Rethinking HIV prevalence determination in developing countries.

The process for HIV prevalence determination using antenatal clinic (ANC) sentinel surveillance data has been plagued by criticisms of its biasness. Exploring other means of HIV prevalence determination is necessary to validate that estimates are near actual values or to replace the current system. We propose a data collection model that leverages the increasing adoption and penetration of the Internet and mobile technology to collect and archive routine data from HIV counseling and testing (HCT) client intake forms from all HCT centers and prevention of mother-to-child transmission (PMTCT) sites in a country. These data will then be mined to determine prevalence rates and risk factors at the community level. The need to improve the method for the generation of HIV prevalence rates has been repeatedly echoed by researchers though no one has been able to fashion out a better and more reliable way to the current ANC sentinel surveillance method at a reasonable cost. The chance of using routinely generated data during HCT and PMTCT is appealing and needs to be envisioned as the technology to achieve this is increasingly becoming available and affordable in countries worst hit by the pandemic. Triangulating data generated from routine HCT and PMTCT sites with data from sentinel surveillance and where the confidence of its quality is assured, as the sole source of HIV prevalence rate determination and behavioral risk assessment will improve the acceptance by communities and drive evidence-based interventions at the community level.