Is the HIV burden in India being overestimated?

BACKGROUND The HIV burden estimate for India has a very wide plausibility range. A recent population-based study in a south Indian district demonstrated that the official method used in India to estimate HIV burden in the population, which directly extrapolates annual sentinel surveillance data from large public sector antenatal and sexually transmitted infection (STI) clinics, led to a 2-3 times higher estimate than that based on population-based data. METHODS We assessed the generalisability of the reasons found in the Guntur study for overestimation of HIV by the official sentinel surveillance based method: addition of substantial unnecessary HIV estimates from STI clinics, the common practice of referral of HIV positive/suspect patients by private practitioners to public hospitals, and a preferential use of public hospitals by lower socioeconomic strata. We derived conservative correction factors for the sentinel surveillance data and titrated these to the four major HIV states in India (Andhra Pradesh, Maharashtra, Karnataka and Tamil Nadu), and examined the impact on the overall HIV estimate for India. RESULTS HIV data from STI clinics are not used elsewhere in the world as a component of HIV burden estimation in generalised epidemics, and the Guntur study verified that this was unnecessary. The referral of HIV positive/suspect patients from the private to the public sector is a widespread phenomenon in India, which is likely causing an upward distortion in HIV estimates from sentinel surveillance in other parts of India as well. Analysis of data from the nationwide Reproductive and Child Health Survey revealed that lower socioeconomic strata were over-represented among women seeking antenatal care at public hospitals in all major south Indian states, similar to the trend seen in the Guntur study. Application of conservative correction factors derived from the Guntur study reduced the 2005 official sentinel surveillance based HIV estimate of 3.7 million 15-49 years old persons in the four major states to 1.5-2.0 million, which would drop the official total estimate of 5.2 million 15-49 years old persons with HIV in India to 3-3.5 million. CONCLUSION Plausible and cautious extrapolation of the trends seen in a recent large and rigorous population-based study of HIV in a south Indian district suggests that India is likely grossly overestimating its HIV burden with the current official sentinel surveillance based method. This method needs revision.