Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613450
Title: Agent based modelling of Malaria
Author: Rowlands, Jessica S.
Awarding Body: Prifysgol Bangor University
Current Institution: Bangor University
Date of Award: 2013
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Abstract:
Malaria is a disease that affects millions of people each year, with 90% of deaths occurring in Africa alone. The subject of this dissertation is the agent based modelling of malaria in populations that are suffering mass migration , living in unsanitary conditions or undergoing other effects of impoverished circumstances. The research is important due to the large numbers of people affected by malaria globally, with about 3.3 billion at risk. A large proportion of those exposed to the risk live in Sub-Saharan African countries. Agent based modelling is a type of computational modelling which is commonly used for the simulation of interacting, autonomous agents. Using agent based modelling it is possible to assess the effects of interactions between individual agents and populations of agents on the whole system. There is a limited availability of associated documentation and quantifiable research data in many areas of malaria spread research. To address the problem, three models have been built that investigate different aspects of malaria transmission. The models are developed with flexibility and adaptability as important factors in their use, so that they can provide verifiable results with potentially limited availability of data. The three models produced are as follows. • Malaria in Displaced Populations. • Malaria in Peri-Urban Settlements. • Malaria and Human Immunodeficiency Virus (HIV) Dual Infection. The first model simulates malaria spread amongst a migratory population of agents. The second model simulates malaria spread amongst a settled population of agents living in peri-urban conditions with an associated mapping.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.613450  DOI: Not available
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