3
Historical, Scientific, and Technological Approaches to Studying the Climate-Disease Connection

OVERVIEW

A variety of methods are employed to identify, measure, evaluate, and predict the direct and indirect effects of climate change on infectious diseases. As illustrated in the contributions to this chapter, these include the following:

  • Analyses of historical records to discern long-term or ancient patterns of climate and infectious disease

  • Monitoring programs that track disease in wild animals, which are especially sensitive environmental sentinels

  • Comparisons of environmental measurements obtained from satellite imagery with epidemiological data

  • Climate-driven predictive models of infectious disease transmission

Each of these approaches contributes to an expanding interdisciplinary effort to understand the influence of climate change and extreme weather events on infectious disease distribution and transmission dynamics.

Historical analysis provides a perspective on climate and infectious disease far more sweeping than can be obtained from scientific monitoring, as demonstrated in this chapter’s first paper, which chronicles the association between drought and epidemic disease and its influence on Mexican civilizations over the past millennium. Searching the historical record of the Valley of Mexico for evidence of famines and epidemics, speaker Rodolfo Acuña-Soto of the Universidad Nacional Autónoma de México, and coauthors identified several drought-associated epidemics of hemorrhagic fevers that had swept the region,



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3 Historical, Scientific, and Technological Approaches to Studying the Climate-Disease Connection OVERVIEW A variety of methods are employed to identify, measure, evaluate, and predict the direct and indirect effects of climate change on infectious diseases. As illus- trated in the contributions to this chapter, these include the following: • Analyses of historical records to discern long-term or ancient patterns of climate and infectious disease • Monitoring programs that track disease in wild animals, which are espe- cially sensitive environmental sentinels • Comparisons of environmental measurements obtained from satellite imagery with epidemiological data • Climate-driven predictive models of infectious disease transmission Each of these approaches contributes to an expanding interdisciplinary effort to understand the influence of climate change and extreme weather events on infectious disease distribution and transmission dynamics. Historical analysis provides a perspective on climate and infectious disease far more sweeping than can be obtained from scientific monitoring, as demon- strated in this chapter’s first paper, which chronicles the association between drought and epidemic disease and its influence on Mexican civilizations over the past millennium. Searching the historical record of the Valley of Mexico for evidence of famines and epidemics, speaker Rodolfo Acuña-Soto of the Universidad Nacional Autónoma de México, and coauthors identified several drought-associated epidemics of hemorrhagic fevers that had swept the region, 7

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0 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS causing massive mortality. Among these, the authors describe four especially destructive epidemics that appear to have killed between 20 and 90 percent of the entire population, leading to societal collapse: the epidemics of 1003-1011, 1545-1548, 1576-1578, and 1736-1737. The authors also compare circumstances in contemporary Mexico with those associated with apparent past episodes of infectious disease emergence, when increasing human connectivity (roads then, globalization today), and the emergence of new pathogens transmitted by aerosols (smallpox and measles in the past, severe acute respiratory syndrome [SARS] and influenza today), proved to be a very dangerous combination. Emerging infectious diseases of wildlife arise when the delicate balance of host, pathogen, and environment is disturbed. Therefore, these events represent a critical target for infectious disease monitoring efforts of all sorts, including those that seek to track the influence of climate change, according to speaker William Karesh of the Wildlife Conservation Society. In the chapter’s second paper, he and coauthors provide several examples of studies that illustrate the direct and indirect influences of climate on infectious diseases of wildlife. They make the case that such interactions can serve as the basis for monitoring the ecological effects of climate change on emergent diseases that threaten not only wildlife, but also livestock and humans, because wild animals often serve as reservoirs for microbes that may cause pathogenic diseases in humans; these microbes are not necessarily pathogenic in their animal hosts. Moreover, the authors note, wild animals offer a number of advantages for disease monitoring programs: their comparatively short generation times reflect environmental changes more quickly than do humans; the great variety of wild species offers an equally wide range of life histories for the observation of disease dynamics; and they provide sensitive sentinels for changes in the environments to which they are specifically adapted. As discussed by Chretien and coauthors in Chapter 2 and as first described in Linthicum et al. (1999), efforts to predict risk for Rift Valley fever (RVF) demon- strated that trends in environmental variables detected from satellite imagery can be compared with epidemiological data to reveal relationships between climate and infectious disease transmission and geographic distribution. In his workshop presentation, speaker Compton Tucker of the National Aeronautics and Space Administration (NASA)—who coauthored both of the previously mentioned papers—described how remote sensing data are collected and analyzed, and pre- sented two additional examples of the use of this tool in examining links between climate and infectious disease. The first involved a search for significant environmental factors common to sporadic outbreaks of Ebola hemorrhagic fever (EHF). Ebola virus also affects nonhuman primates, which have been implicated as the source of several—but not all—human outbreaks through contact with the meat of infected apes (Pinzon et al., 2004). Tucker and colleagues chose to investigate the possibility that Ebola outbreaks occur independently of human cases, in nonhuman primates, and to

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 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION identify environmental factors that precipitate these outbreaks, which can then spread to humans. Analyzing satellite data—the monthly Normalized Difference Vegetation Index (NDVI), a proxy for precipitation—that had been collected continuously in tropical Africa since 1981, Tucker and coworkers found that the majority of documented EHF outbreaks (in humans) occurred toward the end of rainy seasons, when a sharply drier period was followed by a sudden return to very wet conditions. They hypothesize that these apparent “trigger events” enhance viral transmission from reservoir species—which remain unknown 1—to nonhuman primates and humans. Today, satellite data from eastern equatorial Africa are screened routinely for the Ebola-triggering weather pattern, Tucker said. The results guide targeted testing for the virus in local primates, which may provide an early warning of future human outbreaks. Tucker also described the use of satellite imagery to investigate an unusual outbreak of RVF in southwestern Arabia, the first ever recorded there. Records of a satellite-derived index of photosynthetic capacity, the NDVI, showed that significant precipitation had fallen in the region prior to the outbreak and that the RVF outbreak was thus due to natural causes. The origin of the outbreak has since been attributed to infected cattle that were imported into southwestern Arabia from the Horn of Africa (Tucker et al., in press). As these examples and others in Chapter 2 illustrate, relatively simple cor- relations between remotely-sensed measurements of climatic variables (e.g., precipitation; sea surface temperature, height) and disease incidence have proven to be useful indicators of risk for a variety of infectious diseases. However, as speaker William Reisen noted, such correlations are not universally applicable and may have to be interpreted in light of other important environmental influ- ences on infectious disease transmission (see also Summary and Assessment section “Predictive Models”). In the chapter’s final paper, Reisen and Christopher Barker (both at the University of California, Davis) describe the design, imple- mentation, and limitations of climate-driven predictive models of mosquito-borne encephalitis transmission used by the State of California to estimate disease risk and inform public health interventions. Under the auspices of this disease surveillance and control program, mos- quito abundance and encephalitis virus activity have been actively monitored for more than 50 years throughout many of California’s diverse biomes and across wide gradients of latitude (north-south) and elevation (east-west). Early in the 1 In a personal communication on June 20, 2008, Dr. William Karesh stated that LeRoy et al. (2005) is probably the best work done to demonstrate (1) the presence of Ebola Zaire strain viral particles or viral fragments in 3 species of fruit bats, and (2) serological evidence of immune response to filovirus in those same species of bats. Earlier work by Swanepoel et al. showed viral shedding with no pathol- ogy for up to 28 days after fruit bats were experimentally infected with Ebola Zaire in a laboratory setting. To date, there is nothing published on live Ebola virus being isolated from naturally occurring, free-ranging bats. That, in addition to showing that those bats can serve to infect other animals, would help determine if one or more species serve as an effective reservoir.

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2 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Human cases Equine cases Amplification Avian infection Mosquito infection Climate Mosquito abundance Time [months] FIGURE 3-1 Sequence of surveillance data collected during seasonal virus amplification. SOURCE: Reisen and Barker (2008). Figure 3-1 also season, before insect and wildlife testing become feasible, climate-based fore- casts inform disease control measures (Figure 3-1). Surveillance activities begin Figure 3-5 in the spring, with the goal of arresting viral amplification and avoiding the need for adult mosquito control. In the case of West Nile virus (WNV), early-season temperature measurements are paramount, because the effects of precipitation on viral transmission have been found to vary among regions (Reisen et al., in press) and vector species (e.g., urban Culex pipiens mosquitoes do well under hot, dry conditions, whereas rural Culex tarsalis do well under wet conditions in many areas). Although these early-season predictions enable response activities (such as equine vaccination, larval mosquito control, and public education) that can reduce the public health consequences of mosquito-borne disease, Reisen and Barker note that the rationale for applying insecticides in advance of an epidemic is not always understood by the public. They also warn that while WNV “provided a wake-up call for public health agencies and clearly delineated the inability of cur- rent control programs to contain an invading, mosquito-borne, zoonosis,” waning of the epidemic has led to a loss of funding for WNV research and surveillance and, more importantly, for more general surveillance and detection programs capable of spotting “the next invading pathogen.”

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 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION DROUGHT, EPIDEMIC DISEASE, AND MASSIVE POPULATION LOSS: 1,000 YEARS OF RECORD IN MExICO Rodolfo Acuña-Soto, M.D., M.Sc., D.Sc.2 Universidad Nacional Autónoma de México David W. Stahle, Ph.D. University of Arkansas Matthew D. Therrell, Ph.D. Southern Illinois University José Villanueva Diaz, Ph.D. Centro Nacional de Investigación Disciplinaria Introduction The Valley of Mexico with its benign climate, rich soil, and once abundant water has been a preferred population center for centuries. Today, with 20 mil- lion inhabitants, Mexico City’s metropolitan area is one of the largest human conglomerates in history (Yu-ping and Heligman, 1994). While this has been the result of constant growth for the last 85 years, history has not always been this benign. Over the past 1,000 years the Valley of Mexico went through three periods of catastrophic population losses (Clavijero, 1945; Cook and Simpson, 1948; Hugh, 1993). Founded only 675 years ago, Mexico City is located in the same region where the once magnificent cities Teotihuacán and Tula collapsed 1,255 and 1,000 years ago, respectively. Similar catastrophic events occurred during the sixteenth cen- tury, when the Valley of Mexico, as well as the whole country, lost 80 to 90 per- cent of its inhabitants due to highly lethal epidemics. During the seventeenth to twentieth centuries, the population again went through several calamitous periods of high mortality, droughts, famines, and epidemics (Gerhard, 1986; León, 1982; Ocaranza, 1933; Therrell et al., 2004; Yu-ping and Heligman, 1994). 2 Corresponding author. Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Edificio “A” de Investigación, 2o. Piso, Facultad de Medicina, Ciudad Universitaria, C.P. 04510, México, D.F. Phone (55) 56 23 23 81; Fax: (55) 56 23 23 82; E-mail: yvonne@ibt.unam.mx. 3Tree-Ring Laboratory, Department of Geosciences, Ozark Hall 113, Fayetteville, AR 72701. 4 Geograpy and Environmental Resources, Carbondale, Illinois. 5 Relación Agua-Suelo-Planta-Atmósfera CENID-RASPA, Km. 6.5 Margen Derecha Canal de Sacramento, C. P. 35140, Gómez Palacio, Durango, México.

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 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS In spite of the importance of this topic, the formal study of famines and epi- demics in Mexico has been primarily descriptive and remains largely incomplete. The aims of this work are to present a chronology of famines and epidemics and to review some of the major events of massive population loss in the Valley of Mexico over the last 1,000 years. For this study, previously published chronologies of epidemics and famines in Mexico were reviewed. This was complemented with an exhaustive multiyear review of epidemiological, environmental, and demographic information available in archives and libraries in Mexico and the United States. The search included chronicles, old medical books, diaries, newspapers, and official documentation. Quantitative data from censuses and burial records were also obtained. In addition, events indicative of social distress, such as special religious acts, urgent govern- ment measures, or local officials asking for help, were recorded. For all documents, priority was given to descriptions written by eye witnesses. Drought was consid- ered as such when firsthand witnesses indicated the absence or drastic reduction of rain, normally associated with crop failure. Information was complemented with data from a previous publication (Therrell et al., 2004). Only materials related to the Valley of Mexico were taken into consideration for this study.6 The Chronology of Famines and Epidemics Over the last 1,500 years, a total of 119 major epidemics and 38 famines were identified (see Table 3-1). Drought was the main cause of 28 (73 percent) famines. The epidemics of smallpox of 1520-1521 and 1538-1539 induced fam- ine by generalized social disruption. Other historic famines were caused by the particularly disastrous combination of summer frost followed by drought. Such was the case of the legendary famine of 1542-1545, when early frost killed all the corn plants in 1542 and was followed by prolonged drought during 1543-1544 when no rain was registered for 20 months. With no new harvest, reserves ran out, creating a very stressful situation that paved the way to a major famine (Therrell et al., 2004). This series of events recurred in 1784-1786, the infamous “year of the hunger” (Cook and Sherburne, 1985). After the Conquest in 1520, famines were recorded with decreasing frequency in the following centuries: 10 in the sixteenth century, 8 in the seventeenth century, and 5 in the eighteenth century; no major famines were recorded during the nineteenth or twentieth centuries. For the 1,500-year period, a total of 119 epidemics were identified (see Table 3-2). Of these, viral diseases caused 55 (46.2 percent) and bacteria were 6 For representative documents, see Acuña, 1982; Anonymous, 1978, 1980a,b, 1981, 1995, 1998; Carmago, 1999; Chimalpahin, 1998, 2001; Cook and Sherburne, 1985; de Alva Ixtlixóchitl, 1975; de Cárdenas, 1945; de Grijalva, 1924; de Lorenzana, 1992; de Obregón, 1988; de Ortega Montañez, 1955; de Torquemada, 1969; Farfan, 1592; Keber, 1995; Lopez de Hinojoso, 1578, 1595; Mendieta, 1997; Sahagún, 1997; Somolinos, 1956.

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 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION TABLE 3-1 Famines in the Valley of Mexico Years Causes Remarks 1 1003-1011 Drought, war Famine, epidemic, high mortality 2 1029-1035 Drought Famine, high mortality 3 1253 Drought Famine, epidemic 4 1332-1335 Drought Famine 5 1382-1385 Floods Famine 6 1403 Locust Famine 7 1430 Drought Famine 8 1434 Drought Famine 9 1446-1456 Locust, floods, frost, snow, drought Famine, probably associated with epidemic of hemorrhagic fever, high mortality 10 1464 Heat waves, strong winds Famine 11 1488 Locust Famine 12 1492 Floods Famine 13 1498-1499 Floods Famine 14 1503-1505 Drought Famine, high mortality 15 1514 Drought Famine 16 1520-1521 War, first smallpox epidemic Famine 17 1538-1539 Second smallpox epidemic Famine 18 1541-1548 Drought, frost, strong winds, crop Famine, epidemic of hemorrhagic disease. fevers, high mortality 19 1550-1555 Drought, mumps epidemic Famine 20 1558-1559 Frost, locust Famine, epidemic of hemorrhagic fevers 21 1562-1564 Drought, epidemics Famine, epidemics of measles, smallpox, and hemorrhagic fevers; high mortality 22 1571-1573 Drought, epidemic Famine, epidemic of unknown origin 23 1576-1579 Drought Famine, epidemic of hemorrhagic fever, high mortality 24 1584-1588 Drought Famine, epidemic of hemorrhagic fever, high mortality 25 1594 Drought, frost, heat waves Famine 26 1610-1613 Drought, frost, strong winds Famine 27 1615-1517 Drought, frost Famine, epidemic of measles 28 1621-1623 Drought Famine 29 1629 Floods Famine 30 1634-1635 Drought Famine, epidemic of whooping cough 31 1639-1642 Drought Famine, epidemics of measles, whooping cough, and hemorrhagic fever 32 1658-1663 Drought Famine, epidemic of measles 33 1691-1697 Drought, frost, floods, speculation Famine, riots, epidemics of measles and other unknown diseases continued

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 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS TABLE 3-1 Continued Years Causes Remarks 34 1713-1714 Drought, frost Famine, epidemic of unknown disease, high mortality 35 1718 Drought Famine 36 1736-1739 Drought Famine, epidemic of hemorrhagic fever, high mortality 37 1746-1749 Drought Famine, epidemics of smallpox and typhus 38 1784-1789 Drought Famine, epidemic of hemorrhagic fever, high mortality SOURCE: Adapted from Chimalpahin (2001); Cooper (1965); de Alva Ixtlixóchitl (1975); Flores and Malvido (1985); Garcia et al. (2003); Gerhard (1986); Gibson (1964); Therrell et al. (2004). TABLE 3-2 Major Epidemics in the Valley of Mexico Number of Epidemics That Caused High Mortalitya Diseases (n = 15) Number Duration (years) 1 Hemorrhagic fevers: 24 1.78 ± .62 4 cocoliztli, matlazahuatl 2 Smallpox 20 1.22 ± .42 5 3 Typhus 18 1.25 ± 1.94 3 4 Unknown 19 1.30 ± 1.41 3 5 Measles 13 1.21 ± .42 3 6 Influenza 7 1.0 ± 0 1 7 Typhoid fever 4 1.25 ± .50 0 8 Poliomyelitis 3 1.4 ± .54 0 9 Cholera 3 3.0 ± 2 2 10 Whooping cough 2 1.0 ± 0 0 11 Scarlet fever 2 1.5 ± .70 0 12 Mumps 1 1.0 ± 0 1 13 Chickenpox 1 1.0 ± 0 1 14 Meningitis 1 1.0 ± 0 0 15 Croup 1 1.0 ± 0 0 a >1% of the total population. SOURCE: Adapted from Chimalpahin (1998); Cooper (1965); de Torquemada (1969); Flores (1888); Flores and Malvido (1985); Garcia et al. (2003). involved in 31 (26.05 percent) of the cases. For the remaining 33 (27.73 percent) epidemics, including 24 described as hemorrhagic fevers, the cause remains to be identified. All 13 known diseases that led to epidemics were caused by exclusive human pathogens with known human-to-human transmission (smallpox, measles, typhus, etc.). Aerosols were the most common mechanism for person-to-person

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7 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION contagion, accounting for 48 (40 percent) of all the epidemics. This was followed by insect vectors, with 18 (8.4 percent) epidemics, and water-borne diseases accounting for 10 (8.4 percent). For the remaining 43 epidemics the mechanism of transmission remains unknown. As in many parts of the world, five diseases were emerging infections of their respective times. All of them were imported and became permanently established in the country (AIDS, chickenpox, measles, mumps, and smallpox). For reasons that remain unclear, cholera disappeared after each introduction. Influenza behaved with the same periodic outbreaks as it does in the rest of the world, and hemorrhagic fevers reemerged locally from a distant past. The four most destructive epidemics (see Table 3-3), with mortality rates ranging from 20 to 90 percent of the entire population, were associated with a sequence of climate extremes, with drought in the years preceding the epidemic followed by wetness during the year of the epidemic (Acuña-Soto et al., 2000, 2002). Drought and the Collapse of Teotihuacán The city of Teotihuacán, located about 40 km north of Mexico City, was one of the largest and most sophisticated human conglomerates of the preindustrial world. With a complex urban design, the city was the cultural, religious, and military center of a vast area in Mesoamerica. Following its splendor between the years 300 A.D. and 600 A.D, the city went into decline between 650 A.D. and 750 A.D. (Millon, 1970). Undeniably severe and sustained drought occurred in the eighth and ninth centuries in North America (Acuña-Soto et al., 2005). TABLE 3-3 Deadliest Epidemics in Central Mexico Mortality of the Diseases Year Total Population (%) 1 Unknown 1003-1011 90 (?) 2 Hemorrhagic fevers (cocoliztli) 1545-1548 70-80 3 Hemorrhagic fevers (cocoliztli) 1576-1578 50 4 Hemorrhagic fevers (matlazahuatl) 1736-1737 ~20-30 5 Smallpox 1520 ~15 6 Hemorrhagic fevers (mysterious fevers) 1813-1815 ~10 7 Influenza 1918 ~5 8 Cholera 1833 ~5 9 Smallpox-typhus 1763-1764 ~5 10 Smallpox 1779 ~4 11 Smallpox 1797-1798 ~4 12 Cholera 1850-1854 4 13 Typhus 1915 1 14 Smallpox 1840 1 SOURCE: Adapted from Chimalpahin (1998); Cooper (1965); de Torquemada (1969); Flores (1888); Flores and Malvido (1985); Garcia et al. (2003).

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 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS Based on the similarities of the climate (drought) and demographic (large popu- lation loss) events of the sixteenth century in the same area, it has been pro- posed recently that drought-associated epidemics of hemorrhagic fever may have contributed to the massive population loss during the collapse of Teotihuacán (Acuña-Soto et al., 2005). The specific co-occurrence of drought and abandon- ment of Teotihuacán has not been proved, but it is an attractive hypothesis given the well-documented occurrence of megadrought in adjacent areas (Hodell et al., 1995; Metcalfe and Hales, 1994). The Fall of Tula As a result of the meticulous labor of certain educated Indian nobility and Spanish friars during the sixteenth century, pre-Hispanic Mexico’s written history—lost as a consequence of the Spanish order to set fire to the library of the city of Texcoco—was partially recovered. Indian authors such as Fernando Alvarado Tezozómoc (Tezozómoc, 1975), Domingo Chimalpahin (Chimalpahin, 1998, 2001), and Fernando de Alva Ixtlixóchitl (de Alva Ixtlixóchitl, 1975) inter- viewed many elders and studied some of the texts that survived the fire but have since disappeared. Europeans, such as Friar Bernardino de Sahagún (Sahagún, 1997), worked with informants. Fernando de Alva Ixtlixóchitl related the fall of Tula (de Alva Ixtlixóchitl, 1975). He described a series of climatic disasters that plagued the Toltecs for 20 years before a huge epidemic that resulted in a dramatic population loss. Beginning in the year 984 A.D., heavy rains “that destroyed most buildings and lasted for 100 days” were followed by a year of intense heat that “dried all plants and trees.” The next year came with frost “that took all the land without leaving anything.” The year after, heavy rains came again “with great hailstorms and lightning, so abundant that all the surviving trees were destroyed.” This period was followed by an intermission of 12 years of normal weather, but 4 years before the epidemic, a plague of worms infested the grain. Fernando de Alva Ixtlixóchitl (1975) describes what appears to have been an epidemic in the year 1003, in the style of pre-Hispanic legends: In the year 1003, when in the first days, a little boy that was white, blond and beautiful, that had to have been a demon, was on a hill. They took him to the City to show him to the king. When the king saw him, he demanded that they bring him back from where they had taken him, because it did not seem to be a good sign. And then the little demon boy’s head began to rot, and many people died from the horrible smell. The Toltecs decided to kill him when one of them was able to reach him, because every one who arrived near the boy died soon after. With this horrible smell, disease spread all over the land and out of the 1,000 Toltecs, 900 died. . . . From this time forward, there was a law that on its fifth birthday, any blond creature would be sacrificed, and this lasted up until the arrival of the Spanish.

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 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION The collapse of Tula ended with an extremely violent war, as evidenced by archeological data. During the sixteenth century, several Indian historians wrote about the history of the fall of Tula. Other authors, using independent sources of information, narrate the same events (Chimalpahin, 1998, 2001; Tezozómoc, 1975). Yet the climatic history of the collapse of the Tula Empire is waiting for high-resolution proxy evidence of rainfall. Drought-Associated Epidemics of Hemorrhagic Fevers of the Sixteenth Century The post-Conquest collapse of the Mexican population occurred predomi- nantly during the sixteenth century megadrought (Acuña-Soto et al., 2000, 2002, 2004; Stahle et al., 2000). According to all witnesses (Farfan, 1592; Lopez de Hinojoso, 1578, 1595; Somolinos, 1956), the events that caused the highest mortality were a series of epidemics of hemorrhagic fevers referred to as cocoliztli (Nahuatl word for lethal “pestilence”) that probably began in 1536 (see Table 3-4). The epidemics of 1545 and 1576-1580 were particularly lethal. Together, they were responsible for approximately 12 million to 15 million deaths in the highlands of Mexico. During the epidemics, a large proportion of the population was incapacitated. Some witnesses described whole families dying of starvation rather than disease, even when not severely ill. Cocoliztli epidemics evolved as an expanding wave originating in central Mexico that radiated outward over the highlands of central Mexico and caused severe social and economic disintegration. The cause of cocoliztli remains elusive. A brief consensus description, based on contemporaneous attending physicians, is the following: The disease had a very short course, started abruptly with high fever, vertigo, severe headache, insatiable thirst, red eyes, and weak pulse. Shortly after, patients became intensely jaundiced, demented, and restless. Then hard and painful nodules appeared behind one or both ears, sometimes so large that they occupied the entire neck and half of the face. This process was accompanied by intense chest and abdominal pain, as well as dysentery. Toward the end, blood flowed from the ears, anus, vagina, mouth, and nose. The disease was almost inevitably fatal for the native population. The Spaniards were minimally affected, and when they occasionally acquired the disease, it had a benign course (Farfan, 1592; Lopez de Hinojoso, 1578, 1595; Somolinos, 1956). Drought was particularly important for the epidemics of hemorrhagic fevers in Mexico. Using tree-ring reconstructions of rainfall over central Mexico, cocoliztli epidemics were found to occur in years of abundant rain embedded in the midst of the sixteenth-century megadrought (Acuña-Soto et al., 2002, 2004; Stahle et al., 2000). The 1736 and 1813 epidemics were also highly lethal and were asso- ciated with a similar sequence of drought and dryness. The hemorrhagic fevers mysteriously disappeared after 1815 (Acuña-Soto et al., 2000; Cooper, 1965). At

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20 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS A Kern Co. 35 Duration of EIP50 Risk level 2 30 25 3 20 Days 15 4 5 10 5 0 30 26 22 18 Temp[C] B 5 COAV 4 GRLA Figure 3-7A KERN Risk level MERC bitmapped, except gray box (days/temp) lower right PLCR each map is separate 3 SAYO Kern Co. SHAS SJCM SUYA TEHA 2 TRLK WEST WVAL 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT Half-month FIGURE 3-7 Figure 3-7B

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209 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION C Number of cases Kern Co. Half-month FIGURE 3-7 California mosquito district risk levels 1-5 for WNV transmission: esti- mated from (A) temperatures downloaded from the TOPS system (inset shows the increas- ing duration of extrinsic incubation period with decreasing temperature and associated risk), (B) the entire risk assessment model calculated bimonthly for selected mosquito control agencies, and (C) the number of human cases within each mosquito control region of California. mosquito control and recommendations for human personal protection provide the only methods to interrupt transmission and protect the public. Use of forecasts and nowcasts13 for making control decisions have inherent problems, especially in California and other areas where the public (especially anti-insecticide advocates) frequently believes that the risk of applying insec- ticides, even in ultralow volumes (ULVs), exceeds the risk of illness or death from viral infection. Using forecasts and surveillance measures, it is possible to accurately determine that the risk of an epidemic is imminent and to apply large-scale aerial ULV adulticide treatments to immediately reduce vector abun- dance and transmission. In this scenario, cases are prevented, but the rationale for a large monetary expenditure and exposure of the human population appears unjustified to some because we cannot know whether the prevented cases would have occurred in the absence of vector control measures. The actions of vector control and public health officials are then questioned in the press, despite the fact that risks from pyrethrin insecticides and synergists are minimal (Peterson et al., 2005). If concurrent measures of risk are used instead of forecasts, the virus may have amplified to higher levels, some humans will have been infected before 13 Forecasts or real-time measures of events in the immediate future.

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20 GLOBAL CLIMATE CHANGE AND EXTREME WEATHER EVENTS A Public education: Reactive Personal Protection emergency intervention EPIDEMIC Amplification AMPLIFICATION Proactive population CONTROL MAINTENANCE management WINDOW Time [months] Preventive methods B Figure 3-8A Integrated vector management Personal protection: - avoidance - repellents Reservoir removal or vaccination Vaccination FIGURE 3-8 Intervention options for WNV shown in relation to (A) the amplification curve and (B) the transmission cycle. Figure 3-8B SOURCE: Figure 3-8B is modified from CDC (2005).

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2 APPROACHES TO STUDYING THE CLIMATE-DISEASE CONNECTION adulticides are applied, and the public health consequences can be considerable. In this scenario, cases of severe illness and some deaths occur, the epidemic peak frequently is realized and recognized by the public, and the population is exposed to the same level of adulticides as during preventive sprays. In the latter case, both the antispray advocates and the families of affected cases are perplexed and the cost-benefit ratio is increased. Surveillance in a Changing World West Nile virus will not be the last invading zoonosis to reach North Amer- ica. Rapid globalization of commerce and travel increases the probability of additional vector or pathogen introductions. For example, Aedes albopictus mos- quitoes, which are vectors of dengue, chikungunya, and other viruses, were transported to California and distributed throughout Los Angeles with imported “Lucky Bamboo” (Dracaena spp.) from China (Linthicum et al., 2003; Madon et al., 2002). Fortunately, surveillance detected this introduction and the invading mosquitoes were eradicated. Vector-borne pathogens also frequently enter the United States. Travelers from India with chikungunya viremia levels sufficient to infect mosquitoes have been detected in the United States during the current epidemic (Lanciotti et al., 2007), but the risk for local transmission is unknown because the vector competence of the local mosquito populations is unknown. Climate change exacerbates these situations in time and space by elongating transmission seasons and increasing the geographic area receptive to pathogen introduction (Epstein, 1998; Patz et al., 2000). The WNV epidemic has provided a wake-up call for public health agencies and clearly delineated the inability of current control programs to contain an invading, mosquito-borne zoonosis (Holloway, 2000). Unfortunately, the waning WNV epidemic has resulted in the diversion of both research and surveillance funding to other health problems, and many of those programs still in place focus surveillance diagnostics only on WNV and will not detect the next invading pathogen. Acknowledgments This research was funded by the Climate Variability and Human Health and the California Applications Programs, Office of Global Programs, NOAA; Deci- sion Support through Earth Science Results, NASA; Research Grant AI55607 from the National Institute of Allergy and Infectious Diseases, NIH. We are especially indebted to the corporate members of the Mosquito and Vector Control Association of California and the California Department of Public Health who granted permission for us to utilize their surveillance data for this project. Forrest Melton, NASA, and Bborie Park, UC Davis, assisted with data manipulations.

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