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.
