Evaluating the completeness of hiv surveillance using capture– recapture models, alameda county, california

Abstract

HIV prevalence in Alameda County (including Oakland) is among the highest in California, yet the case registry may under-appreciate the full burden of disease. Using lists from health care facilities serving socioeco-nomically diverse populations and the HIV surveillance list, we applied capture–recapture methods to evaluate the completeness of the surveillance system by estimating the number of diagnosed people living with HIV and seeking care in Alameda County in 2013. Of the 5376 unique individuals reported from the lists, 397 were missing from the surveillance list. Models projected the total population size to be 5720 (95% CI 5587–6190), estimating the surveillance system as 87% complete. Subgroup analyses identified groups facing a disproportionate burden of HIV as more likely to be detected by the surveillance list. The Alameda County HIV surveillance system reports a high proportion of persons diagnosed with HIV within the jurisdiction. Capture–recapture analysis can help track progress towards maximizing engagement in HIV care.