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..20 3-2-3...20 3-2-4...21 3-2-5...22 3-3.

3 1 2 3 ( ) 4 27 (OR=7.66) 30 (OR=6.70) 19 (OR=4.99) 27 (OR=24.62) 30 (OR=11.65) 20 (OR=8.80) : 1

4 Abstract Global climate changes may alter the ecosystem and environmental quality, and result in, potentially, significant threats to human health. For instance, weather variability and climate change are known to impact on the dynamics of infectious diseases especially in vector borne diseases and water/ food borne diseases. Our study was therefore to (1) review and summarize previous studies on the relationship between climate change and infectious diseases, (2) identify the existing databases in Taiwan available for evaluating the relationship between general climate factors and infectious diseases, (3) examine the associations between the trends of general climate factors (ex. temperature, rainfall, and relative humidity ) and occurrence of certain infectious diseases in Taiwan, and (4) recommend the strategy for developing surveillance systems of certain infectious diseases integrated with weather parameters in Taiwan. To date, our study has established various databases including infectious diseases case registry, weather parameters, and demographic and vector densities. We have also applied geographic information system to map the geographic distribution of common vector and water borne diseases in Taiwan. Relations of the occurrence of dengue fever to various climatic and environmental factors in southern Taiwan have been continuously documented since Our finding indicated that the surveillance of domestic vector density could not predict the outbreak of dengue fever in Kaohsiung County, a hot spot for such a disease in Taiwan. Yet, temperature appeared to be an effective indicator for predicting the disease outbreak. Analyses showed that when the monthly average temperature (T mean ) went higher than 27, monthly average maximum temperature (T max ) higher than 30 and monthly average minimum temperature (T min ) higher than 19 in the previous month (Lag=1), the risk of the occurrence of minor outbreak (reporting case 17) will increase (OR=7.66, 6.70, and 4.99). Meanwhile, if the T mean went higher than 27, T max higher than 30, and T min higher than 20 in the previous month, the risk of occurrence of major outbreak (reporting cases 81) will also increase (OR=24.62, 11.65, 8.80) for the following month. Such a prediction could not be established with the level of monthly rainfall or relative humidity. Our study is likely to be the first to demonstrate a positive and statistical relationship between 2

Our study was therefore to (1) review and summarize previous studies on the relationship between climate change and infectious diseases, (2) identify the existing databases in Taiwan available for

5 temperature and outbreak of dengue fever, using the case registry and environmental data from southern Taiwan. This finding support, with quantitative information, the proposition that as the environment became warmer, the dengue fever endemic in southern Taiwan would also be worsen. Further studies may focus on developing models to estimate the associations between climate change and extreme weather events and their impacts on geographical distribution of dengue fever epidemic in Taiwan. International comparisons would be made when the scenarios are properly characterized. Keywords: climate change, weather variability, temperature, dengue fever, infectious diseases 3

6 (Intergovernmental Panel on Climate Change; IPCC) IPCC [IPCC, 1996] [IPCC, 2001] IPCC (hydrological cycle) [IPCC, 2001] 4

7 5 [, 2004] [Keatinge et al., 1986; Semenza et al., 1999; Huynen et al., 2001; Kaiser et al., 2001; Diaz et al., 2002; Nayha, 2002; Weisskopf et al., 2002] [WHO, 2003] (chain of infection) (reservoir) ( 1-1) [Nelson, 2001] ( ) [Patz et al., 2000; Gubler et al., 2001; Rose et al., 2001] (El Nino)

, 2002] [WHO, 2003] (chain of infection) (reservoir) ( 1-1) [Nelson, 2001] (

8 (Vibrio chlorae, V. parahemolyticus V. vulnificus) ( ) [Checkley et al. 2000; Pascual et al. 2002; Pascual et al. 2000; Rodo et al. 2002] [Pascual et al., 2000] [Hales et al., 2002; Rogers and Randolph, 2000; Lindgren and Gustafson, 2001] [Zhou et al., 2000] 100 IPCC 75% 660 6

9 . (reservoirs) (anthroponoses) Humans Humans Humans Vector/Vehicle Humans Vector/Vehicle (zoonoses) B Vector borne: Proper air-borne: Food-/ water- borne: A Animals Animals Vector/Vehicle Animals Animals Vector/Vehicle Humans Humans ( / ) Vector borne: Food-/ water- borne: Proper air-borne: Nature environments Water/Soil Nature environments Water/Soil Humans Humans Vector/Vehicle Proper air-borne: (Histoplasmosis, cryptococcosis),, Food-/ water- borne: 7

Humans Humans ( / ) Vector borne: Food-/ water- borne: Proper air-borne: Nature environments Water/Soil Nature

10 ( ) 4. 8

11 2-1 ( ) review article

12 (geography information system; GIS) 2-4 surveillance [, 2002b] ( ) ( ) ( ) 10

13 3-1 (1) [Halstead, 1996] [Altekruse et al., 1998] (2) ( ) (Plasmodium falciparum) [Macdonald, 1957; Mellor et al., 2000] (3) [Moller et al., 2000] 11

14 3-1 [WHO, 2004] (1000 DALYs a ) c b? STDs ( ) 106,231 ** -- N/A Influnza ( ) 97,658 ***** ** Cholera ( ) 62,227 ***** ***** Malaria ( ) 40,213 >100 ***** ***** Tuberculosis ( ) 35,792 ** - N/A Meningococcal Menungitis ( ) Lymphatic filariasis ( ) 5,751 ***** *** 5, ** NA a DALYs (Disability Adjust Life Year) b * ** *** **** ***** c * ** *** **** ***** 12

15 3-1 ( ) (Leishmaniasis) (1000 DALYs a ) c b? 1,810 ** *** Schistosomiasis ( 1,713 * * ) Japanese encephalitis ( ) 426 *** *** St. Louis encephalitis NA *** *** Dengue fever ( ) 433 **** *** Lyme disease ( ) N/A * * Yellow fever ( ) NA **** ** a DALYs (Disability Adjust Life Year) b * ** *** **** ***** c * ** *** **** ***** 13

St. Louis encephalitis NA *** *** Dengue fever ( ) 433 **** *** Lyme disease ( )

16 (1) : Hales 2002 Lancet ( 50-60% ) [Hales et al., 2002] [Hay et al., 2002; Rogers and Randolph, 2000] Plasmodium falciparum [Bouma et al., 1996; Bouma et al., 1994]

, 2002; Rogers and Randolph, 2000] 1981-1991

17 [Watts et al., 1987] 3-2. [modified from Gubler, 2001] Temperature effects on selected vectors and vector- borne pathogens Vectors - Survival can decrease or increase depending on the species - Some vectors have higher survival at higher latitude and altitude with higher temperature - Changes in rates of vector population growth - Changes in feeding rate and host contact (which may alter survival rate) - Changes in the seasonality of populations Pathogens - Decreased extrinsic incubation period of pathogen in vector at higher temperature - Changes in the transmission season - Changes in distribution - Decrease or increase viral replication Effects of changes on precipitation on selected vectors, vector- borne pathogens and animal reservoirs Vectors - Increased rain may increase larval habitat and vector population size by creating a new habitat - Excess rain or snow pack can eliminate habitats by flooding, thus decreasing the vector population - Low rainfall can create habitat by causing rivers to dry into pools (dry season malaria) - Epic rainfall events can synchronize vector host-seeking and virus transmission - Increased humidity increases vector survival, decreased humidity decrease vector survival Pathogens - Few direct effects but some data on humidity effects on malaria parasite development in the anopheline mosquito host Animal reservoirs (rodents) - Increased rain can increase vegetation, food availability, and population size - Increased rain can also cause flooding and decrease population size but increase contact with humans - Decrease rain can eliminate food and force rodents into housing areas, increasing human contact, but it can also decrease population size Increased Sea level effects on selected vector-borne pathogens Alter estuary flow and change existing salt marshes and associated with mosquito species, decreasing or eliminating selected mosquito breeding sites (e.g. reduced habitat for Culista melanura) 3-1 Chan [Chan et al., 1999] 15

survival at higher latitude and altitude with higher temperature - Changes in rates of vector population growth - Changes in feeding rate and host contact (which may alter survival rate) - Changes in

18 Climate change Ecologic changes Biodiversity loss Community relocation Nutrition cycle changes Changes in transmission biology Vector dynamics - Migration - Breeding - Physiology - Behavior Pathogen dynamics - Reproduction - Transmissibility - Virulence Sociological changes Mitigation/ travel Nutrition Sanitation Population/ economy Epidemiological changes Host physiology/ immunity Diseases morbidity and mortality Effect arrow showing potential influence among factors Direct climate change effects

Sociological changes Mitigation/ travel Nutrition Sanitation Population/ economy Epidemiological changes Host physiology/

19 (2) / 3. (2-7 ) (Nicholls, 1993; Bouma and Dye, 1997; Pascual et al., 2000; Rodo et al., 2002) 200 (Checkley et al., 2000) Vibrio cholerae (Lipp et al., 2002) oocysts (Payment, 1999)

20 3-3. [Rose, 2001]. (e.g. Hepatitis A virus, Coxsackie B virus) (e.g. V. vulnificus, V. Recreational, parahaemolyticus, V. cholerae wound non-o1); Gymnodium, infections Pseudonitzschia spp. (e.g. Cyclospora Cyclospora, Cryptosporidium) : (1) (2) 86 18

21 5% 20 1 CD OO 0.2% ICD-9 A-code 90 ICD-9 ICD-9 A-code A-code (3)

22 : = /

23 [ ] 3-5 [ ] 21

24 ( ) 24 A ( ) ( A ) b A ( )

25 3-6 ( / ) / A ( ) ( 28 / ) 338 / ( ) ( ) 23

26 ( 3-2) (2002 )

27 19 (shigellosis) (shigella) ( 3-3 ) ( 3-4)

28 (Entamoeba histolytica) A

29 3-3-2 (1) Identification dengue fever classic dengue primary dengue (Flavivirus) 4 (DEN-1, DEN-2, DEN-3, DEN-4) Aedes aegypti Aedes albopictus [ 2002] dengue hemorrhagic fever DHF dengue shock syndrome DSS secondary dengue viremia 8-12 (2) Halstead

30 [IPCC, 2001] WHO [WHO, 2005] (3) [ ]

31 Pletch

32 , [ 1997]

33 ( 3-8 ) >80 DEN DEN-1,2, DEN-1,3, DEN-1,2, DEN-1, DEN DEN-1, DEN-1 DEN-2 DEN-2,3, DEN-1 DEN DEN-2 DEN ( ) DEN-2 DEN-2 1 DEN DEN DEN DEN ( ) 2003 ( ) DEN-2 DEN-2 [ Lei etc.,2002; ] (4) [, 1991] 31

34 [, 1997] [APHA, 2000] (67 ) (79 ) 32

35 [, 1989;, 1997] % ( 3-7) ( 3-8)

36 (1) ( ) >2 50% (n=77) >2 50% (n=170) 34

37 ( 3-9) vector>2(%)(l) = *x vector>2(%)(r) = *x vector>2(%)(l) vector>2(%)(r) 3-9 (2002 ) 3-10 ( ) 35

38 ( 3-9 ) >2 3-9 (Lag=0) (Lag=1) ( ) >2 B Sig. R Square Lag= Lag= (2) >2 (>90 th percentile=36 cases)

39 Dengue Dengue VD>2(%) VD>2(%) (Case) (%) >2 (3) th 17 90th 81 ( 3-12 ) (p<0.05) ( 3-10) 37

40 Case numbers 17 Case numbers 81 Mean Mean p Mean Mean p Non-outbreak Outbreak Non-outbreak outbreak

41 Reed et al. [1901] [Flu, 1920] [Watts et al., 1987] [, 1991] ( 3-11) 27 (OR=7.66) 30 (OR=6.70) 19 (OR=4.99) 27 (OR=24.62) 30 (OR=11.65) 20 (OR=8.80) >27 >

42 3-11 ( ) Average temperature Case numbers 17 Case numbers 81 OR 95% C.I. OR 95% C.I. Tmean_ Tmean_ Tmean_ Tmean_ Tmean_ Tmean_ Tmean_ Tmean_ Tmean_ Maximum temperature Tmax_ Tmax_ Tmax_ Tmax_ Tmax_ Tmax_ Minimum temperature Tmin_ Tmin_ Tmin_ Tmin_ Relative humidity RH_ RH_ RH_ Rainfall Rain_ Rain_ Rain_ Imported cases

43 3-11 Average temperature 27 Maximum temperature 30 Minimum temperature 19 Minimum temperature 20 Case numbers 17 Case numbers 81 OR 95% C.I. OR 95% C.I (4)

44 >

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46 and cold spells on mortality rates in the Dutch population. Environmental Health Perspectives. 109: Intergovernmental Panel on Climate Change (IPCC) Cliamte Change 2001: Impacts, Adaptation, and Vulnerability. Intergovernmental Panel on Climate Change (IPCC) Climate Change 1995: The Science of Climate Change. Cambridge University Press. Kaiser, R., et al Heat-related death and mental illness during the 1999 Cincinnati heat wave. American Journal of Forensic Medicine & Pathology.22: Keatinge, W.R., Coleshaw, S.R., Easton, J.C., Cotter, F., Mattock, M.B., Chelliah, R. 1986, Increased platelet and red cell counts, blood viscosity, and plasma cholesterol levels during heat stress, and mortality from coronary and cerebral thrombosis. American Journal of Medicine 81: Lindgren, E. and Gustafson, R Tick-borne encephalitis in Sweden and climate change. Lancet. 358:16-8. Lipp, E. K., et al. 2002, Effects of global climate on infectious disease: the cholera model. Clinical Microbiology Reviews. 15: MacDonald G The epidemiology and control of malaria. London: Oxford University Press. Mellor, P.S. and Leake, C.J. 2000, Climatic and geographic influences on arbovial infections and vectors. Revue Scintifique et Technique de l Office International des Epizooties. 19: Nayha, S Cold and the risk of cardiovascular diseases. A review. International Journal of Circumpolar Health. 61: Nelson K.E., Williams C.M., Graham N.M.H Infectious Disease Epidemiology: Theory and Practice. Maryland: Aspen Publishers, Inc.. Nicholls, N El nino-southern oscillation and vector-borne disease. Lancet. 342:

47 Pascual, M., et al Cholera and climate: revisiting the quantitative evidence. Microbes & Infection. 4: Pascual, M., et al Cholera dynamics and El Nino-Southern Oscillation. Science. 289: Patz, J. A., et al The effects of changing weather on public health. Annual Review of Public Health. 21: Payment, P Poor efficacy of residual chlorine disinfectant in drinking water to inactivate waterborne pathogens in distribution systems. Canadian Journal of Microbiology. 45: Reed W., Carroll, J., Agramonte, A Yellow fever. American Medicine Association 2: Rodo, X., et al ENSO and cholera: a nonstationary link related to climate change? Proceedings of the National Academy of Sciences of the United States of America. 99: Rogers, D. J. and Randolph, S. E The global spread of malaria in a future, warmer world. Science. 289: Rose, J. B.,et al Climate variability and change in the United States: potential impacts on water- and foodborne diseases caused by microbiologic agents. Environmental Health Perspectives. 109(Suppl 2): Semenza, J.C., McCullough, J.E., Flanders, W.D., McGeehin, M.A., Lumpkin, J.R. 1999, Excess hospital admissions during the July 1995 heat wave in Chicago. American Journal of Preventive Medicine. 16: Watts D.M., Burke D.S., Harrison B.A., Whitmire R.E., Nisalak A Effect of temperature on the vector efficiency of Aedes aegypti for dengue 2 virus. American Journal of Tropical Hygiene, 36: Watts, D. M., et al Effect of temperature on the vector efficiency of Aedes aegypti for dengue 2 virus. American Journal of Tropical Medicine & Hygiene. 36:

48 Weisskopf, M.G., et al Heat wave morbidity and mortality, Milwaukee, Wis, 1999 vs 1995: an improved response? American Journal of Public Health. 92: World Health Organization (WHO) Climate change and Human Health- Risk and Responses (Summary), Geneva: WHO. WHO Using climate to predict infectious disease outbreak: A review. Geneva: WHO. WHO Zhou, C. and Shu H. 2000, Environmental change of Taiwan and the assessment of vulnerability to the impacts of global change-climate. Taipei: National Science Council.,, 1997, 16 (6): ( ) Kaoksiung Journal of Medical Science 5:

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