Estimating the Number of HIV+ Latino MSM Using RDS, SS-PSE, and the Census

TL;DR

This paper introduces a novel method combining RDS data, census, and LGBT population data to estimate the size of hidden populations like Latino MSM, avoiding unreliable community size estimates.

Contribution

The paper develops a new model that integrates multiple data sources with SS-PSE to accurately estimate hidden population sizes without relying on RDS-derived community size estimates.

Findings

Successfully estimated Latino MSM populations in Chicago and San Francisco.

Demonstrated the model's ability to use living situation data for population size estimation.

Provided a framework applicable to other hidden populations.

Abstract

This paper presents a method for estimating the overall size of a hidden population using results from a respondent driven sampling (RDS) survey. We use data from the Latino MSM Community Involvement survey (LMSM-CI), an RDS dataset that contains information collected regarding the Latino MSM communities in Chicago and San Francisco. A novel model is developed in which data collected in the LMSM-CI survey serves as a bridge for use of data from other sources. In particular, American Community Survey Same-Sex Householder data along with UCLA's Williams Institute data on LGBT population by county are combined with current living situation data taken from the LMSM-CI dataset. Results obtained from these sources are used as the prior distribution for Successive-Sampling Population Size Estimation (SS-PSE) - a method used to create a probability distribution over population sizes. The strength of our model is that it does not rely on estimates of community size taken during an RDS survey, which are prone to inaccuracies and not useful in other contexts. It allows unambiguous, useful data (such as living situation), to be used to estimate population sizes.