Determinants of Population Variability in HIV across West Africa: Ecological and Mathematical Modelling Analyses.
Prudden, HJ; (2016) Determinants of Population Variability in HIV across West Africa: Ecological and Mathematical Modelling Analyses. PhD thesis, London School of Hygiene & Tropical Medicine. DOI: 10.17037/PUBS.02634790
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Introduction: Mathematical models of HIV transmission have played an important role in helping to understand the drivers of the HIV epidemic, and shape the global HIV response. The underlying approaches, assumptions and structures used in HIV modelling have the potential to fundamentally influence the conclusions of any modelling analyses. For this reason, it is important that approaches to modelling HIV transmission in different contexts carefully consider how best to ‘characterise’ a populations distribution of risk and networks of sexual interaction based on data, and the implications of incorporating different levels of epidemiological complexity into their modelling. Across West Africa there are substantial variations in population HIV prevalence - ranging from 0.5-6%. To date, there has been limited exploration of the potential factors influencing this population variation. This PhD aims to inform our understanding of the determinants of population variations in HIV prevalence across West Africa, using a combination of ecological analysis of population data, and both simple and more complex epidemiological modelling. The findings are used both to explore the determinants of HIV transmission across West Africa, and to discuss the implications for future modelling and epidemic appraisal approaches. Methods: A range of modelling and epidemiological analytical approaches were used. Firstly, an existing policy model, The Modes of Transmission (MoT) model, designed to predict patterns of HIV incidence, was revised and re-parameterised using data from Nigeria, to explore the effect on overall conclusions of adding additional heterogeneity into the model, and considering more explicitly how to model HIV risk amongst lower-risk subgroups. Secondly, population data from 13 West African countries were compiled. Linear regression analyses were used to assess potential relationships between HIV prevalence in high-risk groups and population HIV prevalence and the size of high-risk population subgroups and HIV prevalence in the general population. Based on the findings from the MoT and ecological analysis, a dynamic deterministic model was developed to explore the variations in HIV prevalence across West Africa. The population model not only included sex work, client and general population sub-groups, but also included a category of adolescent females (15-24) and a category of males with multiple sexual partners, with a mixing formulation being used to vary the degree the adolescent females form partnerships with clients of female sex workers and the subgroup of males who have multiple partnerships Input parameters were sampled from ranges relevant for West Africa, using Latin Hypercube sampling. The model was fitted to equilibrium prevalence in the general population. Results: A critique and revisions to the MoT, identified high levels of infections in previously unrecognised subgroups. These included 16% of new infections occurring in young females engaging in transactional sex. Findings from the ecological analysis, showed that across West Africa HIV prevalence in FSWs and their clients is not associated with higher HIV prevalence in the general population. Instead, the size of groups of males and females with multiple partners is correlated with higher HIV prevalence levels. The deterministic model generated 11000 fits. Grouping fits, based on epidemic size (with 1% incremental increases from 0-6%), the findings revealed that population sizes of key subgroups is the predominant driver of the epidemic. For epidemics where prevalence is less than 3%, FSW population size is the most important determinant of HIV prevalence. For epidemics above 3%, it is the size of the group of adolescent females with multiple partners and their level of interaction with clients of FSWs that is the most significant variable related to higher HIV prevalence. When the limiting effects on HIV transmission of male circumcision are removed from the model, the findings are less clear, with both sex work and the role of adolescent females with multiple partners being important determinants of the epidemic. Circumcision is however shown to significantly limit the magnitude of an epidemic and epidemic categorisation should account for these variations accordingly. Conclusions: Behavioural heterogeneity has long been recognised as an important component of model development. The results from this thesis show the importance of carefully considering how to compartmentalise population HIV models. Even for simple static models, the inclusion of additional subgroups change model conclusions and suggests different intervention priorities. The use of results and findings from ecological analyses, whilst unable to provide strong evidence of causality, can provide useful insights into the relationship between population level factors or behavioural variables and HIV prevalence in the general population. These findings may then be used to inform model development. Deterministic dynamic modelling used in this thesis demonstrates that the size and sexual networks of vulnerable subgroups in the population may be of key importance in determining levels of HIV epidemics in West Africa. In-particular, adolescent females engaging in noncommercial multiple partnerships, often associated with transactional exchange are an important determinant of the HIV epidemic in West Africa. An improved understanding of this group, their size and motivations for engaging in multiple partnerships, through the use of epidemic mapping techniques and social research, will be important to future HIV intervention activities.
|Contributors:||Watts, C (Thesis advisor);|
|Faculty and Department:||Faculty of Public Health and Policy > Dept of Global Health and Development|
|Funders:||UKaid from the Department for International Development (STRIVE)|
|Copyright Holders:||Holly Prudden|
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