Factor Configurations with Governance as Conditions for Low HIV/AIDS Prevalence in HIV/AIDS Recipient Countries: Fuzzy-set Analysis

J Korean Med Sci. 2015 Nov;30 Suppl 2(Suppl 2):S167-77. doi: 10.3346/jkms.2015.30.S2.S167. Epub 2015 Nov 6.

Abstract

This paper aims to investigate whether good governance of a recipient country is a necessary condition and what combinations of factors including governance factor are sufficient for low prevalence of HIV/AIDS in HIV/AIDS aid recipient countries during the period of 2002-2010. For this, Fuzzy-set Qualitative Comparative Analysis (QCA) was used. Nine potential attributes for a causal configuration for low HIV/AIDS prevalence were identified through a review of previous studies. For each factor, full membership, full non-membership, and crossover point were specified using both author's knowledge and statistical information of the variables. Calibration and conversion to a fuzzy-set score were conducted using Fs/QCA 2.0 and probabilistic tests for necessary and sufficiency were performed by STATA 11. The result suggested that governance is the necessary condition for low prevalence of HIV/AIDS in a recipient country. From sufficiency test, two pathways were resulted. The low level of governance can lead to low level of HIV/AIDS prevalence when it is combined with other favorable factors, especially, low economic inequality, high economic development and high health expenditure. However, strengthening governance is a more practical measure to keep low prevalence of HIV/AIDS because it is hard to achieve both economic development and economic quality. This study highlights that a comprehensive policy measure is the key for achieving low prevalence of HIV/AIDS in recipient country.

Keywords: Corruption; Democratic Accountability; Effectiveness of Official Development Assistance; Fuzzy-set Qualitative Comparative Analysis; HIV/AIDS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acquired Immunodeficiency Syndrome / epidemiology*
  • Acquired Immunodeficiency Syndrome / prevention & control
  • Computer Simulation
  • Developing Countries / economics*
  • Developing Countries / statistics & numerical data
  • Economic Development / statistics & numerical data
  • Fraud / economics
  • Fraud / statistics & numerical data*
  • Fuzzy Logic
  • HIV Infections / epidemiology*
  • HIV Infections / prevention & control
  • Humans
  • Models, Statistical
  • Prevalence
  • Risk Factors
  • Socioeconomic Factors