Open AccessImproving Underestimation of HIV Prevalence in Surveys Using Time-Location Sampling
Author(s) -
Ana B. Barros,
Maria do Rosário Oliveira Martins
Publication year - 2020
Publication title -
journal of urban health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.211
H-Index - 92
eISSN - 1468-2869
pISSN - 1099-3460
DOI - 10.1007/s11524-019-00415-8
Subject(s) - percentile , logistic regression , human immunodeficiency virus (hiv) , demography , sampling (signal processing) , statistics , men who have sex with men , population , medicine , geography , environmental health , mathematics , computer science , virology , filter (signal processing) , syphilis , sociology , computer vision
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.