Treat All versus targeted strategies to select HBV-infected people for antiviral therapy in The Gambia, west Africa: a cost-effectiveness analysis.

BACKGROUND: Global elimination of hepatitis B virus (HBV) requires expanded uptake of antiviral therapy, potentially by simplifying testing algorithms, especially in resource-limited countries. We evaluated the effectiveness, cost-effectiveness, and budget impact of three strategies that determine eligibility for anti-HBV treatment, as compared with the WHO 2015 treatment eligibility criteria, in The Gambia. METHODS: We developed a microsimulation model of natural history using data from the Prevention of Liver Fibrosis and Cancer in Africa programme (known as PROLIFICA) in The Gambia, for an HBV-infected cohort of individuals aged 20 years. The algorithms included in the model were a conventional strategy using the European Association for the Study of the Liver (EASL) 2017 criteria, a simplified algorithm using hepatitis B e antigen and alanine aminotransferase (the Treatment Eligibility in Africa for the Hepatitis B Virus [TREAT-B] score), a Treat All approach for all HBV-infected individuals, and the WHO 2015 criteria. Outcomes to measure effectiveness were disability-adjusted life years (DALYs) and years of life saved (YLS), which were used to calculate incremental cost-effectiveness ratios (ICERs) with the WHO 2015 criteria as the base-case scenario. Costs were assessed from a modified social perspective. A budget impact analysis was also done. We tested the robustness of results with a range of sensitiviy analyses including probabilistic sensitivity analysis. FINDINGS: Compared with the WHO criteria, TREAT-B resulted in 4877 DALYs averted and Treat All resulted in 9352 DALYs averted, whereas the EASL criteria led to an excess of 795 DALYs. TREAT-B was cost-saving, whereas the ICER for Treat All (US$2149 per DALY averted) was higher than the cost-effectiveness threshold for The Gambia (0·5 times the country's gross domestic product per capita: $352). These patterns did not change when YLS was the outcome. In a modelled cohort of 5000 adults (aged 20 years) with chronic HBV infection from The Gambia, the 5-year budget impact was $1·14 million for Treat All, $0·66 million for TREAT-B, $1·03 million for the WHO criteria, and $1·16 million for the EASL criteria. Probabilistic sensitivity analysis indicated that among the Treat All, EASL, and TREAT-B algorithms, Treat All would become the most preferred strategy only with a willingness-to-pay threshold exceeding approximately $72 000 per DALY averted or $110 000 per YLS. INTERPRETATION: Although the Treat All strategy might be the most effective, it is unlikely to be cost-effective in The Gambia. A simplified strategy such as TREAT-B might be a cost-saving alternative. FUNDING: UK Research and Innovation (Medical Research Council). TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Estimating the health burden of road traffic injuries in Malawi using an individual-based model.

BACKGROUND: Road traffic injuries are a significant cause of death and disability globally. However, in some countries the exact health burden caused by road traffic injuries is unknown. In Malawi, there is no central reporting mechanism for road traffic injuries and so the exact extent of the health burden caused by road traffic injuries is hard to determine. A limited number of models predict the incidence of mortality due to road traffic injury in Malawi. These estimates vary greatly, owing to differences in assumptions, and so the health burden caused on the population by road traffic injuries remains unclear. METHODS: We use an individual-based model and combine an epidemiological model of road traffic injuries with a health seeking behaviour and health system model. We provide a detailed representation of road traffic injuries in Malawi, from the onset of the injury through to the final health outcome. We also investigate the effects of an assumption made by other models that multiple injuries do not contribute to health burden caused by road accidents. RESULTS: Our model estimates an overall average incidence of mortality between 23.5 and 29.8 per 100,000 person years due to road traffic injuries and an average of 180,000 to 225,000 disability-adjusted life years (DALYs) per year between 2010 and 2020 in an estimated average population size of 1,364,000 over the 10-year period. Our estimated incidence of mortality falls within the range of other estimates currently available for Malawi, whereas our estimated number of DALYs is greater than the only other estimate available for Malawi, the GBD estimate predicting and average of 126,200 DALYs per year over the same time period. Our estimates, which account for multiple injuries, predict a 22-58% increase in overall health burden compared to the model ran as a single injury model. CONCLUSIONS: Road traffic injuries are difficult to model with conventional modelling methods, owing to the numerous types of injuries that occur. Using an individual-based model framework, we can provide a detailed representation of road traffic injuries. Our results indicate a higher health burden caused by road traffic injuries than previously estimated.