AnoSpEx: a spatially explicit predictive computational model for studying Anopheles metapopulation dynamics towards malaria control

PhD thesis

Oluwagbemi, O. 2012. AnoSpEx: a spatially explicit predictive computational model for studying Anopheles metapopulation dynamics towards malaria control. PhD thesis Covenant University Department of Computer Science
TypePhD thesis
TitleAnoSpEx: a spatially explicit predictive computational model for studying Anopheles metapopulation dynamics towards malaria control
AuthorsOluwagbemi, O.
Abstract

Anopheles mosquitoes transmit malaria, a major public health problem among many African countries. One of the most effective methods to control malaria is by controlling the Anopheles mosquito vectors that transmit the parasites. Mathematical models have both predictive and explorative utility to investigate the pros and cons of different malaria control strategies. We have developed a C++ based, stochastic spatially explicit model (ANOSPEX; Ano phelesSpatially-Explicit) to simulate Anopheles metapopulation dynamics. The model is biologically rich, parameterized by field data, and driven by field-collected weather data from Macha, Zambia. To preliminarily validate ANOSPEX, simulation results were compared to field mosquito collection data from Macha; simulated and observed dynamics were similar. The ANOSPEX model will be useful in a predictive and exploratory manner to develop, evaluate and implement traditional and novel strategies to control malaria, and for understanding the environmental forces driving Anopheles population dynamics.

KeywordsAnoSpEx; Computational Model; Malaria; Anopheles; Control
Sustainable Development Goals3 Good health and well-being
Middlesex University ThemeHealth & Wellbeing
Department nameDepartment of Computer Science
Institution nameCovenant University
Publication dates
OnlineJan 2013
Publication process dates
Deposited19 Apr 2024
Output statusPublished
Web address (URL)https://eprints.covenantuniversity.edu.ng/1152/
LanguageEnglish
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