Evaluating the Completeness of HIV Surveillance Using Capture–Recapture Models, Alameda County, California

  • Paul Wesson
  • Richard Lechtenberg
  • Arthur Reingold
  • Willi McFarland
  • Neena Murgai
Original Paper

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.

Keywords

Human immunodeficiency virus (HIV) Surveillance Population size estimation Capture–recapture Bayesian modeling 

Supplementary material

10461_2017_1883_MOESM1_ESM.docx (65 kb)
Supplementary material 1 (DOCX 64 kb)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.University of California, BerkeleyBerkeleyUSA
  2. 2.Alameda County Public Health DepartmentOaklandUSA
  3. 3.University of California, San Francisco, Center for AIDS Prevention Studies/Prevention Research CenterSan FranciscoUSA
  4. 4.San Francisco Department of Public HealthSan FranciscoUSA

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