Agent-based modeling and simulation of the transmission dynamics of malaria.

Date

4-2011

Degree

Bachelor of Science in Applied Physics

College

College of Arts and Sciences (CAS)

Adviser/Committee Chair

Hannah Rissah E. Forio

Co-adviser

Vachel Gay V. Paller

Abstract

The transmission dynamics of malaria was studied and implemented using Agent-Based Modeling Simulation (ABMS) based on the SEIR-SE1 model (also known as SEIRS model). The human population was divided into four disease states, namely: susceptible (SO; exposed (Eh); infectious (1h); and recovered (Rh). The mosquito disease states were divided in the same manner except that there was no recovered state. Due to a shorter lifespan, the mosquitoes were classified as infectious until they die. The parameters used in the study were based on the malaria model by Chitnis (2005). However, due to the limitations of the program two of the parameters were not considered, namely: biting rate and death due to the disease. The data generated from the program were compared to results from previous works. Results from the ABMS showed behavior similar to that obtained in the approach using ordinary differential equations. It was observed that prevalence of malaria decreased the number of susceptible individuals. Eventually the number of infectious individuals decreased. These individuals recovered and acquired immunity. As a consequence, the disease did not stay in the population for a long time. Prevention measures were simulated by varying the probabilities of transmission of infection which are parameters important to the spread and control of the disease. It was shown that decreasing the probability of transmission of infection decreases the number of infectious humans.

Language

English

Location

UPLB Main Library Special Collections Section (USCS)

Call Number

Thesis

Document Type

Thesis

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