'Mobile men with money': HIV prevention and the erasure of difference

Glob Public Health. 2014;9(3):257-70. doi: 10.1080/17441692.2014.889736. Epub 2014 Mar 4.

Abstract

Mobile Men with Money is one of the latest risk categories to enter into HIV prevention discourse. Used in countries in Asia, the Pacific and Africa, it refers to diverse groups of men (e.g. businessmen, miners and itinerant wage labourers) who, in contexts of high population movement and economic disparity, find themselves at heightened risk of HIV as members of a 'most-at-risk population', or render others vulnerable to infection. How adequate is such a description? Does it make sense to develop HIV prevention programmes from such understandings? The history of the epidemic points to major weaknesses in the use of terminologies such as 'sex worker' and 'men who have sex with men' when characterising often diverse populations. Each of these terms carries negative connotations, portraying the individuals concerned as being apart from the 'general population', and posing a threat to it. This paper examines the diversity of men classified as mobile men with money, pointing to significant variations in mobility, wealth and sexual networking conducive to HIV transmission. It highlights the patriarchal, heteronormative and gendered assumptions frequently underpinning use of the category and suggests more useful ways of understanding men, masculinity, population movement, relative wealth in relation to HIV vulnerability and risk.

MeSH terms

  • Commerce / economics
  • Commerce / statistics & numerical data
  • Female
  • HIV Infections / epidemiology
  • HIV Infections / prevention & control*
  • HIV Infections / transmission
  • Humans
  • Income / statistics & numerical data
  • Male
  • Men's Health / economics
  • Men's Health / statistics & numerical data*
  • Risk-Taking
  • Sex Workers / statistics & numerical data*
  • Sexual Behavior / statistics & numerical data*
  • Transients and Migrants / statistics & numerical data*
  • Travel / economics
  • Travel / statistics & numerical data*
  • Unsafe Sex / statistics & numerical data
  • Workforce