Malaria and lymphatic filariasis (LF) cause the largest public health burden of all vector-borne diseases worldwide. Some 350-500 million clinical episodes and 1 million deaths each year are caused by malaria, of which approximately 60% and 80% respectively occur in Africa. More than 50 million people are also thought to be infected with lymphatic filariasis in 39 endemic countries in sub-Saharan Africa, with approximately 14.6 million individuals living in these endemic countries estimated to suffer from the two major filarial debilitating conditions, lymphodema or hydrocele. These two infections are co-endemic in large parts of Africa and are transmitted by the same vector, namely the Anopheles mosquito. The overall aim of the PhD was to develop a framework which could be used to evaluate the economic costs and benefits of different control strategies for reducing or eliminating the transmission of LF and malaria in Africa and, in particular, considering whether integrated control could offer a more effective approach for disease control. This problem was split into three key areas: 1) Mapping the geographic distribution of malaria and LF infection in Africa and identifying areas where the infections are co-endemic. Initially a maximum entropy modelling approach was used to identify areas at risk of LF based on environmental factors and population density. Then, a Bayesian spatial modelling approach was used to map the prevalence of malaria and LF in Africa, to estimate the number of people infected, and to identify areas of co-endemicity. 2) Developing a combined malaria-LF transmission model for humans and mosquitoes. This involved integrating a LF transmission model into a malaria transmission model. Interactions between the infections were captured using the model, specifically the increase in vector mortality as a result of LF larvae infection, and alterations in the host immune response as a result of co-infection. The model was used to investigate how the presence of one infection affected the prevalence of the other. 3) Finally, performing an economic evaluation of the economic costs and benefits of different control strategies, focusing on the potential for an integrated control approach. The economic benefits of the two primary control approaches (long lasting insecticidal nets for malaria and mass drug administration for LF) were modelled for a range of different scenarios using the co-infection model. The benefit of a control strategy was defined as the financial cost of the resulting reduction in treatment costs and work days lost due to infection and disease. The cost-benefit analysis was used to identify the optimal control strategy for different infection prevalence scenarios and the results were combined with the maps created in 1) to produce maps showing the optimal control strategy for different regions of Africa.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:575996 |
| Date | January 2012 |
| Creators | Slater, Hannah Claire |
| Contributors | Michael, Edwin |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/11643 |
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