Simulation Modeling and Forecasting of Dengue Spread using Agent-based Modeling

Abstract

Dengue Fever a “mosquito-borne” viral disease is also known as “break bone Fever”, with the symptoms of sudden commencement of fever (for>3 days and <10 days), aches, nausea, severe joints pain, rashes, leukopenia (Platelets<150,000), and thrombocytopenia. It is instigated by one of four Dengue viruses or serotypes (belonging to Flavivirus group), DENV-1, DENV-2, DENV 3 and DENV-4. It is challenging to control and prevent epidemic disease such as dengue in Pakistan because of its complex dynamics. There is a need to develop a simulation framework that models the population dynamics of both humans and mosquitoes and their interactions to analyze the transmissibility and forecast the spread of dengue disease in a given area. This research work is based on computational epidemiology, in which we aim to explore the mathematical model SEIR, across space and time. Our goal is to develop an Agent-based simulation model, based on a mathematical framework of SEIR (Susceptible, Exposed, Infectious, Recovered), compute the vector density based on the reproductive behavior of vector, by studying the complex dynamics of existing epidemic disease to simulate the spread of Dengue Fever. The simulation results with respect to real data are analyzed. Through vector density estimation and the rate of disease transmission, we aim to generate graphs that can be used for forecasting and analyzing the dengue outbreak risks. The graph peaks identify the expected Dengue cases and their direction of spread, which eventually detect epidemic outbreaks. We have proposed a framework that provides visualization and forecasting capabilities and flexibility to modeler to add features that assist stakeholders to study the epidemiology of the region to make prediction. This simulation tool can be used to help the Public Health field to formulate and apply different strategies to cater the risk of Dengue in regions with a high prevalence of Aedes Aegypti and dengue virus infection.