Influence of climatic variations on dengue fever incidence in Eastern Thailand

Abstract

This study explored the relationship between meteorological factors and dengue fever incidence in Eastern Thailand from 2013 to 2024. This study used secondary data from the Thai Meteorological Department and the Bureau of Epidemiology, spanning the period from 2013 to 2024. Data for seven provinces in Eastern Thailand including Chanthaburi, Chachoengsao, Chonburi, Trat, Prachinburi, Rayong, and Sa Kaeo were analyzed. Climatic variables (precipitation, relative humidity, minimum and maximum temperatures, and the number of rainy days) were obtained from the Thai Meteorological Department, while dengue fever case data were sourced from the Bureau of Epidemiology. The analysis focused on identifying the temporal associations between climate variability and dengue incidence. Stepwise multiple linear regression was applied to examine the influence of climatic factors on dengue fever, with the model accounting for variations in temperature, humidity, rainfall, and rainy days. Stepwise multiple linear regression analysis revealed that average minimum temperature, average maximum temperature, and relative humidity were significant predictors of dengue incidence. The minimum temperature had the strongest positive effect, suggesting that warmer nights promote mosquito survival and virus transmission. High daytime temperatures and humidity were found to reduce mosquito activity and breeding suitability. The model accounted for 14.2% of the variance in dengue incidence, indicating the need for further consideration of other factors like urbanization and public health interventions. These findings emphasize the importance of integrating meteorological data into early warning systems and developing climate-sensitive prevention strategies.