Detect Climatic Factors Contributing to Dengue Outbreak based on Wavelet, Support Vector Machines and Genetic Algorithm

摘要

Dengue Fever, existing throughout the contemporary history of mankind, poses an endemic threat to most tropical regions. Dengue virus is transmitted to humans mainly by the Aedes Aegypti mosquito. It has been observed that there are significantly more Aedes Aegypti mosquitoes present in tropical areas than in other climate areas. As such, it is commonly believed that the tropical climate suits the life-cycle of the mosquito. Thus, studying the correlation between the climatic factors and trend of dengue cases is helpful in conceptualising a more effective pre-emptive control measure towards dengue outbreak. In this paper, we proposed to use Wavelet transformation for data pre-processing before employing a Support Vector Machines (SVM)-based Genetic Algorithm to select the most important features. After which, regression based on SVM is used to perform forecasting of the model. The analytical result drawn from this model based on dengue data in Singapore shows improvement in prediction performance of dengue cases ahead. This can help the health control agency to improve its strategic planning for disease control to combat dengue outbreak. The experimental result arising from this model also suggests strong correlation between the monsoon seasonality and dengue virus transmission. It also confirms with previous work that mean temperature and monthly seasonality have minimal contribution to the outbreak.