Vladimir Zah, Mondher Toumi

To model the budget and survival impact of implementing interventions to increase the proportion of HIV infections detected early in a given UK population. A Microsoft Excel decision model was designed to generate a set of outcomes for a defined population. Survival was modeled on the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) study extrapolated to a 5-year horizon as a constant hazard. Hazard rates were specific to age, sex, and whether detection was early or late. The primary outcomes for each year up to 5 years were: annual costs, numbers of infected cases, hospital admissions, and surviving cases. Three locations in the UK were chosen to model outcomes across a range of HIV prevalence areas: Lambeth, Southwark, and Lewisham (LSL), Greater Manchester Cluster (GMC), and Kent and Medway (K&M). In LSL, the projected cumulative cost savings over 5 years were £3,210,206 or £5,290,206 when including the value of the 104 life-years saved. Savings were insensitive to transmission rates, but sensitive in direct proportion to the percentage shift from late to early detection. In GMC, savings were in a similar proportion to LSL, but the magnitude was smaller, as a consequence of the lower base-case HIV prevalence. In K&M, with a smaller population and lower HIV prevalence than GMC, savings were commensurately smaller (£733,202 cumulatively over 5 years). The results strengthen the rationale for implementing increased testing in high prevalence areas. However, in areas of low prevalence, it is unlikely that costs will be returned over a 5-year period.