Epidemiological modelling to address burden of hepatitis B in resource poor settings: Impact & cost-effectiveness of intervention strategies

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Hepatitis B (HBV) is a virus which can cause liver damage and liver cancer if left untreated. In the developing world, in particular in sub-Saharan Africa (SSA), although up to 15% of the population are estimated to be chronically infected with the virus, free treatment is not universally available. Tenofovir is a safe & effective drug which is used to treat HBV in the developed world and is now is also routinely available for use in HIV treatment programmes in developing countries. A recent 5 year research platform called PROLIFICA (Prevention of Liver Fibrosis and Cancer in Africa), funded by the EU, has been set up in West Africa to screen the population for hepatitis B carriers (who often have no symptoms), and offer treatment if needed, with the main aim of reducing liver cancer and death due to HBV, in West Africa. It is also looking at various epidemiological, biological and genetic factors involved in the development of liver cancer in the West African population.Since HBV, is often, a slowly progressing chronic disease, the actual impact of interventions to reduce HBV morbidity and mortality can takes decades to assess by following clinical observation cohorts. Epidemiological models are therefore, a useful tool in public health to use current knowledge of how a disease progresses, to project the likely impact of interventions on controlling the disease and its related mortality. Delaying interventions until full outcomes are available can miss a vital opportunity to help those already afflicted by the disease. Although epidemiological models for HBV exist, they mostly apply to high/middle income countries, countries with lower prevalence of HBV, have too simplistic model structures and don't evaluate the effect of community based screening. Therefore, their use in projecting disease control strategies in SSA, is limited.I aim to develop a model for HBV, specifically applicable to resource-poor countries and use this model, to predict the impact of various interventions including screening & treatment programmes. The hypothesis is that early intervention should reduce primary liver cancer and death due to HBV. Initial methods include reviewing published literature on the natural history of HBV and the probabilities of developing different stages of the disease. Computer based programming techniques will be employed to generate disease transmission models. Limited published data exists on how the Hepatitis B virus behaves in the African population. Therefore, data derived as part of the PROLIFICA programme, can be inputted to make this model applicable to the West African population.In countries, where budgets are limited, it is not sufficient to just demonstrate that clinical interventions are effective against a disease, but that they also represent value for money. I therefore propose to explore whether this strategy is cost effective. Again, analyses exist, but mainly in high-income countries, and vary in medications used. Using locally applicable data on costs, both to the health care provider and to the households, these economic analyses will provide key information for health policy makers. As liver cancer due to HBV, in West Africa, often occurs in males in their 30s-40s, loss to the economy is potentially underestimated by traditional CE analyses, which are routinely used in the western world.Results from this research, will be important in informing health policy makers, like WHO, and funding agencies, like the Global Fund, into the immense public health importance of providing treatment (like that offered in PROLIFICA) free for patients suffering from HBV, in the developing world, to prevent premature death and suffering due to HBV. While initially focusing on HBV in West Africa, the research will develop a model that can be adjusted to be applicable in other countries with varying prevalence of hepatitis B and costs.