Mathematical modelling approaches to optimising the allocation of limited HIV resources

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Copyright: Shattock, Andrew
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Abstract
By the end of 2015, 35 million individuals had died from illnesses related to Acquired Immunodeficiency Syndrome (AIDS) since the start of the global epidemic in the 1970’s. An estimated 37 million people were living with Human Immunodeficiency Virus (HIV); the virus that causes AIDS, with 2.1 million infected in 2015 alone. Large amounts of resources have been invested in the global HIV/AIDS response, with an estimated 19 billion USD spent in low- and middle-income countries in 2015. However, with ambitious targets to control the global epidemic by 2030, resource gaps are still substantial in many countries. In this context, it is of fundamental importance that resources be spent efficiently to achieve maximum impact. Mathematical modelling has been applied to forecast global and national disease burdens of HIV, establish the expected impact of prevention and treatment programs, and provide policy-makers with quantitative evidence to design the most effective epidemic responses. Recently, models have attempted to assess allocative efficiency by employing optimisation algorithms to identify priority programs to scale-up and associated program coverage targets. Such models have been used to identify the maximum impact of likely future resources, and to determine the minimum costs of achieving strategic targets. In this thesis we apply and extend such approaches to: 1) identify general principles for efficiently allocating resources in concentrated epidemics, 2) illustrate how allocative efficiencies can be synergistically combined with implementation and technical efficiencies to achieve desirable outcomes, 3) illustrate how the optimal timing of HIV program implementation can result in epidemiological gains in a generalised epidemic setting, and 4) describe how resources can be optimally allocated across service delivery models of HIV testing, linkage, care, and treatment-related programs to achieve desirable clinical outcomes. The results presented in this thesis illustrate how substantial epidemiological gains can be attained by targeting limited resources to the right population groups with the right programs at the right time through the right service delivery approaches. These findings enhance the knowledge base of HIV allocative efficiency and provide policy-makers with both high-level and finely granulated insights to make informed allocation decisions with available resources.
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Author(s)
Shattock, Andrew
Supervisor(s)
Gray, Richard
Wilson, David
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Publication Year
2017
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
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