An Analysis of Connectivity Between Dengue Cases and Climate Factors in Sri Lanka Based on Field Data

Abstract

Dengue is the most critical mosquito-borne viral disease that has rapidly spread within recent years. Understanding of the seasonal pattern of dengue cases and relationship with climate data could be useful in deciding control mechanisms. In this study, monthly dengue cases, average rainfall data, average temperature data and relative humidity data of each province in Sri Lanka from 2010 to 2019 have been analyzed to identify the periodic pattern and the delayed effect of climate factors on dengue cases. First, we have used the Fast Fourier Transform (FFT) to identify the periodic patterns of dengue cases and climate data. Next, we have used the Pearson’s correlation coefficient to find the time delay between climate data and dengue cases. The results reflected that out of nine provinces, dengue cases in Western, Central, Southern, North Western and North Central provinces are influenced by both monsoon seasons. Moreover, in Western, Southern, North Western, Sabaragamuwa, Northern and Eastern provinces, periodic pattern of dengue cases follows the periodic pattern of the rainfall data with two months time delay. The delayed effect of average temperature on dengue cases is three months and that of relative humidity is one/two months. These results could be used in health planning during the outbreaks.