Estimating the Threshold Effects of Climate on Dengue: A Case Study of Taiwan
Open Access
- 21 February 2020
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 17 (4), 1392
- https://doi.org/10.3390/ijerph17041392
Abstract
Climate change is regarded as one of the major factors enhancing the transmission intensity of dengue fever. In this study, we estimated the threshold effects of temperature on Aedes mosquito larval index as an early warning tool for dengue prevention. We also investigated the relationship between dengue vector index and dengue epidemics in Taiwan using weekly panel data for 17 counties from January 2012 to May 2019. To achieve our goals, we first applied the panel threshold regression technique to test for threshold effects and determine critical temperature values. Data were then further decomposed into different sets corresponding to different temperature regimes. Finally, negative binomial regression models were applied to assess the non-linear relationship between meteorological factors and Breteau index (BI). At the national level, we found that a 1°C temperature increase caused the expected value of BI to increase by 0.09 units when the temperature is less than 27.21 °C, and by 0.26 units when the temperature is greater than 27.21 °C. At the regional level, the dengue vector index was more sensitive to temperature changes because double threshold effects were found in the southern Taiwan model. For southern Taiwan, as the temperature increased by 1°C, the expected value of BI increased by 0.29, 0.63, and 1.49 units when the average temperature was less than 27.27 °C, between 27.27 and 30.17 °C, and higher than 30.17 °C, respectively. In addition, the effects of precipitation and relative humidity on BI became stronger when the average temperature exceeded the thresholds. Regarding the impacts of climate change on BI, our results showed that the potential effects on BI range from 3.5 to 54.42% under alternative temperature scenarios. By combining threshold regression techniques with count data regression models, this study provides evidence of threshold effects between climate factors and the dengue vector index. The proposed threshold of temperature could be incorporated into the implementation of public health measures and risk prediction to prevent and control dengue fever in the future.This publication has 47 references indexed in Scilit:
- Spatial Analysis of Dengue Fever in Guangdong Province, China, 2001-2006Asia Pacific Journal of Public Health, 2013
- The Incubation Periods of Dengue VirusesPLOS ONE, 2012
- Effects of Extreme Precipitation to the Distribution of Infectious Diseases in Taiwan, 1994–2008PLOS ONE, 2012
- Climate-Based Models for Understanding and Forecasting Dengue EpidemicsPLoS Neglected Tropical Diseases, 2012
- Ecological factors associated with dengue fever in a central highlands Province, VietnamBMC Infectious Diseases, 2011
- Dengue, Urbanization and Globalization: The Unholy Trinity of the 21st CenturyTropical Medicine and Health, 2011
- Lagged temperature effect with mosquito transmission potential explains dengue variability in southern Taiwan: Insights from a statistical analysisScience of The Total Environment, 2010
- A spatio-temporal climate-based model of early dengue fever warning in southern TaiwanStochastic Environmental Research and Risk Assessment, 2010
- Aedes aegyptiLarval Indices and Risk for Dengue EpidemicsEmerging Infectious Diseases, 2006
- Tests of Hypotheses in Overdispersed Poisson Regression and other Quasi-Likelihood ModelsJournal of the American Statistical Association, 1990