DEVELOPING A TWO DIMENSIONAL CLIMATE RISK MODEL FOR DENGUE DISEASE TRANSMISSION IN URBAN COLOMBO

Dengue has been a major public health concern in the tropical world for decades now. The dynamics of dengue disease transmission are complex and uncertain due to various external factors such as climate, human behavior, geography and demography. Fuzzy logic and fuzzy set theory are useful tools in mathematics to model systems under uncertainty where classical approaches are insucient. We are particularly concerned with modeling the potential risk of dengue disease transmission with respect to climate variables namely, rainfall and temperature. We define fuzzy membership functions for rainfall and temperature which describe the levels of unfavorable conditions to spread dengue. Then a modified version of the Einstein Sum Operator is used to measure the overall effect from rainfall and temperature; hence we obtain a fuzzy valued time series of potential risk produced by the climate. This risk measure is validated with the actual dengue cases reported in urban Colombo from year 2006 to 2015. The residuals of the predicted and the real risk of dengue transmission is less than 0.4 (80% accurate) in 86.77% of the time considered to the study. The sensitivity analysis of the model is also carried out to investigate how it responses to the measurement errors in the climate parameters.