This year saw the announcement of the ambitious aim of ending the HIV epidemic by 2030 from UNAIDS. To meet this ambitious goal, a renewed commitment to the prevention of new HIV infections will be essential to stop further expansion of the epidemic. The growing array of prevention tools available must be utilised efficiently, and the core principles of a targeted and strategic combination prevention response revisited in order to ensure the greatest impact possible is generated. This thesis uses mathematical modelling to answer some of the key questions in HIV prevention programming with a view to increasing the efficiency of the response. The role of different prevention modalities in an optimised combination prevention programme is examined to understand how they can be best applied. Increasing data on the epidemic suggest that it is highly diverse across populations and settings, both in its magnitude and drivers, and also in the intensity of the response, and this provides a blueprint for designing a more strategic and tailored prevention strategy. Epidemiological and programmatic information is used to develop a geographically focused approach to prevention programming, which can generate considerably greater impact through being responsive to local epidemiology and directing funds to populations and locations where they can have greatest impact. How best to set local targets for prevention and monitor the response in light of the local characteristics of the epidemic is also investigated. We also examine how the pattern of funding available to policymakers shapes prevention programmes, and we find greater ‘front-loading’ of investment is needed to maximise impact. In this way, key strategies for improving the impact of investments are identified which can be used to inform the future of HIV prevention.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:745220 |
| Date | January 2015 |
| Creators | Anderson, Sarah-Jane |
| Contributors | Hallett, Timothy ; Ward, Helen |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/59953 |
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