Modelling homogeneous regions of social vulnerability to malaria in Rwanda

Geospat Health. 2016 Mar 31;11(1 Suppl):404. doi: 10.4081/gh.2016.404.

Abstract

Despite the decline in malaria incidence due to intense interventions, potentials for malaria transmission persist in Rwanda. To eradicate malaria in Rwanda, strategies need to expand beyond approaches that focus solely on malaria epidemiology and also consider the socioeconomic, demographic and biological/disease-related factors that determine the vulnerability of potentially exposed populations. This paper analyses current levels of social vulnerability to malaria in Rwanda by integrating a set of weighted vulnerability indicators. The paper uses regionalisation techniques as a spatially explicit approach for delineating homogeneous regions of social vulnerability to malaria. This overcomes the limitations of administrative boundaries for modelling the trans-boundary social vulnerability to malaria. The utilised approach revealed high levels of social vulnerability to malaria in the highland areas of Rwanda, as well as in remote areas where populations are more susceptible. Susceptibility may be due to the populations' lacking the capacity to anticipate mosquito bites, or lacking resilience to cope with or recover from malaria infection. By highlighting the most influential indicators of social vulnerability to malaria, the applied approach indicates which vulnerability domains need to be addressed, and where appropriate interventions are most required. Interventions to improve the socioeconomic development in highly vulnerable areas could prove highly effective, and provide sustainable outcomes against malaria in Rwanda. This would ultimately increase the resilience of the population and their capacity to better anticipate, cope with, and recover from possible infection.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Susceptibility*
  • Humans
  • Incidence
  • Malaria / epidemiology*
  • Models, Theoretical*
  • Population Dynamics
  • Risk Assessment
  • Risk Factors
  • Rwanda / epidemiology
  • Social Environment
  • Socioeconomic Factors
  • Vulnerable Populations*