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 socioeconomically 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.

Characteristics and Population Size Estimation of Female Sex Workers in Bhutan

“…15 Overestimation is due to negative dependence (e.g., those receiving the object avoid participating in the survey); underestimation is due to positive dependence (e.g., those receiving the object are also more likely to participate in the survey). The multiple sample capture-recapture method can adjust for nonindependence, 18 but samples sizes were too small within each district. Finally, our estimate of FSW among the WHR is vulnerable to social desirability response bias with the questionnaire, with possible underreporting of sex work.…”

“…1, detailed hereinafter) 12–15 . Methods were key informant mapping, 16 census and enumeration, 17 unique object multiplier, 13–15 and multiple sample capture-recapture 18 . Results of the several methods were synthesized using a Bayesian approach called the anchored multiplier 19,20 .…”

“…[12][13][14][15] Methods were key informant mapping, 16 census and enumeration, 17 unique object multiplier, [13][14][15] and multiple sample capture-recapture. 18 Results of the several methods were synthesized using a Bayesian approach called the anchored multiplier. 19,20 Using a proxy indicator of the urban adult male population, linear regression was used to extrapolate from the empirical estimates of the 9 study districts to estimates for all 20 districts of Bhutan.…”

“…[13][14][15] The estimate is given by the formula: population size = number of objects distributed/proportion who report receiving the object, with the 95% confidence interval (CI) calculation as for capturerecapture methods. 18 Two weeks before the census and enumeration, outreach workers distributed a distinct key chain to as many WHR they encountered. In the community-based survey (during the first capture), respondents were asked if they had received the key chain.…”

Modeling COVID-19 Contact-Tracing Using the Ratio Regression Capture–Recapture Approach

“…Evaluating completeness of surveillance systems using capture-recapture methods is nowadays an established and accepted method. A recent example on HIV surveillance is given in Wesson et al (2018). Also, capture-recapture methods are now widely applied in the social and medical sciences, beyond their origin in ecology and wildlife (McCrea and Morgan, 2015;Böhning et al, 2018), although applications in medicine have a long tradition (McKendrick, 1926).…”