Modelling homogeneous regions of social vulnerability to malaria in Rwanda

Type Journal Article - Geospatial health
Title Modelling homogeneous regions of social vulnerability to malaria in Rwanda
Author(s)
Volume 11
Issue 1s
Publication (Day/Month/Year) 2016
Page numbers 129-146
URL http://geospatialhealth.net/index.php/gh/article/view/404/445
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.

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