Page 137

Index

A

Advanced Very High Resolution Radiometer, 76
Aerosols, 24, 27, 30, 54
Africa, 35
     see also Rift Valley fever; West Nile virus
     cryptosporidiosis, 56
     famine, 101-102
     malaria, 40, 48
     meningitis, 22, 39
Aggregation bias, 67, 72, 73
Agriculture, 5, 22, 42, 44, 85
     El Niño, 97-98
     remote sensing, 78
AIDS, see HIV/AIDS
American Association for the Advancement of Science, 16
Asia, 14, 39
     cryptosporidiosis, 56
     influenza, 40
     malaria, 40, 65
Atlantic Ocean, 25
     North Atlantic Oscillation, 21

B


Bjerknes, Vilhelm, 15
Bjerknes, Jacob, 17
Bubonic plague, 12-13, 78

C

Centers for Disease Control and Prevention, 7, 73, 74, 108
Cholera, 34, 57-58, 79
     drought/famine, 38-39
     El Niño, 9, 57-58
     geographic factors, 16-17
     historical perspectives, 16-17, 58
     modeling studies/risk assessment, 70-71
     temperature factors, 57-58
Clouds, general circulation models, 27
Coccidioidomycosis, 33, 38
Communication, see Public communication
Computer databases, see Databases
Computer models, 5, 6, 15-16, 24, 105
     seasonal variations, 25
Cost and cost-effectiveness, 105
     agricultural planning, El Niño, 98
     bubonic plague, 13
     early warning systems, 4-5, 68, 91
     surveillance, 74


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Page 137 Index A Advanced Very High Resolution Radiometer, 76 Aerosols, 24, 27, 30, 54 Africa, 35      see also Rift Valley fever; West Nile virus      cryptosporidiosis, 56      famine, 101-102      malaria, 40, 48      meningitis, 22, 39 Aggregation bias, 67, 72, 73 Agriculture, 5, 22, 42, 44, 85      El Niño, 97-98      remote sensing, 78 AIDS, see HIV/AIDS American Association for the Advancement of Science, 16 Asia, 14, 39      cryptosporidiosis, 56      influenza, 40      malaria, 40, 65 Atlantic Ocean, 25      North Atlantic Oscillation, 21 B Bjerknes, Vilhelm, 15 Bjerknes, Jacob, 17 Bubonic plague, 12-13, 78 C Centers for Disease Control and Prevention, 7, 73, 74, 108 Cholera, 34, 57-58, 79      drought/famine, 38-39      El Niño, 9, 57-58      geographic factors, 16-17      historical perspectives, 16-17, 58      modeling studies/risk assessment, 70-71      temperature factors, 57-58 Clouds, general circulation models, 27 Coccidioidomycosis, 33, 38 Communication, see Public communication Computer databases, see Databases Computer models, 5, 6, 15-16, 24, 105      seasonal variations, 25 Cost and cost-effectiveness, 105      agricultural planning, El Niño, 98      bubonic plague, 13      early warning systems, 4-5, 68, 91      surveillance, 74

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Page 138 Crowding, see Population density Cryptosporidiosis, 1, 33, 46, 56-57 D Databases, 107      see also Internet      El Niño, 97      Geographic Information System (GIS), 4, 7, 76-77, 105, 108      standards for surveillance, 6, 66, 74-75, 107 Definitional issues      early warning system, 86      epidemiology, 28-30      glossary, 110-114      risk assessment terminology, 68-69, 111, 112, 113      weather vz climate, 20-22 Demographic factors, 3, 27, 41-42, 70      see also Population density; Urban areas      early warning systems, 90      emerging diseases, 29      SEIR modeling, 33 Dengue virus, 1, 9, 10, 33, 34, 41, 42, 43, 45-48, 74      El Niño, 10      humidity, 46, 47, 48      temperature factors, 33, 34, 47-48      urban areas, 42, 85      water, 25, 42, 46, 47 Department of Defense, 73-74 Developing countries, general, 3, 74, 90, 91 Diagnosis      dengue virus, 74      epidemics, 13, 28 Disasters, see Extreme weather events Dose-response models, 68, 69, 71, 111 Drought, 33, 35, 36-37, 38-39      cholera, 38-39      early warning systems, 5, 101-102      risk assessment, 38 Drug resistance, 2, 43      gonorrhea, 40      historical perspectives, 9      malaria, 48 Drugs, see Pharmaceuticals E Early-warning systems, 2, 4-7, 10, 11, 27, 86- 102, 105-106      committee meetings, 133-134, 135      cost factors, 4-5, 68, 91, 93      defined, 86      demographic factors, 90      drought/famine, 5, 101-102      ecological factors, 5, 86-87, 89-90      fire, 99      funding, 93      historical perspectives, 14-16      hurricanes, 101      local factors, 88, 90, 91, 92, 93-97, 101, 102, 106, 135      models, 26-27, 88, 89      national-level factors, 14-15, 88, 90, 92, 102      population density, 90      public communication, 89, 91, 95-96, 102, 135      public health services, 5, 88, 90-92, 93      regional factors, 90, 92, 93      risk assessment, 87-88, 89, 90, 94-95      sanitation, 90, 94      sentinel animals, 86, 87, 89      state-level factors, 92      temporal factors, 91, 92      uncertainty, 87      vaccines, 90      waterborne diseases, general, 90, 94, 96 Ecological factors, xi, xii , 9, 10, 11, 35, 36, 75, 80-85, 103, 104, 107-108      aggregation bias, 67      committee study methodology, 2, 134      early warning systems, 5, 86-87, 89-90      emerging diseases, 29, 30      historical perspectives, 17      interdisciplinary studies, 7, 71-72      remote sensing, 6, 7, 10, 70, 75-79, 90, 101, 105      SEIR modeling, 33      time-series analysis, 60 Economic factors, 27, 74, 90, 134      see also Cost and cost-effectiveness; Socioeconomic factors      developing countries, general, 3, 74, 90, 91 Education, see Internet; Professional education; Public communication

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Page 139 El Niño/Southern Oscillation (ENSO), 1, 4, 5, 21, 22, 25, 37, 83, 85, 88, 105      agricultural planning, 97-98      cholera, 9, 57-58      databases, 97      defined, 111      dengue virus, 10      global climate, general, 22, 23      historical perspectives, 17, 25      Internet, 23, 98      malaria, 48-49      prospective observations, 60      time-series analysis, 60 Emerging diseases, 29-30, 73-74, 104 Emigration, see Migration Endemic outbreaks, general, 78, 96-97      defined, 28-29, 111 Environmental Protection Agency, 68 Epidemics, 4, 9, 35      see also Early warning systems      committee meetings, 132      defined, 28, 111      diagnostic issues, 13, 28      extreme weather events, 38      hantavirus, 51-52      historical perspectives, 12-13, 36, 38, 49-50      malaria, 48-49      St. Louis encephalitis, 49-50      urban areas, 36 Epidemiology, xii , 4, 5, 6, 10, 28-33, 66, 67- 68, 73-75, 105-106, 107      see also Early warning systems; Risk assessment; Surveillance systems      committee meetings, 134, 135      definitional issues, 28-30      dengue fever, 47-48      extreme weather conditions, 38      historical perspectives, 13, 14, 16-17, 18, 19      meta-analysis, 67      sanitation and, 16 Error of measurement, 24-25, 66-67, 82-85      aggregation bias, 67, 72, 73 Experimental studies, 5, 11, 62-63, 66, 67, 80, 82, 83, 107      interdependence with observational and modeling studies, 6, 67 Expert opinion, xi , 10, 62, 66, 99 Exposure and exposure assessment, 65, 69-70      cholera, 70, 71      dose-response models, 68, 69, 71, 111      food and waterborne diseases, 65      hantavirus, 52      housing and, 38      immunity and, 30      vector-borne diseases, 38, 43, 49, 50 Extreme weather events      see also Drought      flooding, 33, 36-37, 38, 63, 78-79      hurricanes, 36-37, 38, 101      monsoons, 14, 81      risk assessment, 38      temporal factors, 36-37 F Famine      cholera, 38-39      early warning systems, 5, 101-102 Famine Early Warning System, 101-102 Federal Emergency Management Agency, 92 Federal government, 1-2, 7, 73, 107-108      Centers for Disease Control and Prevention, 7, 73, 74, 108      committee meetings, 132      Department of Defense, 73-74      Environmental Protection Agency, 68      Federal Emergency Management Agency, 92      Forest Service, 99      funding, 7, 62, 93      National Center for Ecological Analysis and Synthesis, 6, 107      National Institute of Allergy and Infectious Diseases, 7, 108      National Oceanic and Atmospheric Administration, 60, 76, 93      National Weather Service, 15, 87 Fires and fire control, 99 Flooding, 36-37, 78      cryptosporidiosis, 33      meningitis, 33      remote sensing, 78-79      Rift Valley fever, 33, 63      risk assessment, 38 Food, see Famine; Nutrition and malnutrition Food-borne pathogens, 44, 46, 57, 58, 68, 76, 96

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Page 140 Forests and deforestation, 22, 24, 42, 78, 99 Forest Service, 99 Funding      early warning systems, 93      interdisciplinary studies, 7, 62 G General circulation models, 27 Genetic factors, 3, 35, 36, 105      emerging diseases, 29-30, 73-74, 104 Geographic factors, 1, 3-4, 6      see also Local factors; National-level factors; Regional factors; Spatial factors; State-level factors      cholera, 16-17      cryptosporidiosis, 56      historical perspectives, 12, 13, 17      modeling studies, 27, 65, 66 Geographic Information System (GIS), 4, 7, 76-77, 105, 108 Global Change Research Program, xi-xii, 7, 9, 108 Global climate, general, 2, 17, 81, 82, 104      El Niño, 22, 23      surveillance and, 74 Global Emerging Infections Surveillance and Response Systems, 74 Global warming, 3, 9, 10, 22-24, 27, 37, 81, 82, 104      greenhouse gases, 22, 24, 27      influenza, 55      integrated assessment, 72      mosquito vectors, 9, 49      West Nile virus, 97 Gonorrhea, 40 Greenhouse gases, 22, 24, 27 H Hantavirus, 46, 51-52, 78, 94 Hill, Austin Bradford, 17 Historical perspectives, 1, 9-10, 12-19, 99      cholera, 16-17, 58      committee meetings, 132      cryptosporidiosis, 56      early warning systems, 14-16      El Niño, 17, 25      epidemics, 12-13, 36, 38, 49-50      epidemiology, 13, 14, 16-17, 18, 19      geographic factors, 12, 13, 17      interdisciplinary approaches, 17      precipitation, 14, 25      public health, 18, 19      regional factors, 12-13, 14, 17      research methodology, 13-15, 61      sanitation, 14, 16, 18      seasonal variation, 8, 12, 14, 21, 25      surveillance, 89      time-series analysis, 58, 59-60, 61      vaccines, 9, 42-43      waterborne diseases and water treatment, 14, 16, 18, 44 HIV/AIDS, 1, 40, 90 Housing      early warning systems, 90      Lyme disease, 40      regional factors, 3      vector-borne diseases, 38, 40, 42 Humidity, 2, 46      see also Precipitation      coccidioidomycosis, 33      cryptosporidiosis, 33, 46      dengue virus, 46, 47, 48      influenza, 55      malaria, 46, 48, 65      meningitis, 33, 39      modeling studies, 65      Rift Valley fever, 33 Hurricanes, 36-37, 38, 101 I Immigration, see Migration Immune response, 35-36, 111-112      see also Drug resistance; Vaccines      cholera, 57      influenza, 54-55      refugees, 37, 40      Rift Valley fever, 51      travelers and migrants, 40 Incidence and prevalence, 6, 9, 10, 70, 74      see also Endemic outbreaks; Epidemics; Surveillance      cholera, 57      cryptosporidiosis, 56      defined, 28, 112, 113      dengue fever, 45-46      emerging diseases, 29      influenza, 54      Lyme disease, 10, 52-53

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Page 141      malaria, 10, 48-49      time-series analysis, 60 Indian Ocean, 17, 21, 25, 51 Influenza, 1, 8, 46, 54-55, 134      temperature factors, 33, 55      travelers, 40 Insects, 36, 81      see also Lyme disease; Mosquitos; Pesticides; Vector-borne diseases      eradication of vectors, 36, 43, 46, 49 Integrated assessment, 59, 71-73 Inter-American Institute, 93 Interannual variation, 1, 2-3, 21, 81, 82-83, 103, 104      see also El Niño/Southern Oscillation Interdisciplinary approaches, 2, 7, 62      ecological factors, 7, 71-72      funding, 7, 62      historical perspectives, 17      integrated assessment, 59, 71-73      modeling studies, 6, 7, 104-105, 107-108      professional education, 6, 7, 62      remote sensing and, 76      research centers, 6, 62      social factors, 7, 71-72      socioeconomic factors, 7, 72, 107 Intergovernmental Panel on Climate Change (IPCC), 9, 24, 37 International Research Institute for Climate Prediction, 93 Internet, 74      El Niño, 23, 98 K Koch, Robert, 16-17 L Land cover and land use, 3, 22, 24, 35, 39-40, 42      agriculture, 5, 22, 42, 44, 78, 85, 97-98      forests and deforestation, 22, 24, 42, 78, 99      Lyme disease, 39-40, 54      seasonal variation, 25-26      soil, 33, 34, 54, 76, 79      urban areas, 35, 36, 40, 41, 42, 46, 49-50, 55, 79, 85, 93-97      vegetation, general, 22, 24, 54, 76, 78, 81, 83-84      wetlands, 79 Local factors, 24      early warning systems, 88, 90, 91, 92, 93-97, 101, 102, 106, 135      epidemics, 13      modeling studies, 65      surveillance systems, 73 Lorenz, Edward, 16 Lyme disease, 39-40, 46, 52-54, 78, 79 M Malaria, 1, 8, 43, 46, 48-49, 78, 79, 85, 135      air transport, 41      drug-resistant, 48      global warming, 9      humidity, 46, 48, 65      incidence, 10, 48-49      migrants, 40      modeling studies, 65      precipitation, 46, 48, 65      seasonal variation, 33      temperature, 33, 34, 46, 48      water, standing, 42, 46      wind, 48 Malnutrition, see Nutrition and malnutrition Mass media, 10 Mathematical, 9, 13, 15-16, 63-68, 88, 112      committee meetings, 133      SEIR framework, 31-33, 36, 63, 88 Mechanistic models, 63-64, 65, 106-107 Meningitis, 1, 22, 33, 39 Meta-analysis, 67, 112 Methodology, see Research methodology Migration, 10, 35, 40-41      see also Travel and tourism      refugees, 37, 40 Modeling studies, 5-6, 11, 59, 70, 98, 104-105, 106-107      agricultural land uses, 98      animal models, 16-17, 55      cholera, 70-71      climate, 7, 9      computer models, 5, 6, 15-16, 24, 25, 105      disease transmission, 30      dose-response, 68, 69, 71, 111      early warning systems, 26-27, 88, 89      epidemiology, 4, 107

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Page 142      experimental studies and, 6, 67      forest fire conditions, 99      general circulation models, 27      geographic factors, 27, 65, 66      historical perspectives, 9      humidity, 65      influenza, 55      interdisciplinary approaches, 6, 7, 104- 105, 107-108      land/atmosphere, 26      malaria, 65      mathematical, 9, 13, 15-16, 63-68, 71, 72, 88      SEIR framework, 31-33, 36, 63, 88      mechanistic models, 63-64, 65, 106-107      multivariate models, 64, 65      observational studies and, 6, 67      ocean, seasonal variation, 25      ocean/land/atmosphere, 27      precipitation, 27, 65      prediction and prevention, 10      public health services, 66      spatial factors, 61, 65, 66, 67      statistical-empirical models, 6, 64, 66, 106      temperature, 65      temporal factors, 66      uncertainty, 3, 27, 103-104 Monsoons, 14, 81 Mosquitos, 1, 9, 30, 34, 43, 47-49, 135      see also Dengue virus; Malaria; Yellow fever      modeling studies, 65      remote sensing, 76, 78-79      Rift Valley fever, 33, 35, 46, 50-51, 63, 76, 78, 88      St. Louis encephalitis, 46, 49-50      West Nile virus, 90, 93-97 Multidisciplinary approaches, see Interdisciplinary approaches Multivariate models, 64, 65 N National Center for Ecological Analysis and Synthesis, 6, 107 National Institute of Allergy and Infectious Diseases, 7, 108 National-level factors, 135      early warning systems, 14-15, 88, 90, 92, 102      meteorological systems, 75      surveillance systems, 73, 74 National Oceanic and Atmospheric Administration, 60, 76, 93 National Weather Service, 15, 87 Natural disasters, see Extreme weather events Normalized Difference Vegetation Index, 76 North Atlantic Oscillation, 21 Nutrition and malnutrition, 37, 38-39, 41-42, 43      see also Famine; Food-borne pathogens O Observational studies, 5, 11, 59-62, 73, 75, 80-81, 88, 105, 107      historical perspectives, 9      interdependence with experimental and modeling studies, 6, 67      prospective observations, 60-61      remote sensing, 6, 7, 10, 70, 75-77, 90, 101, 105      temporal factors, 59-60, 61, 80-81      uncertainty, 3, 103-104 Oceans      see also El Niño/Southern Oscillation; North Atlantic Oscillation      Atlantic Ocean, 21, 25      color, 79      Indian Ocean, 17, 21, 25, 51      Pacific Ocean, 17, 25, 51      seasonal variability models, 25      surface height, 22, 58, 79      surface temperature, general, 9, 27, 51, 57-58, 79 Office of Global Programs (NOAA), 60, 93 Outbreaks, see Epidemics P Pacific Ocean, 17, 25, 51      see also El Niño/Southern Oscillation; North Atlantic Oscillation Parasitic diseases, 1, 9, 35      see also Malaria      cryptosporidiosis, 1, 33, 46, 56-57      schistosomiasis, 39, 43, 78, 79 Pesticides, 43, 96      historical perspectives, 9      resistance to, 2, 9

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Page 143 Pharmaceuticals, 3, 9, 36      see also Drug resistance; Vaccines Population density, 3, 35, 37, 41, 46, 55      early warning systems, 90      influenza, 33, 55      see also Urban areas Population factors, other, see Demographic      factors; Social factors;      Socioeconomic factors Precipitation, 21, 46, 90, 97      see also Drought; Flooding      cryptosporidiosis, 1, 46, 56      dengue fever, 46, 47      general circulation models, 27      historical perspectives, 14, 25      malaria, 46, 48, 65      modeling studies, 27, 65      monsoons, 14, 81      Rift Valley fever, 46, 51      seasonal, general, 25      vegetative cover and, 24, 78 Prevalence, see Incidence and prevalence Professional education      interdisciplinary, 6, 7, 62      response strategies, 94 Prospective observations, 60-61 Public communication, 89, 91, 95-96, 98, 102, 135      see also Internet      Mass media, 10 Public health, 3, 10, 36, 42-43, 68, 135      see also Housing; Sanitation; Vaccines; Waterborne diseases and water treatment      bubonic plague, 13      early warning systems, 5, 88, 90-92, 93      emerging diseases, 29      historical perspectives, 18, 19      hurricanes, 100      interdisciplinary studies, 7      modeling studies, 66      quarantine, 13, 36      vector eradication, 36, 43, 46, 49 Public opinion, 10, 91 Q Quantitative risk characterization, 2, 4, 27, 62, 64, 65, 69, 71, 72, 96, 105 Quarantine, 13, 36 R Rain, see Precipitation Regional factors, 3, 21, 22, 24, 61      see also Epidemics      developing countries, general, 3, 74, 90, 91      early warning systems, 90, 92, 93      epidemics, 12-13      general circulation models, 27      global warming, 24      historical perspectives, 12-13, 14, 17      modeling studies, 65, 66      monsoons, 14      precipitation, 24      remote sensing, 73      surveillance systems, 73, 105-106      temperature, general, 24      time-series analysis, 60 Remote sensing, 6, 7, 10, 70, 75-79, 90, 101, 105 Reporting bias, 66 Research methodology, 5, 59-79      see also Interdisciplinary approaches; Modeling studies; Observational studies; Uncertainty      aggregation bias, 67, 72, 73      causal relations, general, 83-84      committee study at hand, 2, 132-135      error of measurement, 24-25, 66-67, 82- 85      experimental studies, 5, 6, 11, 62-63, 66, 67, 80, 82, 83, 107      expert opinion, xi, 10, 62, 66, 99      historical perspectives, 13-15, 61      meta-analysis, 67, 112      remote sensing, 6, 7, 10, 70, 75-79, 90, 101, 105      stochastic processes, 73      time-series analysis, 58, 59-60, 61 Retrospective analysis of historical trends, 61 Retrospective analysis of natural variation, 59-60 Richardson, Lewis Frye, 15 Rift Valley fever, 33, 35, 42, 46, 50-51, 63, 76, 78, 88 Risk assessment, 59, 68-71      see also Exposure and exposure assessment      cholera, 70-71      defined, 113      dose-response models, 68, 69, 71, 111

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Page 144      drought, 38      early warning systems, 87-88, 89, 90, 94-95      extreme weather events, 38      flooding, 33, 63      forest fire conditions, 99      integrated assessment, 59, 71-73      modeling studies, 65      quantitative, 2, 4, 27, 62, 64, 65, 69, 71, 72, 96, 105      sanitation, 38      waterborne diseases, 38, 68      West Nile virus, 94-95 S Sanitation, 3, 36, 41, 43      see also Waterborne diseases and water treatment      dengue fever, 42      early warning systems, 90, 94      epidemiology and, 16      historical perspectives, 14, 16, 18      malaria, 49      regional factors, 3      response strategies, 94      risk assessment, 38      St. Louis encephalitis, 49-50      urban areas, 41-42 Satellite technology, see Remote sensing Schistosomiasis, 39, 43, 78, 79 Seasonal variation, 2-3, 21, 25-27, 81, 82-83, 103, 104      see also El Niño/Southern Oscillation      cholera, 57-58      computer models, 25      cryptosporidiosis, 56-57      dengue virus, 33      historical perspectives, 8, 12, 21, 14, 25      influenza, 33, 55      malaria, 33      modeling of, 25      monsoons, 14, 81      vibrios, 57-58 Sea surface      height, 22, 58, 79      temperature, 9, 27, 51, 57-58, 79;       see also El Niño/Southern Oscillation; North Atlantic Oscillation SEIR framework, 31-33, 36, 63, 88 Sentinel animals, 86, 87, 89 Social factors, 9, 36, 41-42      see also Demographic factors      committee study methodology, 2      interdisciplinary studies, 7, 71-72      population density, 3, 33, 35, 37, 41, 46, 55, 90;      see also Urban areas      time-series analysis, 60 Socioeconomic factors      developing countries, general, 3, 74, 90, 91      interdisciplinary studies, 7, 72, 107 Soil conditions      Lyme disease, 54      remote sensing, 76, 79      wind-blown dust, 33, 34 Spatial factors, 2, 5, 6, 11, 13, 20, 59, 61, 80- 85, 107      see also Geographic factors      aggregation bias, 67, 72      climate defined, 20-21      cryptosporidiosis, 56      general circulation models, 27      global warming, 24      Lyme disease, 53      modeling studies, 61, 65, 66, 67      temperature factors and, 20-21, 24, 61      uncertainty, 3-4, 82-83, 104 Standards      databases, 6, 66, 74-75, 107      public health response, 92      reporting bias, 66 State-level factors      early warning systems, 92      surveillance systems, 73 Statistical-empirical models, 6, 64, 66, 106 St. Louis encephalitis, 46, 49-50, 61, 89-90 Stochastic processes, 73 Storms, 21      flooding, 33, 36-37, 38, 63, 78-79      hurricanes, 36-37, 38, 101      monsoons, 14, 81 Surveillance systems, 4, 5-7, 10, 66, 69, 73- 75, 89-90, 93, 95, 105-108      see also Early warning systems; Epidemiology; Observational studies      committee study methodology, 2, 135      cost factors, 74      influenza, 54      prospective observations, 60      regional factors, 73, 105-106      reporting bias, 66

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Page 145      standards, 6, 66, 74-75, 107      time-series analysis, 60 T Temperature, 1, 2, 22, 81      see also Global warming; El Niño/Southern Oscillation      cholera, 57-58      climate defined, 20-21      dengue virus, 33, 34, 47-48      historical perspectives, 14      influenza, 33, 55      integrated assessment, 71-72      Lyme disease, 53-54      malaria, 33, 34, 46, 48      microbe replication rate, 34      modeling studies, 65      sea surface, general, 9, 27, 51, 57-58, 79      spatial factors and, 20-21, 24, 61      St. Louis encephalitis, 50      vector-borne diseases, general, 34, 65      vibrios, other than cholera, 58 Temporal factors, 5, 59, 80-85      see also Interannual variation; Seasonal variation      climate defined, 20, 21-22      early warning systems, 91, 92      epidemics, 13      extreme weather events, 36-37      Lyme disease, 53      modeling studies, 66      observational studies, 59-60, 61, 80-81      uncertainty, 3-4, 72, 82-83, 104 Time-series analysis, 58, 59-60, 61 Togavirus, see Yellow fever Travel and tourism, 3, 10, 29, 35, 40-41, 97, 104      see also Migration      influenza, 55      quarantine, 36      surveillance systems, 73 U Ultraviolet radiation, 33, 55 Uncertainty, 3-4, 82-85, 104      aggregation bias, 67, 72, 73      early warning systems, 87      error of measurement, 24-25, 66-67, 82- 85      integrated assessments, 72, 73      modeling studies, 3, 27, 103-104      observational studies, 3, 103-104      reporting bias, 66      spatial factors, 3-4, 82-83, 104      temporal factors, 3-4, 72, 82-83, 104 United Nations, 75 Urban areas, 35, 36, 40, 41, 79      dengue fever, 42, 85      influenza, 55      sanitation, 41-42      St. Louis encephalitis, 46, 49-50      West Nile virus, 93-97 V Vaccines, 3, 7, 36, 42-43, 94      early warning systems, 90      historical perspectives, 9, 42-43 Vector-borne diseases, 1, 2, 30, 31, 38, 94      see also Dengue virus; Insects; Lyme disease; Malaria; Mosquitos; Pesticides; Rift Valley fever      air transport, 41      bubonic plague, 12-13, 78      committee meetings, 133, 135      control of vectors, 7      definitions, 113-114      eradication of vectors, 36, 43, 46, 49      hantavirus, 46, 51-52, 78, 94      housing, 38, 40, 42      land cover, 39-40      migration and travel, 46      modeling studies, 65      St. Louis encephalitis, 46, 49-50, 61, 89-90      temperature factors, 34, 65 Vegetation, 22, 24, 81, 83-84      agriculture, 5, 22, 42, 44, 78, 85, 97-98      forests and deforestation, 22, 24, 42, 78, 99      Lyme disease, 54      remote sensing, 76, 78 Vibrios, 46, 57-58      see also Cholera Viruses, 1      see also Dengue virus      hantavirus, 46, 51-52, 78, 94      HIV/AIDS, 1, 40, 90

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Page 146      St. Louis encephalitis, 46, 49-50, 61, 89-90      West Nile virus, 90, 93-97      yellow fever, 1, 9, 78 W Waterborne diseases and water treatment, 7, 38, 42, 44, 46, 79      see also Flooding; Sanitation; Vibrios; Wetlands      cholera, 16-17, 34, 38-39, 57-58, 70-71, 79      cryptosporidiosis, 1, 33, 46, 56-57      dengue fever, 25, 42, 46, 47      drought and, 38-39      early warning systems, 90, 94, 96      historical perspectives, 14, 16, 18, 44      malaria, 42, 46      response strategies, 90, 94      Rift Valley fever, 42      risk assessment, 38, 68      schistosomiasis, 39      temperature factors, 34      vibrios, other than cholera, 58 West Nile virus, 90, 93-97 Wetlands, 79 Wind, 12, 14, 20, 21, 34, 38, 48 World Health Organization, 9, 43, 54, 73, 134 World Meteorological Organization, 75, 134 World Weather Watch, 75 Y Yellow fever, 1, 9, 78