Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions

Ann Epidemiol. 2016 Aug;26(8):557-569. doi: 10.1016/j.annepidem.2016.06.004. Epub 2016 Jun 15.

Abstract

In the context of generalized human immunodeficiency virus (HIV) epidemics, there has been limited recent investment in HIV surveillance and prevention programming for key populations including female sex workers. Often implicit in the decision to limit investment in these epidemic settings are assumptions including that commercial sex is not significant to the sustained transmission of HIV, and HIV interventions designed to reach "all segments of society" will reach female sex workers and clients. Emerging empiric and model-based evidence is challenging these assumptions. This article highlights the frameworks and estimates used to characterize the role of sex work in HIV epidemics as well as the relevant empiric data landscape on sex work in generalized HIV epidemics and their strengths and limitations. Traditional approaches to estimate the contribution of sex work to HIV epidemics do not capture the potential for upstream and downstream sexual and vertical HIV transmission. Emerging approaches such as the transmission population attributable fraction from dynamic mathematical models can address this gap. To move forward, the HIV scientific community must begin by replacing assumptions about the epidemiology of generalized HIV epidemics with data and more appropriate methods of estimating the contribution of unprotected sex in the context of sex work.

Keywords: Generalized HIV epidemics; HIV; Mathematical models; Population attributable fraction; Sex work; Sub-Saharan Africa.

Publication types

  • Review

MeSH terms

  • Africa South of the Sahara / epidemiology
  • Communicable Disease Control / methods*
  • Evidence-Based Medicine
  • Female
  • HIV Infections / prevention & control*
  • HIV Infections / transmission*
  • Health Promotion / organization & administration
  • Humans
  • Models, Theoretical
  • Needs Assessment
  • Prevalence
  • Risk Assessment
  • Sex Workers*
  • Sexual Behavior
  • Unsafe Sex / statistics & numerical data*