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

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 1.8A degrees 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

Estimating the Economic Impact of Climate Change on Cardiovascular Diseases—Evidence from Taiwan

“…As another extreme example, Liu et al [18] estimated the WTP to reduce the risk of infection and death from severe acute respiratory syndrome (SARS) in Taiwan and found that the values per statistical life ranged from 3 to 12 million US dollars. Their WTP estimates are higher than those of Tseng et al [11] and this study because of the higher mortality rate associated with SARS. Comparing with other diseases such as the food-borne diseases Campylobacteriosis or Salmonellosis, Goldberg and Roosen [19] applied CVM and found that an individual's WTP ranged from US$2.98 for a risk reduction of 40% for Campylobacteriosis or Salmonellosis to US$5.88 for a risk reduction of 80% for Salmonellosis and a risk reduction of 40% for Campylobacteriosis.…”

“…To estimate the effects of climate change on the mortality of cardiovascular diseases in Taiwan, a two-step estimation approach is applied. Such an estimation procedure is similar to that in the study by Tseng et al [11]. As the first step, the relationship between the number of deaths from cardiovascular diseases and various climatic conditions needs to be established and estimated.…”

Climate Change and Vector-borne Diseases: An Economic Impact Analysis of Malaria in Africa

“…The estimated coefficients give information on the relationship between observed malaria cases, temperature and precipitation. The theoretical model follows the analysis in Li and Racine as well as Tseng et al [28,31] and is specified as follows: $y_{\mathit{\text{it}}}=f(X_{\mathit{\text{it}}})+\beta Z_{\mathit{\text{it}}}+{\alpha }_i+u_{\mathit{\text{it}}},\hspace{0.17em}\hspace{0.17em}t=1,\hspace{0.17em}\dots ,\hspace{0.17em}T\hspace{0.17em}\text{and}\hspace{0.17em}i=1,\hspace{0.17em}\dots ,N$where y it is the natural log of the number of reported malaria cases per 1,000 people in country i at time period t; X it is a vector of climate variables that includes temperature, precipitation and a measure of climate variability; Z it is a vector of socio-economic control variables that includes population density, per capita gross domestic product, inequality index, per capita healthcare expenditure and number of hospital beds per 1,000 people; α i are unobserved individual country effects and u it is an idiosyncratic error term. The function f , the coefficients β and the unobserved country effects α i are all parameters to be estimated.…”

Willingness to Pay for Ancillary Benefits of Climate Change Mitigation

“…Recent studies using SP methods to assess the WTP of the general population for the total economic value of climate change mitigation policies include Berk and Fovell (1999), Roe et al (2001), Berrens et al (2004), Li et al (2004), Nomura and Akai (2004), Li et al (2005), Hidano and Kato (2007), Longo et al (2008) and Tseng et al (2009). All of these studies have focused on the global benefits of GHG emissions reductions, and none of them has looked at ancillary benefits induced by climate change policies.…”