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Estimating the economic impacts of climate change on infectious diseases: a case study on dengue fever in Taiwan

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Abstract

Researchers of climate change have suggested that climate change and variability has a significant influence on the epidemiology of infectious diseases, particularly vector-borne diseases. The purpose of this study is to explore how climate conditions and the dengue fever epidemic in Taiwan are related and to estimate the economic impact of climate change on infectious diseases. To achieve these objectives, two different methods, one involving the Panel data model and the other the Contingent Valuation Method (CVM), are applied in this study. At first, we use the Panel data model to assess the relationship between climate conditions and the number of people infected by dengue fever during the period from January 2000 to February 2006 in 308 cities and townships in the Taiwan. The results of the empirical estimation indicate that climate conditions have an increasingly significant impact on the probability of people being infected by dengue fever. The probability of being infected by dengue fever due to climate change is then calculated and is found to range from 12% to 43% to 87% which represent low, mid, and high probabilities of infection caused by climate change when the temperature is increased by 1.8°C. The respondent’s willingness to pay (WTP) is also investigated in the survey using the single-bounded dichotomous choice (SBDC) approach, and the results show that people would pay NT$724, NT$3,223 and NT$5,114 per year in order to avoid the increased probabilities of 12%, 43%, and 87%, respectively, of their being infected with dengue fever.

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References

  • Alberini A (1995) Estimating the willingness-to-pay model of discrete choice contingent valuation survey data. Land Econ 71(1):83–95

    Article  Google Scholar 

  • Amemiya T (1971) The estimation of the variances in a variance-components model. Int Econ Rev 12:1–13

    Article  Google Scholar 

  • Baltagi BH (2001) Econometric analysis of panel data. Wiley, Chichester, 2001

    Google Scholar 

  • Bancroft TL (1906) On the etiology of dengue fever. Australas M Gaz 25:17

    Google Scholar 

  • Bishop RC, Heberlein TA (1979) Measuring values of extramarket goods: are indirect measures biased? Am J Agric Econ 61(5):926–930

    Article  Google Scholar 

  • Cameron TA, James MD (1987a) Efficient estimation methods for closed-ended contingent valuation surveys. Rev Econ Stat 69:269–276

    Article  Google Scholar 

  • Cameron TA, James MD (1987b) Estimating willingness to pay from survey data: an alternative pre-test-market evaluation procedure. J Mark Res 24:389–395

    Article  Google Scholar 

  • Chang NT (1996) Occurrence and prevention of mosquito-borne disease of dengue fever. Dissertations in the 8th Workshop on Preventive Technology in Vector-borne Diseases by the EPA, 67–80

  • Chen LT (1997) A study on the willingness-to-pay and consumption decisions for organic vegetables in Taiwan. Department of Agricultural Economics, National Chung-Hsing University, Master’s Thesis

  • Davis RK (1963) Recreational planning as an economic problem. Nat Resour J 3(2):239–249

    Google Scholar 

  • Githeko AK, Lindsay SW, Confalonieri U, Patz J (2000) Climate change and vector-borne diseases: a regional analysis. Bull WHO 78(9):1136–1147

    Google Scholar 

  • Goldberg I, Roosen J (2007) Scope insensitivity in health risk reduction studies: a comparison of choice experiments and the contingent valuation method for valuing safer food. J Risk Uncertain 34:123–144

    Article  Google Scholar 

  • Graham H (1903) The dengue: a study of its pathology and mode of propagation. J Trop Med 6:209–214

    Google Scholar 

  • Gubler DJ (1986) Dengue fever. San Juan, Puerto Rico: San Juan Laboratories, Dengue Branch, Division of Vector-borne Viral Disease, Center for Infectious Diseases, 233–240

  • Hales S, de Wet NA, Maindonald J, Woodward A (2002) Potential effect of population and climate changes on global distribution of dengue fever: an empirical model. Lancet 360:830–834

    Article  Google Scholar 

  • Hwang JS (1991) Ecology of Aedes mosquitoes and their relationships with dengue epidemics in the Taiwan area. Chinese J Entomol, Special Publ 6:105–127

    Google Scholar 

  • Hwang KP (1997) Dengue fever and dengue hemorrhagic fever. J Formos Med Assoc 1(1):50–56

    Google Scholar 

  • Jacobs RJ, Moleski RJ, Meyerhoff AS (2002) Valuation of symptomatic hepatitis a in adults: estimates based on time trade-off and willingness-to-pay measurement. Pharmacoeconomics 20(11):739–747

    Article  Google Scholar 

  • Johnson FR, Manjunath R, Mansfield C, Clayton LJ, Hoerger TJ, Zhang I (2006) High-risk individuals’ willingness to pay for diabetes risk-reduction programs. Diabetes Care 29:1351–1356

    Article  Google Scholar 

  • Kleinman L, McIntosh E, Ryan M, Schmier J, Crawley J, Locke GR, de Lissovoy G (2002) Willingness to pay for complete symptom relief of gastroesophageal reflux disease. Arch Intern Med 162:1361–1366

    Article  Google Scholar 

  • Ko YC (1989) Epidemiology of dengue fever in Taiwan. Kaohsiung J Med Sci 5:1–11

    Google Scholar 

  • Koopman JS, Prevots DR, Miguel A et al (1991) Determinants and predictors of dengue infection in Mexico. Am J Epidemiol 133:1168–1178

    Google Scholar 

  • Miu TS, Lang SJ (1960) Ecological studies on the mosquitoes in Taipei. J Taiwan Norm Univ 5:9–49

    Google Scholar 

  • Nerlove M (1971) A note on error components models. Econometrica 39:383–396

    Article  Google Scholar 

  • Real Climate (2005) Comments. Retrieved July 5, 2006, from http://www.realclimate.org/index.php?p=142

  • Reiter P (2001) Climate change and mosquito-borne disease. Environ Health Perspect 109(1):141–161

    Article  Google Scholar 

  • Sauerborn R, Gbangou A, Dong H, Przyborski JM, Lanzer M (2005) Willingness to pay for hypothetical malaria vaccines in rural Burkina Faso. Scand J Public Health 33(2):146–150

    Google Scholar 

  • Tsai HT, Liu TM (2005) Effects of global climate change on disease epidemics and social instability around the world. Human Security and Climate Change 21–23

  • Wallace TD, Hussain A (1969) The use of error components models in combining cross-section and time-series data. Econometrica 37:55–72

    Article  Google Scholar 

  • Wang CH, Chen HL (1997) The influence of climate warming on the prevalence of dengue fever in Taiwan. Chinese J Pub Health 16(6):455–465

    Google Scholar 

  • World Health Organization, Geneva (1998) Dengue in WHO Western Pacific Region. Wkly Epidemiol Rec 73(36):273–277

    Google Scholar 

  • Wu PI, Hsieh WH (1995) Estimating the demand function of environmental goods: a comparative analysis in a closed-ended contingent valuation model. Taiwan Agric Econ Rev 1(1):1–46

    Google Scholar 

  • Yeung R, Abdullah AS, McGhee SM, Hedley AJ (2005) Willingness to pay for preventive travel health measures among Hong Kong Chinese residents. J Travel Med 12(2):66–71

    Google Scholar 

Download references

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Correspondence to Chi-Chung Chen.

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This work is supported in part by the Ministry of Education, Taiwan, R.O.C. under the ATU plan.

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Tseng, WC., Chen, CC., Chang, CC. et al. Estimating the economic impacts of climate change on infectious diseases: a case study on dengue fever in Taiwan. Climatic Change 92, 123–140 (2009). https://doi.org/10.1007/s10584-008-9437-6

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  • DOI: https://doi.org/10.1007/s10584-008-9437-6

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