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Protocol for Dengue Infections in Mosquitoes A. aegypti and Infection Phenotype Determination
Published on: July 4, 2007
Estimating dynamics of dengue disease in Colombo district of Sri Lanka with environmental impact by quantifying the
Piyumi Chathurangika1, S S N Perera1, S A Kushani De Silva2
1Research & Development Centre for Mathematical Modeling, Department of Mathematics, Faculty of Science, University of Colombo, Colombo, 00030, Sri Lanka.
Abstract:
Dengue is a vector-borne disease transmitted to humans by vectors of genus Aedes causing a global threat to health, social, and economic sectors in many of the tropical countries including Sri Lanka. In Sri Lanka, the tropical climate, marked by seasonal weather primarily influenced by monsoons, fosters optimal conditions for the virus to spread efficiently. This heightened transmission results in increased per-capita vector density. In this work, we investigate the dynamic influence of environmental conditions on dengue emergence in Colombo district - the geographical region with the highest recorded dengue threat in Sri Lanka. An iterative approach is employed to dynamically estimate dengue cases leveraging the Markov chain Monte Carlo simulations, utilizing the dynamics of four seasons per year influenced by monsoon weather patterns governing in the region. The developed algorithm allows to estimate the risk of dengue outbreaks in 2017 and 2019 with high precision, facilitating accurate forecasts of upcoming disease emergence patterns for better preparedness. The uncertainty quantification not only validated the accuracy of outbreak estimates but also showcased the model's capacity to capture extreme cases and revealed undisclosed external factors such as human mobility and environmental pollution that might affect dengue transmission in the Colombo district of Sri Lanka.
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