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Title: The effects of different deployment strategies of artemisinin combination therapies on slowing down the spread of antimalarial drug resistance : investigation with individual-based simulations
Author: Nguyen, Tran Dang
ISNI:       0000 0004 5991 9089
Awarding Body: Open University
Current Institution: Open University
Date of Award: 2016
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Despite the success of recent global malaria control efforts, which. have halved global malaria mortality since 2000, malaria is still one of the world's most deadly diseases causing an estimated half a million deaths, mostly among African children, and around a quarter of billion clinical episodes every year as reported in 2014 1. Drug resistance is one of the most important challenges to malaria elimination. To contain drug resistance, many efforts have been put forth including improvement of surveillance systems and mass treatment in order. to stop or slow down the transmission of the resistant strain. To find out whether a population-level treatment strategy can have any benefit in containing drug resistance, mathematical models are an appropriate approach to this problem and individual-based models allow us to have a better understanding of the effect of individual heterogeneities on the outcome. The first part of the thesis is about building and validating an individual based microsimulation. The model is implemented as an individual-based discrete-time event simulation model in C++. The behaviors and the state changes of human individuals are determined by relevant events and mathematical formulas. This integrated model combines components that reproduce the most important features of malaria transmission and epidemiology: the infectiousness of human populations; clinical model of acute illness; heterogeneities in individuals' age, biting-rate level, drug absorption, drug action, multiple parasite populations, and human immunity. To validate this individual-based model, two types of validation have been done. The model's parameters were obtained from field or clinical data were used directly in the model. For those parameters that cannot be obtained directly from literature review, sensitivity analysis has been done to find how variation in parameter values affects certain key features of malaria epidemiology .
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available