place to avoid problems from more extreme changes in later decades. A first step toward understanding wildland plant responses to climate change and the potential for adaptation to new climatic conditions is to address gene expression and underlying genetic diversity in wild plant populations. Travers et al. (2007) studied the effects of simulated precipitation change on big blue- stem, the dominant grass of tallgrass prairie of the U.S. Great Plains. Under the predicted future precipitation patterns with fewer and larger precipitation events leading to longer periods of drought stress, they observed lower expression of a gene associated with the hypersensitive response, a disease resistance reac- tion. Frank (2007) also studied big bluestem, finding higher infection rates and dampened phytohormonal responses to infection when plants experienced severe drought stress. Studying the diversity of resistance genes in wild plant popula- tions is still challenging because little is known about them and for the moment there are few tools available. Rouse (2007) studied a gene in big bluestem that is related to genes conferring disease resistance in sorghum, finding evidence for historical disease patterns in natural populations that vary in diversity for these genes across a gradient of disease conduciveness. The effectiveness of disease resistance genes may vary with climatic param- eters. For example, Webb et al. (in preparation) found that rice genes conferring resistance to rice blast have different effectiveness depending on temperature. Most resistance genes tested were less effective at higher temperatures, but one of the most effective genes was actually more effective at 35-29ÂºC day-night temperatures than at 29-21ÂºC. These differential responses will influence the selection pressures experienced by pathogen populations as temperatures fluctu- ate annually and shift over years (Webb et al., in preparation). Climatic changes and changes in CO2 concentrations can affect plant physi- ology, growth, and architecture in several ways that influence plant disease risk. On shorter time scales, stomatal closure in response to drought stress makes it more difficult for some pathogens to enter leaves. If plant canopies close ear- lier in the season due to changed conditions, the increased humidity in canopy microclimates may favor many pathogens. CO2 concentrations are expected to
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 149 impact pathogens directly as well, although a model for this impact is unlikely to be simple. For example, in a study of a set of fungal pathogens, Chakraborty et al. (2000) found that some species reproduced more rapidly under increased CO2, while other species reproduced more slowly. In wildland systems, climate change and increased CO2 concentrations may also have mixed effects. Mitchell et al. (2003) found that the fungal pathogen load in tallgrass prairie increased overall in response to higher ambient CO2. In montaine prairie, Roy et al. (2004) found mixed effects of simulated temperature increases, with some pathogens increasing in abundance and others decreasing. Desprez- Loustau et al. (2007) predicted that the effect of climate change on a set of forest pathogens in Europe will be to increase favorability for the majority of pathogens. In general, rising temperatures may favor soil fungi that cause damping-off in seed- lings, sometimes with high rates of mortality, a trend unlikely to be observed in the short term unless studies are designed specifically to look for such effects. Range shifts in pathogens are frequently observed. As others have discussed at this workshop, such range shifts can be difficult to interpret. For example, needle blight is moving northward in North America as temperature and precipi- tation patterns shift (Woods et al., 2005). It is reasonable to think that such range shifts may be driven by changing climatic conditions, but the correlative nature of the data makes it impossible to determine this conclusively. Ultimately these relationships will have to be addressed in projects that combine the full range of factors in field studies as well as more limited and controlled experiments that allow clear conclusions about the effects of factors to partition effects. The potential importance of extreme weather events is illustrated by the introduction of soybean rust to the United States. It is likely that spores of soy- bean rust entered the United States via Hurricane Ivan (Isard et al., 2005). 11 If such extreme weather events become more common, global movement of patho- gens will be accelerated. Soybean rust also offers an interesting example of the potential interactions between two invasive species. The widely introduced and problematic kudzu vine is another host of this pathogen and has the potential to play an important role as a pathogen reservoir during seasons when soybeans are not available for infection. Until now, however, movement of soybean rust has been slower than expected based on some predictions, probably due to environ- mental conditions that have not been conducive to disease. If the public becomes too complacent about the slower-than-predicted progress of soybean rust across the United States, this may result in more substantial problems if there is not sup- port for needed research and if soybean growers do not prepare adequately. The ultimate impact of changes in plant disease pressure, in either agri- cultural systems or wildland systems, will be determined in part by what plant 11â Of course, spores of this pathogen may well have entered the United States previously but been unsuccessful in establishing infection. Entry of large numbers of spores may be necessary for an invasive pathogen to âbeat the odds.â
150 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS genotypes or species replace those that have experienced more damage by dis- ease. Eviner and Likens (2008) summarize factors important for predicting the effects of disease on ecosystems, where one of the most important factors may be the functional similarities of infected host individuals versus the species that replace them. Through a broad ecosystem science lens, plant species may be generalized as composing âa single giant photosynthesizing leaf.â From this standpoint, damage to one or a few plant species may not be important if other species can play the same role. In eastern U.S. forests, while other tree species increased in abundance to photosynthesize in the place of American chestnuts, they did not provide other important ecosystem services such as production of chestnuts as food for humans and wildlife. Likewise, most agricultural systems are not diverse enough to readily accommodate removal of an important species such as soybeans, if soybean production were to become uneconomical due to a new disease such as soybean rust. Potential Interactions, Thresholds, and Positive Feedback Loops If a small change in average temperature or precipitation patterns results in a small change in plant disease risk, this may be relatively easy to accommodate in agricultural disease management and may have little impact on wildland systems. Climate change is a greater concern when interactions serve to amplify the effects on biological systems or when systems are currently near thresholds such that small changes in abiotic drivers may push them beyond the threshold and thus have important effects. Effects may also be exacerbated if positive feedback loops are in place so that increased disease pressure further increases disease risk. Abiotic environmental conditions are understood to be critically important in plant disease epidemiology, as commonly represented in the âplant disease triangleâ (Figure 2-19). The three components of this triangle are a susceptible host, a virulent pathogen (and effective vector, as needed), and a conducive abi- otic environment. For example, many fungal and oomycete pathogens benefit from higher levels of humidity. Surprising new disease problems may occur if the susceptible host and virulent pathogen have been present all along and the environment shifts to become more conducive. For example, potato late blight became an extreme problem for Irish food security during the potato famine when wetter years supported rapid disease development. The further interaction between high losses to disease and widespread reliance on potatoes as a primary food led to a disastrous situation. Allee effects represent one type of threshold. An Allee effect occurs when a species experiences greater limitations on per capita reproduction for small popu- lation sizes. Quorum sensing provides an interesting potential mechanism for this type of phenomenon, where bacterial populations may become pathogenic only when intraspecific signaling indicates that a sufficiently large population is present for infection. Smaller population sizes may also make it less likely that
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 151 Susceptible host Virulent pathogen Conducive environment FIGURE 2-19â The plant disease triangle, illustrating the relationship between host, pathogen, and environment necessary for disease to occur. individuals encounter mates. For example, the Karnal bunt pathogen requires encounters between two mating types for reproduction to occur, yet its propa- gules are wind dispersed, making encounters between individuals of different Figure 2-19 mating types unlikely when populations are small. The resulting Allee effect may help to explain why this species has not been more invasive, since encounters between mating types will be even less likely when dispersed by wind over larger areas (Garrett and Bowden, 2002). For species that experience them, such Allee effects interact with disease nonconducive environmental conditions to reduce the chance of infection still further. As a result, if climatic conditions become more conducive to disease so that pathogens are released from the constraint of the Allee effect, pathogen populations may increase much more rapidly than anticipated. The typical âcompound interestâ development of plant disease epidemics for pathogens with multiple generations per season can also result in important threshold structures. Infection levels can often increase by orders of magnitude toward the end of the season. If the length of the growing season increases, regional production of particular crop species may expand over time, with the longer season length allowing for huge increases in pathogen populations toward the end of the growing season. These populations may reduce yields during that season and also serve as large sources of inoculum for upcoming cropping sea- sons. Such higher regional inoculum loads may produce positive feedback loops, rendering local application of some management techniques less useful. For example, local application of techniques such as sanitation (removal of infected plant materials), use of cultivar mixtures, and use of disease resistance based on lower inoculum production all rely, at least to some extent, on an ability to control
152 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS local inoculum loads. If regional inoculum loads are too high, the contributions of these methods will be diminished (Garrett et al., in revision). Likewise, in wildland systems, plant diversity probably provides baseline regulation of plant disease that is unappreciated but may be diminished if systems become satu- rated with inoculum. Conversely, if seasons become shorter or if climatic condi- tions during significant parts of growing seasons become less disease conducive, greater benefits may be obtained from some management techniques. Pathogen range shifts may occur as climatic conditions change to allow infection and overwintering or oversummering in new areas. The effects of climatic shifts may interact with other phenomena, such as the introduction of new pathogen species or pathogen genotypes. For example, overwintering of the potato late blight pathogen is facilitated by the presence of different mat- ing types, which allows sexual production of a much hardier oospore and the potential for adaptation through production of new genotypes (Widmark et al., 2007). The combination of milder winters and introduction of new mating types may greatly increase problems with such pathogens. Range shifts and pathogen introductions will also result in new encounters between pathogen species, with the potential for hybridization to produce new pathogens (Brasier, 2001). Like- wise, the introduction or range shift of new vector species may make diseases much more important, such as in the case of the movement of the glassy-winged sharpshooter and resulting increased risk of Pierceâs disease of grapevines (Redak et al., 2004). Phenological shifts and range shifts in response to climate change may not follow the same patterns for plant hosts and pathogens. Some pathogens can only infect particular plant growth stages or organs, such as flowers. For example, the Fusarium head blight pathogen infects wheat anthers or other floral organs (Bai and Shaner, 2004). Shifts in flowering time phenology in response to climate change may not match shifts in pathogen phenology such that infection rates may unexpectedly rise or fall. Different patterns of geographic range shifts may result in new pathogen-host combinations (Parker and Gilbert, 2004). The genetic potential for adaptability of pathogen populations will be important in determin- ing whether any resulting reductions in infection will be short term or lasting. In general, the timeline of pathogen adaptation is likely to be much shorter than the timeline for plant adaptation. This will be especially true for long-lived plant species in wildlands, but also for annual crop species even with the full attention of agricultural scientists. Policy may also interact in important ways with abiotic conditions. Along with the Irish potato famine, another dramatic example is the dustbowl in the central United States. Policies that supported extensive plowing of lands in this area coincided with climatic conditions favoring wind erosion of soils. Either factor alone might have caused problems, but the combination of the two led to conditions devastating to the region. The interaction of biological and sociologi- cal factors may also result in amplified effects of climate change. For example, if
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 153 plant pathogens are intentionally introduced (Fletcher and Stack, 2007; Madden and Wheelis, 2003), bioterrorists using them might seek out the most environ- mentally conducive conditions for their establishment in vulnerable cropping sys- tems. Regions where local food security is closely tied to local food production will be particularly vulnerable to changes in crop disease pressure. Yet societies in these regions may also tend to rely on crop species that are less well supported by research and development. These âorphan crops,â such as millet, quinoa, cas- sava, and teff, need more research support to buffer the vulnerability of societies to which they are important (Nelson et al., 2004). Responding to Climate Change The good news for formulation of strategies for plant disease management under changing climate conditions is that much of what needs to be done is the same with or without climate change. Even if there were no long-term trend in climatic parameters, climatic variation from season to season, year to year, and region to region requires knowledge and tools for adapting to the different sce- narios. However, the potential for new combinations of climatic variables, along with the potential for interactions and for more rapid variation in conditions, rein- forces the need for research and policy responses to plant disease risk (Coakley et al., 1999; Garrett et al., 2006). Research directed explicitly toward understanding the complexity of system responses to climate change is needed. A mechanistic understanding of plant and pathogen responses to climate change will be based on characterizing current populations and their potential for adaptation. New genomic tools make it possible to characterize gene expres- sion and genotypic diversity much more readily in both wildland and agricultural plant communities. These tools can be applied in concert with other â-omicsâ approaches to link responses in gene expression (transcriptomics), lipidomics, and metabolomics for a fuller mechanistic understanding of adaptive potential. These approaches will have to be applied in multifactor studies of climate change effects, so that the interactions between the effects of changes in temperature, precipitation, CO2, and other environmental factors can be understood, along with the potential for adaptation. Tools for the study of pathogen population and community structure, gene expression, and other responses are evolving rapidly. Advances in sequencing technologies make the routine characterization of microbial communities feasible (Riesenfeld et al., 2004; Roesch et al., 2007) and will eventually make it inex- pensive. Microarrays, such as the GeoChip (He et al., 2007), are being designed to study microbial gene function in soils. New microarrays are needed to study the presence and expression of microbial genes related to plant disease. It will be important to collect baseline information about microbial community structure and function soon, so that changes in microbial communities under new climatic conditions can be studied. Experiments to compare responses of microbial com-
154 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS munities to new environments will also be important (e.g., Waldrop and Firestone, 2006). Undoubtedly there are many forms of disease suppressiveness provided by microbial communities in soils that offer benefits to agriculture and regulate disease in natural systems and are currently underappreciated. Research to clarify the effects of host landscape structures will help to improve strategies and will be necessary for studying changes at regional, conti- nental, and global scales. Current regional analyses of climatic effects on disease risk tend to be calculated for disease risk in individual âpixels,â important for developing a first-approximation estimate of risk. The next stage for such models will be to incorporate risk neighborhoods to improve estimates, where the risk for any given location will increase with proximity to higher-risk areas. Finally, regional and global models will need to incorporate pathogen evolution. Formu- lating and parameterizing these models will require advances in epidemiological theory and experimentation. For example, better data and models related to patho- gen and host dispersal, current levels of intraspecific diversity, and the strength of selection under different climate change scenarios are needed. Long-term geographically representative records of disease occurrence and the distribution of pathogens and hosts are rare, despite their importance for understanding epidemiology and trends in epidemics (Jeger and Pautasso, 2008). Global networks supporting the analysis of epidemics are needed. Progress toward this goal is in place; for example, the United States has developed a National Plant Diagnostic Network to facilitate data collection and analysis (Stack and Fletcher, 2007). To be most effective, this network ultimately needs to be linked with comparable national networks in other countries. It is to the advantage of the United States to assist other countries in setting up such networks for gather- ing and analyzing data, so that we can all benefit from more complete informa- tion. The use of model predictions for modifying agricultural management has proven useful in many parts of the world, including applications by resource-poor f Â armers based on climate predictions in Zimbabwe (Patt et al., 2005). One of the most important investments we can make is in conservation, char- acterization, and the development of strategies for optimal use of plant genetic resources. In wildland systems, conservation is necessary to increase the chances that plant populations are large enough to include individual genotypes adapted to new climate scenarios. In agricultural systems, conservation of diversity in crop species and their wild relatives is necessary to increase the chances that genes needed for resistance and tolerance to new biotic and abiotic stresses are maintained (Johnson, 2008). In situ conservation allows natural selection to con- tinue acting on these species. Ex situ conservation is a useful backup strategy and simplifies some analyses of accessions. International networks for conservation of crop genetic diversity, such as the institutions in the Consultative Group for Inter- national Agricultural Research (CGIAR), are critical for ensuring conservation and analysis of accessions. The funding currently available for such programs is very low compared to the importance of their mission. While investments such
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 155 as the Svalbard Global Seed Vault provide a last resort, active investigation of plant resources is needed. Ultimately our best response to the challenge of climate change in agriculture will be to develop diverse, flexible, and resilient agricultural systems that can adapt more readily to new climatic conditions. These systems will have to include well-prepared and well-funded agricultural scientists working globally to develop new strategies. In wildland systems, replacing plant species or genotypes at risk is a less attractive option. Since invasive pathogens can have the most important effects and have the potential to exacerbate the effects of climate change, policies to better reduce the spread of exotic pathogens will be important (Anderson et al., 2004; Burdon et al., 2006). Acknowledgments I appreciate valuable comments from members and staff of the Forum on Microbial Threats, R. Bowden, D. Rotenberg, and P. Garfinkel. It is also a plea- sure to acknowledge support by the U.S. National Science Foundation (NSF) through Grant DEB-0516046 and NSF Grant EF-0525712 as part of the joint NSF-National Institutes of Health (NIH) Ecology of Infectious Disease program; by the U.S. Agency for International Development (USAID) to the Office of International Research, Education, and Development (OIRED) at Virginia Tech for the Sustainable Agriculture and Natural Resource Management (SANREM) Collaborative Research Support Program (CRSP) under Award No. EPP-A-00- 04-00013-00 and for the Integrated Pest Management (IPM) CRSP under Award No. EPP-A-00-04-00016-00; and by the Kansas State Experiment Station (Con- tribution No. 08-308-B). CLIMATE CHANGE AND INFECTIOUS DISEASE: IMPACT ON HUMAN POPULATIONS IN THE ARCTIC12 Alan J. Parkinson, Ph.D.13 Centers for Disease Control and Prevention Introduction: The Arctic Environment The circumpolar region is defined as the region that extends above 60oN latitude, borders the Arctic Ocean, and includes all of or the northern parts of eight nations: the United States (Alaska), Canada, Greenland, Iceland, Norway, 12â The findings and conclusions in this report are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention. 13âArctic Investigations Program, Division of Emerging Infections and Surveillance Services, N Â ational Center for Preparedness Detection and Control of Infectious Disease, Anchorage, AK.
156 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Finland, Sweden, and the Russian Federation (see Figure 2-20). The climate in the Arctic varies geographically from severe cold in arid uninhabited regions to temperate forests bordering coastal agrarian regions. Approximately 4 million people live in the Arctic and almost half reside in northern regions of the Rus- sian Federation. Peoples of the Arctic and sub-Arctic regions live in social and physical environments that differ substantially from those of their more southern dwelling counterparts. These populations are comprised of varying proportions of indigenous and nonindigenous peoples (Stephansson Arctic Institute, 2004; see Figure 2-21). The indigenous populations of northern Canada (Northwest Territories, Yukon, Nunavut, northern Quebec, and Labrador), Alaska, and Greenland gener- ally reside in small communities in remote regions. They have little economic infrastructure and depend on subsistence hunting, fishing, and gathering of food for a significant proportion of their diet. In these remote areas, access to public health and acute care systems is often marginal and poorly supported. Life expec- tancy of the indigenous peoples of Alaska, northern Canada, and Greenland is lower than that of the general populations of the United States, Canada, and Nor- dic countries (Young, 2008). Similarly the infant morality rate for the indigenous segments of these populations is higher than that of the comparable national populations. Mortality rates for heart disease and cancer, once much lower among the indigenous populations of the United States, Canada, and northern European countries, are now similar to their respective national rates. The indigenous populations of Alaska, Canada, and Greenland have higher mortality rates for unintentional injury and suicide. Other health concerns of the indigenous peoples of the Arctic include the high prevalence of certain infectious diseases, such as hepatitis B, Helicobacter pylori, respiratory syncytial virus (RSV) infections in infants, and sexually transmitted diseases, as well as heath impacts associated with exposures to environmental pollutants, rapid economic change and modern- ization, and climate change (Bjerregaard et al., 2004). Climate Change and the Arctic Environment The Arctic, like most other parts of the world, warmed substantially over the twentieth century, principally in recent decades. Arctic climate models project continued warming with a 3-5oC mean increase by 2100. The winters will warm more than summers, the mean annual precipitation is projected to increase, and continued melting of land and sea ice is expected to increase river discharge and contribute to rising sea levels. These changes will be accompanied by greater overall climate variability and an increase in extreme weather events (Arctic Council, 2005). The rapid warming in the Arctic is already bringing about substantial eco- logical and socioeconomic impacts, many of which result from the thawing of permafrost, flooding, and shoreline erosion resulting from storm surges and
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 157 FIGURE 2-20â The circumpolar region showing administrative jurisdictions. SOURCE: Map by W. K. Dallmann. Reprinted from Young (2008) with permission from W. K. Dallmann and the International Journal of Circumpolar Health. Copyright 2008. Figure 2-20 color loss of protective sea ice. In many communities, the built infrastructure is sup- bitmapped ported by permafrost. Loss of this permafrost foundation will result in damage to water intake systems and pipes, and may result in contamination of the com- munity water supply. In addition, loss of foundation support for access roads, boardwalks, water storage tanks, and wastewater treatment facilities will render water distribution and wastewater treatment systems inoperable. Several villages already face relocation because village housing, water system, and infrastructure are being undermined (Warren et al., 2005). Rapid warming has resulted in the loss of annual Arctic sea ice. On Septem- ber 11, 2007, the Arctic sea ice cover reached the lowest extent recorded since
158 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Non-Indigenous Indigenous population population Total Population USA (Alaska) 648,818 Canada 130,275 Russia 1,982,450 Greenland Norway o 80 56,676 379,641 Finland 70 o 200,677 Iceland 288,471 Sweden 263,735 Faroe Islands o 60 47,704 Arctic circle AHDR Arctic boundary FIGURE 2-21â The circumpolar region showing indigenous and nonindigenous popula- tion distributions. Figure 2-21, replaced with vector version SOURCE: Reprinted from Stefansson Arctic Institute (2004) with permission from W. K. Dallmann, Norwegian Polar Institute and theoriginal source. Institute. Copyright 2004. downloaded from Stefansson Arctic observations began in the 1970s, exceeding the most pessimistic model predic- tions of an ice-free Arctic by 2050 (Richter-Menge et al., 2008; Figure 2-22). This dramatic reduction in sea ice will have widespread effects on marine eco- systems, coastal climate, human settlements, and subsistence activities. For the first time the reduction in annual sea ice has created ice-free shipping lanes to the northwest, from northern Labrador through the Arctic archipelago in northern Canada, to the Bering Strait, and has almost completely cleared a passage to the northeast, from the Bering Strait along the northern coast of the Russian Federa- tion to Norway (see Figure 2-23). Both routes represent time- and fuel-saving shortcuts between the Pacific and Atlantic Oceans and will bring an increase in marine transport and access to vast oil, gas, and mineral reserves once inacces- sible to exploration and exploitation.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 159 Figure 2-22A also Figure SA-13-B bitmapped image FIGURE 2-22â The Arctic ice cap, September 2001 (Top) and September 2007 (Bottom). SOURCE: NASA, as printed in Borgerson (2008). Figure 2-22B Such access will bring many benefits as well as risks to once isolated Arctic also communities. Construction of new coast guard or military bases and other indus- Figure SA-13-B trial ventures will bring employment opportunities to local populations, but will bitmapped image also affect population distribution, dynamics, culture, and local environments. Tourism will most likely increase. Public sector and government services will then increase to support the new emerging economies. These events will greatly
160 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Northwest Northern Passage Sea Route 2010-2030 2040-2060 Projected Ice Extent Observed Ice Extent (5-Model Average for September) September 2002 2070-2090 Projected Winter Surface Air Temperature Change: Â°C 1990s-2090s +12 +10 +8 +6 +4 +2 0 FIGURE 2-23â Proposed northwest and northeast shipping lanes through the Arctic Ocean joining the Atlantic and Pacific Oceans. SOURCE: Map by C. Grabhorn Reprinted from ACIA (2004) with permission from Cam- bridge University Press and C. Grabhorn. Figure 2-23 Replaced with high-resolution download from source challenge the traditional subsistence way of life for many communities and lead All type is now real type to rapid and long-term cultural change, which will create additional stress on an background is bitmapped already vulnerable population (Curtis et al., 2005). Climate Change and Human Health The direct health effects of climate change will result from changes in ambi- ent temperature, altered patterns of risk from outdoor activities, and changes in the incidence of infectious diseases. As ambient temperature increases, the
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 161 incidence of hypothermia and associated morbidity and mortality may decrease. Conversely hyperthermia may increase, particularly among the very young and the elderly (Nayha, 2005). However, because of the low mean temperature in many Arctic regions, the likelihood of such events having large impacts on public health for the general population is low. More significantly, unintentional injury, mostly related to subsistence hunting and fishingâalready a significant cause of mortality among Arctic residentsâmay increase (Arctic Council, 2005). The reduction in river and sea ice thickness, curtailed ice season, reduced snow cover, and permafrost thawing will make hunting and gathering more difficult, dangerous, and less successful, thereby increasing the risk of injuries and death by drowning. Permafrost thawing erosion or flooding can force relocation. Communities and families undergoing relocation will have to adapt to new ways of living, may face unemployment, and will have to integrate and create new social bonds. Relo- cation may also lead to rapid and long-term cultural change and loss of traditional culture, which will increase individual and community stress, leading to mental and behavioral health challenges (Hess et al., in press). Climate change already poses a serious threat to the food security of many Arctic communities because of their reliance on traditional subsistence hunting and fishing for survival. Populations of marine and land mammals, fish, and waterfowl may be reduced or displaced by changing habitats and migration patterns, further reducing the traditional food supply. Release of environmental contaminants from the atmosphere and melting glaciers and sea ice may increase the levels of these pollutants entering the food chain, making traditional foods less desirable (AMAP, 2003). Reduction in traditional food supply will force indigenous communities to depend increasingly on nontraditional and often less healthy Western foods. This will most likely result in increasing rates of modern diseases associated with processed foods, such as obesity, diabetes, cardiovas- cular diseases, and outbreaks of food-borne infectious diseases associated with imported fresh and processed foods (Bjerregaard et al., 2004; Orr et al., 1994). Many host-parasite systems are particularly sensitive to climate change. Specific stages of the life cycles of many helminths may be greatly affected by temperature. For example, small increases in temperature can substantially increase the transmission of lung worms and muscle worms pathogenic to wild- life that are important as a food source for many northern communities (Hoberg et al., 2008). Climate Change and Infectious Diseases in the Arctic It is well known that climate and weather affect the distribution and risk of many vector-borne diseases, such as malaria, RVF, plague, and dengue fever in tropical regions of the globe. Weather also affects the distribution of food- and water-borne diseases and emerging infectious diseases, such as West Nile virus,
162 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS hantavirus, and Ebola hemorrhagic fever (Haines et al., 2006). Less is known about the impact of climate change and the risk and distribution of infectious dis- eases in Arctic regions. It is known that Arctic populations have a long history of both endemic and epidemic infectious diseases (Parkinson et al., 2008). However, with the introduction of antimicrobial drugs, vaccines, and public health systems, morbidity and mortality due to infectious diseases have been greatly reduced. Despite these advances, high rates of invasive diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, and Mycobacterium tuberculosis persist (Bruce et al., 2008a,b; Christensen et al., 2004; Dawar et al., 2002; Degani et al., 2008; Gessner et al., 1998; Meyer et al., 2008; Netesov and Conrad, 2001; Nguyen et al., 2003; Singleton et al., 2006; SÃ¸borg et al., 2001). Sharp seasonal epidemics of viral respiratory infections also commonly occur (Bulkow et al., 2002; ÂKarron et al., 1999; Van Caeseele et al., 2001). The overuse of antiÂmicrobial drugs in some regions has led to the emergence of multidrug-resistant S. pneumoniae, Helicobacter pylori, and methicillin-resistant Staphylococcus aureus (Baggett et al., 2003, 2004; McMahon et al., 2007; Rudolph et al., 1999, 2000). The impact of climate on the incidence of these existing infectious disease challenges is unknown. In many Arctic regions, however, inadequate hous- ing and sanitation are already important determinants of infectious disease transmission. The cold northern climate keeps people indoors amplifying the effects of household crowding, smoking, and inadequate ventilation. Crowded living conditions increase person-to-person spread of infectious diseases and favor the transmission of respiratory and gastrointestinal diseases and skin infections. Many homes in communities across the Arctic lack basic sanita- tion services (e.g., flush toilet, shower or bath, kitchen sink). Providing these services is difficult in remote villages where small isolated populations live in a harsh cold climate. A recent study in western Alaska demonstrated two to four times higher hospitalization rates among children less than 3 years of age for pneumonia, influenza, and childhood RSV infections in villages where the majority of homes had no in-house piped water, compared with villages where the majority of homes had in-house piped water service. Likewise, outpatient Staphylococcus aureus infections and hospitalization for skin infections among persons of all ages were higher in villages with no in-house piped water service compared to villages without water service (Hennessy et al., 2008). Damage to the sanitation infrastructure by melting permafrost or flooding may there- fore result in increased rates of hospitalization among children for respiratory infections, as well as an increased rate of skin infections and diarrheal diseases caused by bacterial, viral, and parasitic pathogens. Some infectious diseases are unique to the Arctic and lifestyles of the indig- enous populations and may increase in a warming Arctic. For example, many Arctic residents depend on subsistence hunting, fishing, and gathering for food, and on a predictable climate for food storage. Food storage methods often include above ground air-drying of fish and meat at ambient temperature, below ground
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 163 cold storage on or near the permafrost, and fermentation. Changes in climate may prevent the drying of fish or meat, resulting in spoilage. Similarly, loss of the permafrost may result in spoilage of food stored below ground. Outbreaks of food-borne botulism occur sporadically in communities in the United States, Canadian Arctic, and Greenland and are caused by ingestion of improperly pre- pared fermented traditional foods (CDC, 2001; Proulx et al., 1997; Sobel et al., 2004; SÃ¸rensen et al., 1993; Wainwright et al., 1988). Because germination of Clostridium botulinum spores and toxin production will occur at temperatures greater than 4Â°C, it is possible that warmer ambient temperatures associated with climate change may result in an increased rate of food-borne botulism in these regions. Preliminary studies have shown that fermentation of aged seal meat chal- lenged with C. botulinum at temperatures above 4oC results in toxin production (Leclair et al., 2004). Outbreaks of gastroenteritis caused by Vibrio parahaemolyticus have been related to the consumption of raw or inadequately cooked shellfish collected from seawater at temperatures of higher than 15oC. Prior to 2004, the most northerly outbreak occurred in northern British Columbia in 1997. However, in July 2004, an outbreak of gastroenteritis caused by V. parahaemolyticus was documented among cruise ship passengers consuming raw oysters while visiting an oyster farm in Prince William Sound, Alaska (McLaughlin et al., 2005). The outbreak investigation documented an increase of 0.21oC per year in the July-August water temperature since 1997, and reported that 2004 was the first year that the oyster farm water temperature exceeded 15oC in July. This event provides direct evidence of an association between rising seawater temperature and the onset of illness. Warmer temperatures may allow infected host animal species to survive winters in larger numbers, increase in population, and expand their range of habitation, thus increasing the opportunity to pass infections to humans. For example, milder weather and less snow cover may have contributed to a large outbreak of Puumala virus infection in northern Sweden in 2007. Puumala virus is endemic in bank voles, and in humans causes hemorrhagic fever with renal syndrome (Pettersson et al., 2008). Similar outbreaks have been noted in the Russian Federation (Revich, 2008). The climate-related northern expansion of the boreal forest in Alaska and northern Canada has favored the steady north- ward advance of the beaver, extending the range of Giardia lamblia, a parasitic infection of beaver that can infect other mammals, including humans who use untreated surface water (Arctic Council, 2005). Similarly, warmer temperatures in the Arctic and sub-Arctic regions could support the expansion of the geographi- cal range and populations of foxes and voles, common carriers of Echinococ- cus multilocularis, the cause of alveolar echinococcus in humans (Holts et al., 2005). The prevalence of alveolar echinococcus has risen in Switzerland as fox populations have increased in size and expanded their geographic ranges into urban areas (Schweiger et al., 2007). Alveolar echinococcus was common in two
164 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS regions of northwestern Alaska prior to 1997. Disease in humans was associated with contact with dogs; however, improvements in housing and dog lot manage- ment have largely eliminated dog-to-human transmission in Alaska. This may not be the case, however, in other parts of the Arctic where human infections with Echinococcus granulosis, and E. multilocularis are still reported, particularly in association with communities dependent on reindeer herding and dog use (Castrodale et al., 2002; Rausch, 2003). Climate change may also influence the density and distribution of animal hosts and mosquito vectors, which could result in an increase in human illness or a shift in the geographical range of disease caused by these agents. The impact of these changes on human disease incidence has not been fully evaluated, but there is clearly potential for climate change to shift the geographical distribu- tion of certain vector-borne and other zoonotic diseases. For example, West Nile virus entered the United States in 1999 and in subsequent years infected human, horse, mosquito, and bird populations across the United States and as far north as northern Manitoba, Canada (Parkinson and Butler, 2005). In the Russian Federation infected birds and humans have been detected as far north as the region of Novosibirsk (Revich, 2008). Although there is, at present, insufficient information about the relationship between climate and the spread of West Nile virus, a number of factors may contribute to its further northward migration. Milder winters could favor winter survival of infected Culex spp. mosquitoes, the predominant vector of West Nile virus, which since the 1970s have migrated as far north as Prince Albert, Saskatchewan in Canada. Longer, hotter summers increase the transmission season leading to higher numbers of infected mosqui- toes and greater opportunities for human exposure. Climate change may alter the disease ecology and migration patterns of other reservoirs such as birds. These factors may affect disease incidence and result in expansion of the range of other arthropod vector-borne diseases. A number of mosquito-borne viruses that cause illness in humans circulate in the U.S. Arctic and northern regions of the Russian Federation (Walters et al., 1999). Jamestown Canyon and Snowshoe Hare viruses are considered emerg- ing threats to the public health in the United States, Canada, and the Russian Federation, causing flu-like symptoms and central nervous system diseases, such as aseptic meningitis and encephalitis (Walters et al., 1999). Sindbis virus also circulates in northern Europe. The virus is carried northward and amplified by migratory birds. In the late summer, ornithophilic mosquitoes pass the virus onto humans causing epidemics of Pogosta disease in northern Finland, an ill- ness characterized by a rash and arthritis (Kurkela et al., 2008). In Sweden, the incidence of tick-borne encephalitis (TBE) has substantially increased since the mid-1980s (Lindgren and Gustafson, 2001). This increase corresponds to a trend of milder winters and an earlier onset of spring, resulting in an increase in the tick population (Ixodes ricinus) that carries the virus responsible for TBE and other potential pathogens (SkarphÃ©dinsson et al., 2005). Similarly in north-
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 165 eastern Canada, climate change is projected to result in a northward shift in the range of Ixodes scapularis, a tick that carries Borrelia burgdorferi, the etiologic agent of Lyme disease. The current northern limit of Ix. scapularis is southern Ontario including the shoreline of Lake Erie and southern coast of Nova Scotia. Some temperature-based models show the potential for a northward expansion of Ix. scapularis above 60oN latitude and into the Northwest Territories by 2080 (Ogden et al., 2005). However, it should be noted that tick distribution is influenced by additional factors such as habitat suitability and dispersal patterns which can affect the accuracy of these predictions. Whether or not disease in humans is a result of these climate change-induced alterations in vector range depends on many other factors, such as land-use practices, human behavior (suburban development in wooded areas, outdoor recreational activities, use of insect repellents, etc.), human population density, and adequacy of the public health infrastructure. Response to Climate Change in the Arctic In 1992, the IOM published a report titled Emerging Infections: Microbial Threats to Health in the United States. This report uncovered major challenges for public health in the medical community primarily related to detecting and manag- ing infectious disease outbreaks and monitoring the prevalence of endemic infec- tious diseases. It stimulated a national movement to reinvigorate the U.S. public health system to address the HIV/AIDS epidemic, the emergence of new diseases, the resurgence of old diseases, and the persistent evolution of Âantimicrobial resis- tance. In a subsequent report, the IOM provided an assessment of the capacity of the public health system to respond to emerging threats and made recommenda- tions for addressing infectious disease threats to human health (IOM, 2003). Because climate change is expected to exacerbate many of the factors con- tributing to infectious disease emergence and reemergence, the recommendations of the 2003 IOM report can be applied to the prevention and control of emerging infectious disease threats resulting from climate change. A framework for public health response to climate change in the United States has recently been proposed (Frumkin et al., 2008; Hess et al., in press). The framework emphasizes the need to capitalize on and enhance existing essential public health services and to improve coordination efforts between government agencies (federal, state, and local), academia, the private sector, and nongovernmental organizations. Applying this framework to Arctic regions requires enhancing the public health capacity to monitor diseases with potentially large public health impacts, including respiratory diseases in children, skin infections, and diarrheal diseases, particularly in communities with failing sanitation systems. Monitoring certain vector-borne diseases, such as West Nile virus, Lyme disease, and TBE, should be priorities in areas at the margins of focal regions known to support both ani- mal and insect vectors, and where climate change may promote the geographic
166 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS expansion of vectors. Because Arctic populations are relatively small and widely dispersed over a large area, region-specific detection of significant trends in emerging climate-related infectious diseases may be delayed. This difficulty may be overcome by linking regional monitoring systems together for the purposes of sharing standardized information on climate-sensitive infectious diseases of mutual concern. Efforts should be made to harmonize notifiable disease registries, laboratory methods, and clinical surveillance definitions across administrative jurisdictions to allow comparable disease reporting and analysis. An example of such a network is the International Circumpolar Surveillance system for emerg- ing infectious diseases. This network links hospital and public health laboratories together for the purposes of monitoring invasive bacterial diseases and tubercu- losis in Arctic populations (Parkinson et al., 2008). Public health capacity should be enhanced to respond to infectious disease food-borne outbreaks (e.g., botulism, gastroenteritis caused by Giardia lamblia or Vibro parahaemolyticus). Public health research is needed to determine the baseline prevalence of potential climate-sensitive infectious diseases (e.g., West Nile virus, Borrelia burgdorferi, Brucella spp., Echinococcus spp., Toxoplasma spp.) in both human and animal hosts in regions where emergence may be expected. Such studies can be used to accumulate additional evidence of the effect of climate change or weather on infectious disease emergence, to guide early detection and public health intervention strategies, and to provide science- based support for public health actions on climate change. The circumpolar coordination of research efforts will be important not only to harmonize research protocols, laboratory methods, data collection instruments, and data analysis, but also to maximize the impact of scarce resources and to minimize the impact of research on affected communities. Coordination can be facilitated through exist- ing international cooperatives, such as the Arctic Council,14 the International Union for Circumpolar Health,15 and the newly formed International Network of Circumpolar Health Researchers.16 The challenge in the Arctic, however, will be to ensure sufficient public health capacity to allow the detection of disease outbreaks and monitor infectious disease trends most likely to be influenced by climate. The remoteness of many communities from clinical or public health facilities, and the harsh weather condi- tions of Arctic regions, often preclude appropriate specimen and epidemiologic data collection during an outbreak investigation, research, or ongoing surveillance activities. Staffing shortages are frequent in many in local clinics and regional hospitals that are already overwhelmed by routine and urgent care priorities, leaving little capacity for existing staff to assist public health personnel in out- break investigations, research, or maintenance of routine surveillance activities. 14â See http://www.arctic-council.org. 15â See http://www.iuch.org. 16â See http://www.inchr.org.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 167 Additional resources and training may be needed to ensure adequate staffing at these facilities, to address existing gaps between regional clinics and hospitals and public health departments, and to ensure a sufficiently trained staff to address the emerging public health impacts posed by climate change. A key aspect of the public health response to climate change in Arctic regions will be the formation of community-based partnerships with tribal governments to identify potential threats to the community and develop strategies to address those threats. Communities at greatest risk should be targeted for education, out- reach, and assessment of existing or potential health risks, vulnerabilities, and engagement in the design of community-based monitoring and the formulation of intervention strategies. The identification, selection, and monitoring of basic indicators for climate change and community health will be important for any response to climate change at the community level (Furgal, 2005). The selection of site- or village-specific indicators should be guided by local concerns and may include activities such as the surveillance of a key wildlife or insect species in a region where climate changes may contribute to the emergence of new zoonotic diseases or the measurement of weather (i.e., precipitation and temperature), water quality (i.e., turbidity, pathogens), and gastrointestinal illness (i.e., clinic visits) in a community. Linking communities across regions and internationally should facilitate the sharing of standard protocols, data collection instruments, and data for analysis. These linkages will be important for the detection of trends over larger geographic regions, should enhance a communityâs ability to detect changes that impact health, and will allow the development of strategies to minimize the negative health impacts of climate change on Arctic residents in the future. Conclusion Resident indigenous populations of the Arctic are uniquely vulnerable to climate change because of their close relationship with, and dependence on, the land, sea, and natural resources for their cultural, social, economic, and physical well-being. The increasing mean ambient temperature may lead to an increase in food-borne diseases, such as botulism and gastrointestinal illnesses. An increase in mean temperature may also influence the incidence of zoonotic and arboviral infectious diseases by changing the population density and range of animal hosts and insect vectors. The public health response to these emerging microbial threats should include enhancing the public health capacity to monitor climate-sensitive infectious diseases with potentially large public health impacts; the prompt inves- tigation of infectious disease outbreaks that may be related to climate change; and research on the relationship between climate and infectious disease emergence to guide early detection and public health interventions. The development of community-based monitoring networks with links to regional and national public health agencies as well as circumpolar health organizations will facilitate method
168 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS standardization, data-sharing, and the detection of infectious disease trends over a larger geographic area. This capacity is essential for the development of strate- gies to minimize the negative effects of climate change on the health of Arctic residents in the future. REFERENCES Overview References Borgerson, S. G. 2008. Arctic meltdown: the economic and security implications of global warming. Foreign Affairs 87(2):63-77. Chretien, J. P., A. Anyamba, S. A. Bedno, R. F. Breiman, R. Sang, K. Sergon, A. M. Powers, C. O. Onyango, J. Small, C. J. Tucker, and K. J. Linthicum. 2007. Drought-associated chi- kungunya emergence along coastal East Africa. American Journal of Tropical Medicine and Hygiene 76(3):405-407. Fritz, C. L., D. T. Dennis, M. A. Tipple, G. L. Campbell, C. R. McCance, and D. J. Gubler. 1996. Surveillance for pneumonic plague in the United States during an international emergency: a model for control of imported emerging diseases. Emerging Infectious Diseases 2(1):30-36. IPCC (Intergovernmental Panel on Climate Change). 2007. Climate change 2007: the physical science basis. Contribution of Working Group I to the fourth assessment report of the IPCC. Cambridge, UK: Cambridge University Press. Linthicum, K. J., A. Anyamba, C. J. Tucker, P. W. Kelley, M. F. Myers, and C. J. Peters. 1999. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya. Science 285(5426):397-400. Stenseth, N. C., N. I. Samia, H. Viljugrein, K. L. Kausrud, M. Begon, S. Davis, H. Leirs, V. M. Dubyanskiy, J. Esper, V. S. Ageyev, N. L. Klassovskiy, S. B. Pole, and C. Kung-Sik. 2006. Plague dynamics are driven by climate variation. Proceedings of the National Academy of Sci- ences 103(35):13110-13115. Colwell References Colwell, R. R. 1996. Global climate and infectious disease: the cholera paradigm. Science 274(5295):2025-2031. Colwell, R. R., and A. Huq. 1994. Vibrios in the environment: viable but nonculturable Â Vibrio cholerae. In: Vibrio cholerae and cholera: molecular to global perspectives, edited by I. K. Wachsmuth, O. Olsvik, and P. A. Blake. Washington, DC: American Society for Micro- biology. Pp. 117-133. Gil, A. I., V. R. Louis, I. N. Rivera, E. Lipp, A. Huq, C. F. Lanata, D. N. Taylor, E. Russek-Cohen, N. Choopun, R. B. Sack, R. R. Colwell.Â 2004.Â Occurrence and distribution of Vibrio cholerae in the coastal environment of Peru. Environmental Microbiology 6(7):699-706.Â Rawlings, T., G. M. Ruiz, and R. R. Colwell. 2007. Association of Vibrio cholerae O1 El Tor and O139 Bengal with the copepods Acartia tonsa and Eurytemora affinis. Applied Environmental Microbiology 73(24):7926-7933. WHO (World Health Organization). 2005. Weekly epidemiological record 80(31):261-268, http:// www.who.int/wer/2005/wer8031.pdf (accessed May 1, 2008).
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 169 Chretien et al. References Anyamba, A., K. J. Linthicum, R. Mahoney, C. J. Tucker, and P. W. Kelley. 2002. Mapping potential risk of Rift Valley fever outbreaks in African savannas using vegetation index time series data. Photogrammetric Engineering and Remote Sensing 68(2):137-145. Anyamba, A., J. P. Chretien, J. Small, C. J. Tucker, and K. J. Linthicum. 2006. Developing global climate anomalies suggest potential disease risks for 2006-2007. International Journal of Health Geographics 5:60. Bedno, S. A., C. O. Onyango, C. Njugana, R. Sang, S. Gaydos, K. Sergon, and R. F. Breiman. 2006. Outbreak of chikungunya in Lamu, Kenya, 2004. Paper presented at the International Confer- ence on Emerging Infectious Diseases, Atlanta, GA. CDC (Centers for Disease Control and Prevention). 1998. Rift Valley feverâEast Africa, 1997-1998. Morbidity and Mortality Weekly Report 47(13):261-264. Chretien, J, P., and K. J. Linthicum. 2007. Chikungunya in Europeâwhatâs next? Lancet 370(9602):1805-1806. Chretien, J. P., A. Anyamba, S. A. Bedno, R. F. Breiman, R. Sang, K. Sergon, A. M. Powers, C. O. Onyango, J. Small, C. J. Tucker, and K. J. Linthicum. 2007. Drought-associated chi- kungunya emergence along coastal East Africa. American Journal of Tropical Medicine and Hygiene 76(3):405-407. FAO (Food and Agriculture Organization). 2006. Possible RVF activity in the Horn of Africa. EMPRES Watch. IOM (Institute of Medicine). 2003. Microbial threats to health: emergence, detection, and response. Washington, DC: The National Academies Press. IPCC (Intergovernmental Panel on Climate Change). 2007a. Climate change 2007: the physical science basis. Contribution of Working Group I to the fourth assessment report of the IPCC. Cambridge, UK: Cambridge University Press. Chapter 3. âââ. 2007b. Climate change 2007: the physical science basis. Contribution of Working Group I to the fourth assessment report of the IPCC. Cambridge, UK: Cambridge University Press. Chapter 10. Kovats, R. S., M. J. Bouma, S. Hajat, E. Worrall, and A. Haines. 2003. El NiÃ±o and health. Lancet 362(9394):1481-1489. Linthicum, K. J., F. G. Davies, C. L. Bailey, and A. Kairo. 1984. Mosquito species encountered in a flooded grassland dambo in Kenya. Mosquito News 44:228-232. Linthicum, K. J., A. Anyamba, C. J. Tucker, P. W. Kelley, M. F. Myers, and C. J. Peters. 1999. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya. Science 285(5426):397-400. Mavalankar, D., P. Shastri, and P. Raman. 2007. Chikungunya epidemic in India: a major public-health disaster. Lancet Infectious Disease 7(5):306-307. Peters, C. J., and K. J. Linthicum. 1994. Rift Valley fever. In Handbook of zoonoses, Second edition, edited by G. B. Beran. Boca Raton, FL: CRC Press, Inc. Rezza, G., L. Nicoletti, R. Angelini, R. Romi, A. C. Finarelli, M. Panning, P. Cordioli, C. Fortuna, S. Boros, F. Magurano, G. Silvi, P. Angelini, M. Dottori, M. G. Ciufolini, G. C. Majori, and A. Cassone. 2007. Infection with chikungunya virus in Italy: an outbreak in a temperate region. Lancet 370(9602):1840-1846. Save the Children Alliance. 2007 (January 11). Horn of Africa emergency statement, http://www. savethechildren.net/alliance/media/newsdesk/2007-01-01.html (accessed March 4, 2008). Sergon, K., C. Njuguna, R. Kalani, V. Ofula, C. Onyango, L. S. Konongoi, S. Bedno, H. Burke, A. M. Dumilla, J. Konde, M. K. Njenga, R. Sang, and R. F. Breiman. 2008. Seroprevalence of chikungunya virus (CHIKV) infection on Lamu Island, Kenya, October 2004. American Journal of Tropical Medicine and Hygiene 78(2):333-337.
170 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Tsetsarkin, K. A., D. L. Vanlandingham, C. E. McGee, and S. Higgs. 2007. A single mutation in Chi- kungunya virus affects vector specificity and epidemic potential. PLoS Pathogens 3(12):e201. UN (United Nations). 2004. Kenya flash appeal, http://www.un.org/depts/ocha/cap/kenya.html (ac- cessed March 4, 2008). âââ. 2006. Global survey of early warning systems: an assessment of capacities, gaps, and oppor- tunities towards building a comprehensive global early warning system for all natural hazards, http://www.unisdr.org/ppew/info-resources/ewc3/Global-Survey-of-Early-Warning-Systems.pdf (accessed March 4, 2008). Watts, D. M., D. S. Burke, B. A. Harrison, R. E. Whitmire, and A. Nisalak. 1987. Effect of tempera- ture on the vector efficiency of Aedes aegypti for dengue 2 virus. American Journal of Tropical Medicine and Hygiene 36(1):143-152. WHO (World Health Organization). 2004. Using climate to predict infectious disease outbreaks: a review, http://www.who.int/globalchange/publications/oeh0401/en/ (accessed March 4, 2008). âââ. 2006. Chikungunya and dengue in the south west Indian Ocean, http://www.who.int/csr/ don/2006_03_17/en/ (accessed March 4, 2008). âââ. 2007a. Outbreaks of Rift Valley fever in Kenya, Somalia and United Republic of Tanzania, December 2006-April 2007. Weekly Epidemiological Record 82(20):169-178. âââ. 2007b. Health action in crises. Highlights No 140â8 to 14 January 2007, http://www.who. int/hac/donorinfo/highlights/highlights_140_08_14jan2007.pdf (accessed March 4, 2008). Stenseth References Achtman, M., K. Zurth, G. Morelli, G. Torrea, A. Guiyoule, and E. Carniel. 1999. Yersinia pestis, the cause of plague, is a recently emerged clone of Yersinia pseudotuberculosis. Proceedings of the National Academy of Sciences 96(24):14043-14048. Anyamba, A., J. P. Chretien, J. Small, C. J. Tucker, and K. J. Linthicum. 2006. Developing global climate anomalies suggest potential disease risks for 2006-2007. International Journal of Health Geographics 5:60. Baltazard, M., Y. Karimi, M. Eftekhari, M. Chamsa, and H. H. Mollaret. ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ 1963. La conservation interÃ©pizootique de la peste en foyer invÃ©tÃ©rÃ© hypothÃ¨ses de travail. Bulletin de la SociÃ©tÃ© de Pathologie Exotique 56:1230-1241. Ben Ari, T., A. Gershunov, K. L. Gage, T. SnÃ¤ll, P. Ettestad, K. L. Kausrud, and N. C. Stenseth. 2008. Human plague in U.S.: the importance of regional and local climate. Biology Letters (in review). Blanc, G. 1956. Une opinion non conformiste sur le mode de transmission de la peste. Revue dâHygiÃ©ne et de MÃ©decine Sociale 4(6):532-562. Chamberlain, N. 2004. Plague, http://www.kcom.edu/faculty/chamberlain/Website/lectures/lecture/ plague.htm (accessed July 1, 2008). Cohn, S. K., Jr. 2002. The Black Death transformed: disease and culture in early Renaissance Europe. London, UK: Edward Arnold Publishers. Davis, S., M. Begon, L. De Bruyn, V. S. Ageyev, N. L. Klassovskiy, S. B. Pole, H. Viljugrein, N. C. Stenseth, and H. Leirs. 2004. Predictive thresholds for plague in Kazakhstan. Science 304(5671):736-738. Davis, S., H. Leirs, H. Viljugrein, N. C. Stenseth, L. De Bruyn, N. Klassovskiy, V. Ageyev, and M. Begon. 2007. Empirical assessment of a threshold model for sylvatic plague. Journal of the Royal Society Interface 4(15):649-657. Drancourt, M., L. Houhamdi, and D. Raoult. 2006. Yersinia pestis as a telluric, human ectoparasite- borne organism. Lancet Infectious Diseases 6(4):234-241.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 171 Duplantier, J. M., J. B. Duchemin, S. Chanteau, and E. Carniel. 2005. From the recent lessons of the ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ Malagasy foci towards a global understanding of the factors involved in plague reemergence. Veterinary Research 36(3):437-453. Esper, J., S. G. Shiyatov, V. S. Mazepa, R. J. S. Wilson, D. A. Graybill, and G. Funkhouser. 2003. Temperature-sensitive Tien Shan tree ring chronologies show multi-centennial growth trends. Climate Dynamics 21(7/8):8p. Frigessi, A., M. Holden, C. Marshall, H. Viljugrein, N. C. Stenseth, L. Holden, V. Ageyev, and N. L. Klassovskiy. 2005. Bayesian population dynamics of interacting species: great gerbils and fleas in Kazakhstan. Biometrics 61(1):230-238. Fritz, C. L., D. T. Dennis, M. A. Tipple, G. L. Campbell, C. R. McCance, and D. J. Gubler. 1996. Surveillance for pneumonic plague in the United States during an international emergency: a model for control of imported emerging diseases. Emerging Infectious Diseases 2(1):30-36. Gage, K. L., and M. Y. Kosoy. 2005. Natural history of plague: perspectives from more than a century of research. Annual Review of Entomology 50(1):505-528. Galimand, M., A. Guiyoule, G. Gerbaud, B. Rasoamanana, S. Chanteau, E. Carniel, and P. Courvalin. 1997. Multidrug resistance in Yersinia pestis mediated by a transferable plasmid. New England Journal of Medicine 337(10):677-680. Guiyoule, A., F. Grimont, I. Iteman, P. A. Grimont, M. Lefevre, and E. Carniel. 1994. Plague pan- demics investigated by ribotyping of Yersinia pestis strains. Journal of Clinical Microbiology 32(3):634-641. Guiyoule, A., G. Gerbaud, C. Buchrieser, M. Galimand, L. Rahalison, S. Chanteau, P. Courvalin, and E. Carniel. 2001. Transferable plasmid-mediated resistance to streptomycin in a clinical isolate of Yersinia pestis. Emerging Infectious Diseases 7(1):43-48. Hall, F. G., G. Collatz, S. Los, E. Brown de Colstoun, and D. Landis, eds. 2005. ISLSCP Initiative II. DVD/CD-ROM.ï¿½ Hinnebusch, B. J., M.-L. Rosso, T. G. Schwan, and E. Carniel. 2002. High-frequency conjugative transfer of antibiotic resistance genes to Yersinia pestis in the flea midgut. Molecular Microbiol- ogy 46(2):349-354. Hotez, P. J., D. H. Molyneux, A. Fenwick, E. Ottesen, S. Ehrlich Sachs, and J. D. Sachs. 2006. Incor- porating a rapid-impact package for neglected tropical diseases with programs for HIV/AIDS, tuberculosis, and malaria. PLoS Medicine 3(5):e102. Huntington, T. G. 2006. Evidence for intensification of the global water cycle: review and synthesis. Journal of Hydrology 319(1-4):83-95. Inglesby, T. V., D. T. Dennis, D. A. Henderson, J. G. Barlett, M. S. Ascher, E. Eitzen, A. D. Fine, A. M. Friedlander, J. Hauer, J. F. Koerner, M. Layton, J. McDade, M. T. Osterholm, T. OâToole, G. Parker, T. M. Perl, P. K. Russell, M. Schoch-Spana, and K. Tonat. 2000. Plague as a biologi- cal weapon. Journal of the American Medical Association 283(17):2281-2290. IPCC (Intergovernmental Panel on Climate Change). 2007. Climate change 2007: impacts, adapta- tion, and vulnerability. Contribution of Working Group II to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press. Chapter 8. Kausrud, K., H. Viljugrein, A. Frigessi, M. Begon, S. Davis, H. Leirs, V. Dubyanskiy, and N. C. Stenseth. 2007. Climatically driven synchrony of gerbil populations allows large-scale plague outbreaks. Proceedings: Biological Sciences 274(1621):1963-1969. Kausrud, K. L., H. Viljugrein, A. Frigessi, M. Begon, S. Davis, H. Leirs, T. Ben Ari, and N. C. Stenseth. 2008. The epidemiological history of plague in Central Asia: a paleoclimatic modelling study Proceedings of the National Academy of Sciences (in review). Koirala, J. 2006. Plague: disease, management, and recognition of act of terrorism. Infectious Disease Clinics of North America 20(2): viii, 273-287.
172 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Laudisoit, A., H. Leirs, R. H. Makundi, S. Van Dongen, S. Davis, S. Neerinckx, J. Deckers, and R. Libois. 2007. Plague and the human flea, Tanzania. Emerging Infectious Diseases 13(5):687-693. Los, S., G. Collatz, P. Sellers, C. MalmstrÃ¶m, N. Pollack, R. Defries, L. Bounoua, M. Parris, C. Tucker, and D. Dazlich. 2000. A global 9-year biophysical land surface data set from NOAA AVHRR data. Journal of Hydrometeorology 1:183-199. Mudur, G. 1995. Indiaâs pneumonic plague outbreak continues to baffle. British Medical Journal 311(7007):706. Park, S., K. S. Chan, H. Viljugrein, L. Nekrassova, B. Suleimenov, V. S. Ageyev, N. L. Klassovskiy, S. B. Pole, and N. C. Stenseth. 2007. Statistical analysis of the dynamics of antibody loss to a disease-causing agent: plague in natural populations of great gerbils as an example. Journal of the Royal Society Interface 4(12):57-64. Parkhill, J., B. W. Wren, N. R. Thomson, R. W. Titball, M. T. G. Holden, M. B. Prentice, M. Sebai- hia, K. D. James, C. Churcher, K. L. Mungall, S. Baker, D. Basham, S. D. Bentley, K. Brooks, A. M. Cerdeno-Tarraga, T. Chillingworth, A. Cronin, R. M. Davies, and P. Davis. 2001. Genome sequence of Yersinia pestis, the causative agent of plague. Nature 413(6855):523-527. Parmenter, R. R., E. P. Yadav, C. A. Parmenter, P. Ettestad, and K. L. Gage. 1999. Incidence of plague associated with increased winter-spring precipitation in New Mexico. American Journal of Tropical Medicine and Hygiene 61(5):814-821. Pettorelli, N., J. O. Vik, A. Mysterud, J.-M. Gaillard, C. J. Tucker, and N. C. Stenseth. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20(9):503-510. Raoult, D., and G. Aboudharam. 2000. Molecular identification by âsuicide PCRâ of Yersinia pes- tis as the agent of medieval Black Death. Proceedings of the National Academy of Sciences 97(23):12800-12803. Samia, N. I., K.-S. Chan, and N. C. Stenseth. 2007. A generalized threshold mixed model for ana- lyzing nonnormal nonlinear time series, with application to plague in Kazakhstan. Biometrika 94(1):101-118. Schrag, S. J., and P. Wiener. ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ 1995. Emerging infectious diseases: what are the relative roles of ecology and evolution? Trends in Ecology and Evolution 10(8):319-324. Scott, S., and C. J. Duncan. 2001. Biology of plagues: evidence from historical populations. Cam- bridge, UK: Cambridge University Press. Stenseth, N. C. 1999. Population cycles in voles and lemmings: density dependence and phase de- pendence in a stochastic world. Oikos 87(3):427-460. Stenseth, N. C., A. Mysterud, G. Ottersen, J. W. Hurrell, C. Kung-Sik, and M. Lima. 2002. Ecological effects of climate fluctuations. Science 297(5585):1292-1296. Stenseth, N. C., N. I. Samia, H. Viljugrein, K. L. Kausrud, M. Begon, S. Davis, H. Leirs, V. M. Dubyanskiy, J. Esper, V. S. Ageyev, N. L. Klassovskiy, S. B. Pole, and C. Kung-Sik. 2006. Plague dynamics are driven by climate variation. Proceedings of the National Academy of Sciences 103(35):13110-13115. Stenseth, N. C., B. B. Atshabar, M. Begon, S. R. Belmain, E. Bertherat, E. Carniel, K. L. Gage, H. Leirs, and L. Rahalison. 2008. Plague: past, present, and future. PLoS Medicine 5(1):e3. Treydte, K. S., G. H. Schleser, G. Helle, D. C. Frank, M. Winiger, G. H. Haug, and J. Esper. 2006. The twentieth century was the wettest period in northern Pakistan over the past millennium. Nature 440(7088):1179-1182. Twigg, G. 1984. The Black Death: a biological reappraisal. London, UK: Batsform Academic and Educational. WHO (World Health Organization). 2003. Plague, Algeria. Weekly Epidemiological Record 78(29):253. âââ. 2005. Plague. Weekly Epidemiological Record 80(15):138-140. Yersin, A. 1894. La peste bubonique Ã Hong-Kong. Annales de lâInstitut Pasteur 8:662-667.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 173 Zhang, Z., Z. Li, Y. Tao, M. Chen, X. Wen, L. Xu, H. Tian, and N. C. Stenseth. 2007. Relationship ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ between increase rate of human plague in China and global climate index as revealed by cross- spectral analysis and cross-wavelet analysis. Integrative Zoology 2(3):144-153. Ziegler, P. 1969. The Black Death. Wolfeboro Falls, NH: Alan Sutton Publishing Inc. Garrett References Anagnostakis, S. L. 2000. Revitalization of the majestic chestnut: chestnut blight disease. APSnet, http://www.apsnet.org/online/feature/chestnut/ (accessed March 28, 2008). Anderson, P. K., A. A. Cunningham, N. G. Patel, F. J. Morales, P. R. Epstein, and P. Daszak. 2004. Emerging infectious diseases of plants: pathogen pollution, climate change and agrotechnology drivers. Trends in Ecology and Evolution 19(10):535-544. Bai, G., and G. Shaner. 2004. Management and resistance in wheat and barley to Fusarium head blight. Annual Review of Phytopathology 42:135-161. Bergot, M., E. Cloppet, V. PÃ©rarnaud, M. DÃ©quÃ©, B. MarÃ§ais, and M.-L. Desprez-Loustau. 2004. Simulations of potential range expansion of oak disease caused by Phytophthora cinnamomi under climate change. Global Change Biology 10:1539-1552. Brasier, C. M. 2001. Rapid evolution of introduced plant pathogens via interspecific hybridization. BioScience 51(2):123-133. Burdon, J. J., P. H. Thrall, and L. Ericson. 2006. The current and future dynamics of disease in plant communities. Annual Review of Phytopathology 44:19-39. Chakraborty, S., A. V. Tiedemann, and P. S. Teng. 2000. Climate change: potential impact on plant diseases. Environmental Pollution 108(3):317-326. Cheatham, M. R., M. N. Rouse, P. D. Esker, S. Ignacio, W. Pradel, R. Raymundo, A. H. Sparks, G. A. Forbes, T. R. Gordon, and K. A. Garrett. Beyond yield: plant disease in the context of ecosystem services. Phytopathology (in revision). Cline, W. R. 2007. Global warming and agriculture: impact estimates by country. Washington, DC: Center for Global Development and Peterson Institute for International Economics. Coakley, S. M., H. Scherm, and S. Chakraborty. 1999. Climate change and plant disease management. Annual Review of Phytopathology 37:399-426. Daily, G. C., ed. 1997. Natureâs services: societal dependence on natural ecosystems. Washington, DC: Island Press. De Wolf, E. D., and S. A. Isard. 2007. Disease cycle approach to plant disease prediction. Annual Review of Phytopathology 45:203-220. Desprez-Loustau, M.-L., C. Robin, G. Reynaud, M. DÃ©quÃ©, V. Badeau, D. Piou, C. Husson, and B. MarÃ§ais. 2007. Simulating the effects of a climate-change scenario on the geographical range ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ and activity of forest-pathogenic fungi. Canadian Journal of Plant Pathology 29:101-120. Eviner, V. T., and G. E. Likens. 2008. Effects of pathogens on terrestrial ecosystem function. In Infec- tious disease ecology: effects of ecosystems on disease and of disease on ecosystems, edited by R. Ostfeld, F. Keesing, and V. Eviner. Princeton, NJ: Princeton University Press. Pp. 260-283. Fletcher, J., and J. P. Stack. 2007. Agricultural biosecurity: threats and impacts for plant pathogens. In Global infectious disease surveillance and detection. Washington, DC: The National Academies Press. Pp. 86-94. Frank, E. E. 2007. Rust and drought effects on gene expression and phytohormone concentration in big bluestem. M.S. Thesis, Kansas State University, Manhattan, Kansas. Garrett, K. A., and R. L. Bowden. 2002. An Allee effect reduces the invasive potential of Tilletia indica. Phytopathology 92:1152-1159. Garrett, K. A., S. P. Dendy, E. E. Frank, M. N. Rouse, and S. E. Travers. 2006. Climate change effects on plant disease: genomes to ecosystems. Annual Review of Phytopathology 44:489-509.
174 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Garrett, K. A., L. N. ZÃºÃ±iga, E. Roncal, G. A. Forbes, C. C. Mundt, Z. Su, and R. J. Nelson. Intra- specific functional diversity in hosts and its effect on disease risk across a climatic gradient. Ecological Applications (in revision). He, Z. L., T. J. Gentry, C. W. Schadt, L. Y. Wu, J. Liebich, S. C. Chong, Z. J. Huang, W. M. Wu, B. H. Gu, P. Jardine, C. Criddle, and J. Zhou. 2007. GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. ISME Journal 1:67-77. Hijmans, R. J., G. A. Forbes, and T. S. Walker. 2000. Estimating the global severity of potato late blight with GIS-linked disease forecast models. Plant Pathology 49(6):697-705. Isard, S. A., S. H. Gage, P. Comtois, and J. M. Russo. 2005. Principles of the atmospheric pathway for invasive species applied to soybean rust. BioScience 55(10):851-861. Jeger, M. J., and M. Pautasso. 2008. Plant disease and global changeâthe importance of long-term data sets. New Phytologist 177(1):8-11. Johnson, R. C. 2008. Gene banks pay big dividends to agriculture, the environment, and human welfare. PLoS Biology 6(6):e148. Lobell, D. B., M. B. Burke, C. Tebaldi, M. D. Mastrandrea, W. P. Falcon, and R. L. Naylor. 2008. Priori- tizing climate change adaptation needs for food security in 2030. Science 319(5863):607-610. Madden, L., and M. Wheelis. 2003. The threat of plant pathogens as weapons against U.S. crops. Annual Review of Phytopathology 41:155-176. Magarey, R. D., G. A. Fowler, D. M. Borchert, T. B. Sutton, and M. Colunga-Garcia. 2007. NAPPFAST: an Internet system for the weather-based mapping of plant pathogens. Plant Disease 91(4):336-345. Margosian, M. L., K. A. Garrett, J. M. S. Hutchinson, and K. A. With. Connectivity of the American agricultural landscape: assessing the national risk of crop pest and disease spread. BioScience (in revision). McDonald, B. A., and C. Linde. 2002. Pathogen population genetics, evolutionary potential, and durable resistance. Annual Review of Phytopathology 40:349-379. Mitchell, C. E., P. B. Reich, D. Tilman, and J. V. Groth. 2003. Effects of elevated CO 2, nitrogen deposition, and decreased species diversity on foliar fungal plant disease. Global Change Biol- ogy 9(3):438-451. Nelson, R. J., R. L. Naylor, and M. M. Jahn. 2004. The role of genomics research in improvement of âorphanâ crops. Crop Science 44:1901-1904. Oerke, E. C., H. W. Dehne, F. SchÃ¶nbeck, and A. Weber. 1994. Crop production and crop protection. Amsterdam, The Netherlands: Elsevier Science, B.V. Parker, I. M., and G. S. Gilbert. 2004. The evolutionary ecology of novel plant-pathogen interactions. Annual Review of Ecology, Evolution and Systematics 35:675-700. Patt, A., P. Suarez, and C. Gwata. 2005. Effects of seasonal climate forecasts and participatory workshops among subsistence farmers in Zimbabwe. Proceedings of the National Academy of Sciences 102(35):12623-12628. Peng, S., J. Huang. J. E. Sheehy, R. C. Laza, R. M. Visperas, X. H. Zhong, G. S. Centeno, G. S. Khush, and K. G. Cassman. 2004. Rice yields decline with higher night temperature from global warm- ing. Proceedings of the National Academy of Sciences 101(27):9971-9975. 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. 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. Redak, R. A., A. H. Purcell, J. R. S. Lopes, M. J. Blua, R. F. Mizell, and P. C. Andersen. 2004. The biology of xylem fluid-feeding insect vectors of Xylella fastidiosa and their relation to disease epidemiology. Annual Review of Entomology 49:243-270. Riesenfeld, C. S., P. D. Schloss, and J. Handelsman. 2004. Metagenomics: genomic analysis of mi- crobial communities. Annual Review of Genetics 38:525-552.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 175 Rizzo, D. M., M. Garbelotto, and E. A. Hansen. 2005. Phytophthora ramorum: integrative research and management of an emerging pathogen in California and Oregon forests. Annual Review of Phytopathology 43:309-335. Roesch, L. F., R. R. Fulthorpe, A. Riva, G. Casella, A. K. M. Hadwin, A. D. Kent, S. H. Daroub, F. A. O. Camargo, W. G. Farmerie, and E. W. Triplett. 2007. Pyrosequencing enumerates and contrasts soil microbial diversity. ISME Journal 1:283-290. Rouse, M. N. 2007. Diversity of a disease resistance gene homolog in Andropogon gerardii (Poaceae) is correlated with precipitation. M.S. Thesis, Kansas State University, Manhattan, Kansas. Roy, B. A., S. Gusewell, and J. Harte. 2004. Response of plant pathogens and herbivores to a warming experiment. Ecology 85:2570-2571. Rush, C. M., R. Riemenschneider, J. M. Stein, T. Boratynski, R. L. Bowden, and M. H. Royer. 2005. Status of karnal bunt of wheat in the United States 1996-2004. Plant Disease 89(3):212-223. Stack, J. P., and J. Fletcher. 2007. Plant biosecurity infrastructure for disease surveillance and diag- nostics. In Global infectious disease surveillance and detection. Washington, DC: The National Academies Press. Pp. 95-102. Stokstad, E. 2007. Plant pathology: deadly wheat fungus threatens worldâs bread baskets. Science 315(5820):1786-1787. Travers, S. E., M. D. Smith, J. Bai, S. H. Hulbert, J. E. Leach, P. S. Schnable, A. K. Knapp, G. A. Milliken, P. A. Fay, A. Saleh, and K. A. Garrett. 2007. Ecological genomics: making the leap from model systems in the lab to native populations in the field. Frontiers in Ecology and the Environment 5:19-24. UNEP (United Nations Environment Programme). 2004. Childhood pesticide poisoning: information for advocacy and action. ChÃ¢telaine, Switzerland: United Nations Environment Programme. Villanueva, H., R. Raymundo, H. Juarez, W. Perez, and G. Forbes. In preparation. The article and journal titles were not available at the time of publication. Waldrop, M. P., and M. K. Firestone. 2006. Response of microbial community composition and func- tion to soil climate change. Microbial Ecology 52:716-724. Webb, K. M., J. Bai, I. OÃ±a, K. A. Garrett, T. W. Mew, C. M. Vera Cruz, and J. E. Leach. In prepara- tion. The article and journal titles were not available at the time of publication. Widmark, A.-K., B. Andersson, A. Cassel-Lundhagen, M. SandstrÃ¶m, and J. E. Yuen. 2007. Phy- tophthora infestans in a single field in southwest Sweden early in spring: symptoms, spatial distribution and genotypic variation. Plant Pathology 56:573-579. Woods, A., K. D. Coates, and A. Hamann. 2005. Is an unprecedented Dothistroma needle blight epidemic related to climate change? BioScience 55(9):761-769. Zhu, Y., H. Chen, J. Fan, Y. Wang, Y. Li, J. Chen, J. Fan, S. Yang, L. Hu, H. Leung, T. W. Mew, P. S. Teng, Z. Wang, and C. C. Mundt. 2000. Genetic diversity and disease control in rice. Nature 406(6797):718-722. Zhu, Y., H. Fang, Y. Wang, J. X. Fan, S. Yang, T. W. Mew, and C. Mundt. 2005. Panicle blast and canopy moisture in rice cultivar mixtures. Phytopathology 95(4):433-438. Parkinson References AMAP (Arctic Monitoring and Assessment Programme). 2003. AMAP Assessment 2002: human health in the Arctic. Oslo, Norway: Arctic Monitoring and Assessment Program. Arctic Council. 2005. Arctic climate impact assessment scientific report. New York: Cambridge University Press. Pp. 863-960. Baggett, H. C., T. W. Hennessy, R. Leman, C. Hamlin, D. Bruden, and A. Reasonover. 2003. An outbreak of community-onset methicillin resistant Staphylococcus aureus skin infections in southwestern Alaska. Infection Control and Hospital Epidemiology 24(6):397-402.
176 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Baggett, H. C., T. W. Hennessy, K. Rudolph, D. Bruden, A. Reasonover, and A. J. Parkinson. 2004. Community-onset methicillin-resistant Staphylococcus aureus, associated with antibiotic use and cytotoxin Panton-Valentine leukocidin during a furnunculosis outbreak in rural Alaska. Journal of Infectious Diseases 189(9):1565-1573. Bjerregaard, P., K. T. Young, E. Dewailly, and S. O. E. Ebbesson. 2004. Indigenous health in the Arctic: an overview of the circumpolar Inuit population. Scandinavian Journal of Public Health 32(5):390-395. Borgerson, S. G. 2008. Arctic meltdown: the economic and security implications of global warming. Foreign Affairs 87(2):63-77. Bruce, M. G., S. L. Deeks, T. Zulz, D. Bruden, C. Navarro, M. Lovegren, L. Jette, K. Kristinsson, G. Sigmundsdottir, K. Brinklov Jensen, O. Lovoll, J. P. Nuorti, E. Herva, A. Nystedt, A. Sjostedt, A. Koch, T. W. Hennessy, and A. J. Parkinson. 2008a. International Circumpolar Surveillance for invasive pneumococcal disease, 1999-2005. Emerging Infectious Diseases 14(1):25-33. Bruce, M. G., S. L. Deeks, T. Zulz, C. Navarro, C. Palacios, C. Case, C. Hemsley, T. W. Hennessy, A. Corriveau, B. Larke, I. Sobel, M. Lovegren, C. DeByle, R. Tsang, and A. J. Parkinson. 2008b. Epidemiology of Haemophilus influenzae serotype A, North American Arctic 2000-2005. Emerging Infectious Diseases 14(1):48-55. Bulkow, L. R., R. J. Singleton, R. A. Karron, L. H. Harrisson, and Alaska RSV Study Group. 2002. Risk factors for severe respiratory syncytial virus infection among Alaska Native children. Pediatrics 109(2):210-216. Castrodale, L. J., M. Beller, J. F. Wilson, P. M. Schantz, D. P. McManus, L. H. Zhang, F. G. Fallico, and F. D. Sacco. 2002. Two atypical cases of cystic echinococcosis (Echinococcus granulosis) in Alaska 1999. American Journal of Tropical Medicine and Hygiene 66(3):325-327. CDC (Centers for Disease Control and Prevention). 2001. Botulism outbreak associated with eating fermented foodâAlaska. Morbidity and Mortality Weekly Report 50(32):680-682. Christensen, J., P. Poulsen, and K. Ladefoged. 2004. Invasive pneumococcal disease in Greenland. Scandinavian Journal of Infectious Diseases 36(5):325-329. Curtis, T., S. Kvernmo, and P. Bjerregaad. 2005. Changing living conditions, life style and health. International Journal of Circumpolar Health 64(5):442-450. Dawar, M., L. Moody, J. D. Martin, C. Fung, J. Isaac-Renton, and D. M. Patrick. 2002. Two outbreaks of botulism associated with fermented salmon roeâBritish Columbia, August 2001. Canadian Communicable Disease Reports 28(6):45-49. Degani, N., C. Navarro, S. Deeks, and M. Lovegren. 2008. Invasive bacterial diseases in northern Canada. Emerging Infectious Diseases 14(1):34-40. Frumkin, H., J. Hess, G. Luber, J. Maliay, and M. McGeehin. 2008. Climate change: the public health response. American Journal of Public Health 98(3):435-445. Furgal, C. 2005. Monitoring as a community response for climate change and health. International Journal of Circumpolar Health 64(5):440-441. Gessner, B. D., N. S. Weiss, and C. M. Nolan. 1998. Risk factors for pediatric tuberculosis infec- ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ tion and disease after household exposure to adult index cases in Alaska. Jornal de Pediatria 132(3):509-513. Haines, A., R. S. Kovars, D. Campbell-Lendrun, and C. Corvalan. 2006. Climate change and human health: impacts, vulnerability, and mitigation. Lancet 360(9528):2101-2109. Hennessy, T.,ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ T. Ritter, R. C. Holman, D. L. Bruden, K. L. Yorita, L. Bulkow, J. E. Cheek, R. J. Singleton, and J. Smith. 2008. Relationship between in-home water service and the risk ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ of respitatory tract, skin, and gastrointestinal tract infections among Alaska Natives. American Journal of Public Health 98(5):1-8. Hess, J., J. Malilay, and A. J. Parkinson. In press. Climate change: the importance of place and places of special risk. American Journal of Preventive Medicine.
CLIMATE, ECOLOGY, AND INFECTIOUS DISEASE 177 Hoberg, E. P., L. Polley, E. J. Jenins, S. J. Kutz, A. M. Vetch, and B. T. Elkin. 2008. Integrated ap- proaches and empiric models for investigation of parasitic diseases in northern wildlife. Emerg- ing Infectious Diseases 14(1):10-17. Holts, D. W., C. Hanns, T. O. OâHara, J. Burek, and R. Franz. 2005. New distribution records of Echinococcus multilocularis in the brown lemming from Barrow, Alaska. Journal of Wildlife Diseases 41(1):257-259. IOM (Institute of Medicine). 1992. Emerging infections: microbial threats to health in the United States. Washington, DC: National Academy Press. âââ. 2003. Microbial threats to health: emergence, detection, and response. Washington, DC: The National Academies Press. Karron, R. A., R. J. Singleton, L. Bulkow, A. J. Parkinson, D. Kruse, I. DeSmet, C. Indorf, K. M. Petersen, D. Leombruno, D. Hurlburt, M. Santosham, and L. H. Harrison. 1999. Severe respiratory syncytial virus disease in Alaska Native children. Journal of Infectious Diseases 180(1):41-49. Kurkela, S., O. RÃ¤tti, E. Huhtamo, N. Y. UzcÃ¡tegui, P. J. Nuorti, J. Laakkonen, T. Manni, P. Helle, A. Vaheri, and O. Vapalahti. 2008. Sindbis virus infection in resident birds, migratory birds, and humans, Finland. Emerging Infectious Diseases 14(1):41-47. Leclair, D., J. W. Austin, J. Faber, B. Cadieux, and B. Blanchfield. 2004. Toxicity of aged seal meat challenged with Clostridium botulinum type E. Federal Food Safety and Nutrition Research Meeting, Ottawa, Ontario, October 4-5. Lindgren, E., and R. Gustafson. 2001. Tick-borne encephalitis in Sweden and climate change. Lancet 358(9275):16-18. McLaughlin, J. B., A. Depoala, C. A. Bopp, K. A. Martinek, N. Napolilli, C. Allison, S. Murry, E. C. Thompson, M. M. Bird, and T. P. Middaugh. 2005. Emergence of Vibrio parahaemolyticus gastroenteritis associated with consumption of Alaskan oysters and its global implications. New England Journal of Medicine 353(14):1463-1470. McMahon, B. J., M. G. Bruce, T. W. Hennessy, D. L. Bruden, F. Sacco, H. Peters, D. A. Hurlburt, J. M. Morris, A. L. Reasonover, G. Dailde, D. E. Berg, and A. J. Parkinson. 2007. Reinfection after successful eradication of Helicobacter pyloriâa 2 year prospective study in Alaska Natives. Alimentary Pharmacology and Therapeutics 23(8):1215-1223. Meyer, A., K. Ladefoged, P. Poulsen, and A. Kock. 2008. Population-based survey of invasive bacte- rial diseases, Greenland, 1995-2004. Emerging Infectious Diseases 14(1):76-79. Nayha, S. 2005. Environmental temperature and mortality. International Journal of Circumpolar Health 64(5):451-458. Netesov, S. V., and L. J. Conrad. 2001. Emerging infectious diseases in Russia 1990-1999. Emerging Infectious Diseases 7(1):1-5. Nguyen, D., J. F. Proulx, J. Westley, L. Thibert, S. Dery, and M. A. Behr. 2003. Tuberculosis in the Inuit community of Quebec, Canada. American Journal of Respiratory and Critical Care Medicine 168(11):1353-1357. Ogden, N. H., A. Maarouf, I. K. Barker, M. Bigras-Poulin, L. R. Lindsay, M. G. Morshed, C. J. OâCallaghan, F. Ramay, D. Waltner-Twews, and D. F. Charron. 2005. Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada. International Journal of Parasitology 36(1):63-70. Orr, P., B. Lorencz, R. Brown, R. Kielly, B. Tan, D. Holton, H. Clugstone, L. Lugtig, C. Pim, S. McDonald, G. Hammond, M. Moffatt, J. Spika, D. Manuel, W. Winther, D. Milley, H. Lior, and N. Sinuff. 1994. An outbreak of diarrhea due to verotoxin-producing Esherichia coli in the Canadian Northwest Territories. Scandinavian Journal of Infectious Diseases 26(6):675-684. Parkinson, A. J., and J. C. Butler. 2005. Potential impact of climate change on infectious disease emergence in the Arctic. International Journal of Circumpolar Health 64(5):478-486. Parkinson, A. J., M. Bruce, and T. Zultz. 2008. International circumpolar surveillance, and arctic network for surveillance of infectious diseases. Emerging Infectious Diseases 14(1):18-24.
178 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Pettersson, L., J. Boman, P. Juto, M. Evander, and C. Ahlm. 2008. Outbreak of Puumala virus infec- tion, Sweden. Emerging Infectious Diseases 14(5):808-810. Proulx, J. F., V. Milor-Roy, and J. Austin. 1997. Four outbreaks of botulism in Ungava Bay Nunavik, Quebec. Canadian Communicable Disease Report 23(4):30-32. Rausch, R. 2003. Cystic echinococcosis in the Arctic and sub-Arctic. Parasitology 127(suppl): S73-S85. Revich, B. A. 2008. Climate change alters human health in Russia. Studies on Russian Economic Development 19(3):311-317. Richter-Menge, J., S. Nghiem, D. Perovich, and I. Rigor. 2008. Sea ice cover. In Arctic report card, 2007, www.arctic.noaa.gov//reportcard/seaice.html (accessed April 4, 2008). Rudolph, K. M., M. J. Crain, A. J. Parkinson, and M. C. Roberts. 1999. Characterization of a multidrug- resistant clone of invasive Streptococcus pneumoniae serotype 6B in Alaska by using pulsed- field gel electrophoresis and PspA typing. Journal of Infectious Diseases 180(5):1577-1583. Rudolph, K. M., A. J. Parkinson, A. L. Reasonover, L. R. Bulkow, D. J. Parks, and J. C. Butler. 2000. Serotype distribution and antimicrobial resistance patterns of invasive isolates of Streptococcus pneumoniae: Alaska 1991-1998. Journal of Infectious Diseases 182(2):490-496. Schweiger, A., R. W. Ammann, D. Candinas, P. A. Clavien, J. Eckert, B. Gottstein, N. Halkic, B. Muellhaupt, J. Reichen, P. E. Tarr, P. R. Torgerson, and P. Deplazes. 2007. Human al- veolar echinococcus after fox population increase Switzerland. Emerging Infectious Diseases 13(6):878-882. Singleton, R., L. Hammitt, T. Hennessy, L. Bulkow, D. DeByle, A. Parkinson, T. E. Cottle, H. Peters, and J. C. Butler. 2006. The Alaska Haemophilus influenzae type b experience: lessons in control- ling a vaccine-preventable disease. Pediatrics 118(2):421-429. SkarphÃ©dinsson, S., M. Jensen, and K. Kristiansen. ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ 2005. Survey of tickborne infections in Denmark. Emerging Infectious Diseases 11(7):1055-1061. Sobel, J., N. Tucker, A. Sulka, J. McMaughlin, and S. Maslanka. 2004. Foodborne botulism in the United States, 1990-2000. Emerging Infectious Diseases 10(9):1606-1611. SÃ¸borg, C., B. SÃ¸borg, S. Pouelsen, G. Pallisgaard, S. Thybo, and J. Bauer. 2001. Doubling of tu- berculosis incidence in Greenland over an 8 year period (1990-1997). International Journal of Tuberculosis and Lung Disease 5(3):257-265. SÃ¸rensen, H. C., K. AlbÃ¸ge, and J. C. Misfeldt. 1993. Botulism in Ammassalik. Ugeskrift for Laeger 115(2):108-109. Stefansson Arctic Institute. 2004. Arctic human development report. Akureyri, Iceland: Stefansson Arctic Institute. Van Caeseele, P., A. Macaulay, P. Orr, F. Aoki, and B. Martin. 2001. Rapid pharmacotherapeutic inter- vention for an influenza A outbreak in the Canadian Arctic: lessons from Sanikiluaq experience. International Journal of Circumpolar Health 60(4):640-648. Wainwright, R. B., W. L. Heyward, J. P. Middaugh, C. L. Hatheway, A. P. Harpster, and T. R. Bender. 1988. Foodborne botulism in Alaska 1947-1985: epidemiology and clinical findings. Journal of Infectious Diseases 157(6):1158-1162. Walters, L. L., S. J. Tyrrell, and R. E. Shope. 1999. Seroepidemiology of California and Bunyamwera (Bunyaviridae) serogroup virus infections in native populations of Alaska. American Journal of Tropical Medicine and Hygiene 60(5):806-821. Warren, J. A., J. E. Berner, and T. Curtis. 2005. Climate change and human health: infrastructure impacts to small remote communities in the North. International Journal of Circumpolar Health 64(5):487-497. Young, T. K. 2008. Circumpolar health indicators: sources, data, and maps. Circumpolar Health Supplements 3:55-78.