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. 2015 Mar 26;10(3):e0119944.
doi: 10.1371/journal.pone.0119944. eCollection 2015.

Bayesian mapping of HIV infection among women of reproductive age in Rwanda

François Niragire  1 , Thomas N O Achia  2 , Alexandre Lyambabaje  3 , Joseph Ntaganira  4
Affiliations

Bayesian mapping of HIV infection among women of reproductive age in Rwanda

François Niragire et al. PLoS One. .

Abstract

HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

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Conflict of interest statement

Competing Interests: The authors received funding from the Consortium for Advanced Research Training in Africa (CARTA), a program of the African Population and Health Research Centre (APHRC), a non-commercial organisation based in Nairobi, Kenya, East Africa. Among donors to CARTA program there is Google.org. Google.org is the charitable arm of Google that was founded in October 2005, and is noncommercial. For further details, one can visit the website of the Google.org: https://www.google.org/. Therefore there are no concerns regarding the declared no competing interests. The authors confirm that the funders of CARTA program, particularly Google.org does not alter adherence to all PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. District codes and levels of HIV prevalence among women (15–49 years) in Rwanda.
Fig 2
Fig 2. Posterior mean of the unadjusted structured (A) and total (B) spatial effects.
Fig 3
Fig 3. Maps of 95% (A) and 80% (B) posterior probabilities for the unadjusted total spatial effects.
Fig 4
Fig 4. Effect of woman's age with pointwise 95% and 80% credible intervals.
Fig 5
Fig 5. Posterior mean of the adjusted structured (A) and unstructured (B) spatial effects.
See this image and copyright information in PMC

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