Open AccessQuantitative, Qualitative and Geospatial Methods to Characterize HIV Risk Environments
Author(s) -
Erin E. Conners,
Brooke S. West,
Alexis M. Roth,
Kristen G. Meckel-Parker,
MeiPo Kwan,
Carlos Magis-Rodriguez,
Hugo Staines-Orozco,
John D. Clapp,
Kimberly C. Brouwer
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0155693
Subject(s) - geospatial analysis , psychological intervention , environmental health , qualitative research , public health , geography , sex work , qualitative property , human immunodeficiency virus (hiv) , medicine , sociology , cartography , computer science , nursing , social science , family medicine , machine learning
Increasingly, ‘place’, including physical and geographical characteristics as well as social meanings, is recognized as an important factor driving individual and community health risks. This is especially true among marginalized populations in low and middle income countries (LMIC), whose environments may also be more difficult to study using traditional methods. In the NIH-funded longitudinal study Mapa de Salud , we employed a novel approach to exploring the risk environment of female sex workers (FSWs) in two Mexico/U.S. border cities, Tijuana and Ciudad Juárez. In this paper we describe the development, implementation, and feasibility of a mix of quantitative and qualitative tools used to capture the HIV risk environments of FSWs in an LMIC setting. The methods were: 1) Participatory mapping; 2) Quantitative interviews; 3) Sex work venue field observation; 4) Time-location-activity diaries; 5) In-depth interviews about daily activity spaces. We found that the mixed-methodology outlined was both feasible to implement and acceptable to participants. These methods can generate geospatial data to assess the role of the environment on drug and sexual risk behaviors among high risk populations. Additionally, the adaptation of existing methods for marginalized populations in resource constrained contexts provides new opportunities for informing public health interventions.