Improving underestimation of HIV prevalence in surveys using time-location sampling

Research output: Contribution to journalArticle

Abstract

We sought to find a method that improves HIV estimates obtained through time-location sampling (TLS) used to recruit most-at-risk populations (MARPs). The calibration on residuals (CARES) method attributes weights to TLS sampled individuals depending on the percentile to which their logistic regression residues belong. Using a real country database, provided by EMIS-2010, with 9591 men who have sex with men (MSM) and an HIV prevalence of 12.1%, we simulated three populations (termed "pseudo-populations") with different levels of HIV. From each pseudo-population, 1000 TLS samples were drawn, and the HIV prevalence estimated by the TLS method and by the CARES method were recorded and compared with the HIV prevalence of the 9591 men. Results showed that the CARES method improves estimates given by the TLS method by getting closer to the real HIV prevalence.
Original languageEnglish
Number of pages9
JournalJournal of Urban Health
DOIs
Publication statusE-pub ahead of print - 2 Jan 2020

Keywords

  • CARES
  • HIV
  • Time-location sampling
  • Hidden populations
  • Key populations
  • Most-at-risk populations
  • Weight

UN Sustainable Development Goals (SDGs)

  • SDG 3 - Good Health and Well-Being

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