Objective: To introduce the newly developed AVERT model by describing the purpose, logic, advantages and limitations of the model, to validate the model's estimates against seroconversion data from a large randomized controlled trial, and to provide practical examples of its applications.
Design: Static, deterministic spreadsheet-type model based on per sex act HIV-1 transmission probabilities.
Methods: Data from a recently completed trial carried out in Cameroon were used to validate the estimated number of new HIV infections generated by the AVERT model. A relatively limited set of biological and behavioral parameters was used to estimate the impact of a targeted HIV/sexually transmitted disease (STD) prevention intervention in a South African mining community.
Results: The comparison of AVERT estimates with actual seroincidence data from the Cameroon trial not only confirmed the validity of the model's outputs but also illustrated its potential to provide additional options in data analysis. Modeling the pre-and post-intervention scenarios for the South African mining community with AVERT provided estimates of the number of HIV infections averted due to targeted periodic presumptive STD treatment and community-based peer education.
Conclusions: With a small number of accessible input variables, AVERT can provide plausible and defendable impact estimates of intervention effects on the reduction of HIV transmission. The AVERT model may be a helpful tool for decision-makers and planners in setting appropriate program priorities and analysing the cost-effectiveness of different intervention packages.