Abstract
BackgroundIn Thailand, dengue fever is one of the most well-known public health problems. The objective of this study was to examine the epidemiology of dengue and determine the seasonal pattern of dengue and its associate to climate factors in Bangkok, Thailand, from 2003 to 2017.MethodsThe dengue cases in Bangkok were collected monthly during the study period. The time-series data were extracted into the trend, seasonal, and random components using the seasonal decomposition procedure based on loess. The Spearman correlation analysis and artificial neuron network (ANN) were used to determine the association between climate variables (humidity, temperature, and rainfall) and dengue cases in Bangkok.ResultsThe seasonal-decomposition procedure showed that the seasonal component was weaker than the trend component for dengue cases during the study period. The Spearman correlation analysis showed that rainfall and humidity played a role in dengue transmission with correlation efficiency equal to 0.396 and 0.388, respectively. ANN showed that precipitation was the most crucial factor. The time series multivariate Poisson regression model revealed that increasing 1% of rainfall corresponded to an increase of 3.3% in the dengue cases in Bangkok. There were three models employed to forecast the dengue case, multivariate Poisson regression, ANN, and ARIMA. Each model displayed different accuracy, and multivariate Poisson regression was the most accurate approach in this study.ConclusionThis work demonstrates the significance of weather in dengue transmission in Bangkok and compares the accuracy of the different mathematical approaches to predict the dengue case. A single model may insufficient to forecast precisely a dengue outbreak, and climate factor may not only indicator of dengue transmissibility.
Highlights
In Thailand, dengue fever is one of the most well-known public health problems
The Bureau of Epidemiology (BoE) published the data on its website and within the Annual Epidemiological Surveillance Reports (AESRs)
The results show that the importance of independent variables of climate factors to dengue cases
Summary
In Thailand, dengue fever is one of the most well-known public health problems. Dengue fever is one of the most common infectious diseases in Thailand and one of the top threats to global public health. If persons get infected with different serotypes (secondary infection), the risk of developing severe dengue is increasing. The mosquito, Ae. aegypti and Ae. albopictus, are the main vector of the dengue virus and mainly feed on human blood [1]. The World Health Organization suggests that the vaccine only be provided to persons who have exposures previously to dengue virus [4]. The number of Dengue cases is likely to increase in the future because of several factors such as climate change, globalization, development of the virus, insufficient political and economic supports, and limited resources for effective control measures
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