ArticleBMC public health2021
Geostatistical modeling of malaria prevalence among under-five children in Rwanda.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Geographic variation in malaria prevalence among children under five in coastal and inland counties of Liberia: analysis of the 2022 Malaria Indicator Survey.Malaria journal · 2026Article
- Prevalence and Determinants of Malaria Among Children Under Five Years in Malaria-Endemic Areas of Mpumalanga Province, South Africa.Global health, epidemiology and genomics · 2026Article
- Spatio-temporal dynamics of malaria incidence in children under five years of age and correlation with meteorological variability in the North and Far North regions of Cameroon between 2015-2022.Parasite epidemiology and control · 2025Article
- Half-decade of scaling up malaria control: malaria trends and impact of interventions from 2018 to 2023 in Rwanda.Malaria journal · 2025Review
- Spatio-temporal dynamics of malaria in Rwanda between 2012 and 2022: a demography-specific analysis.Infectious diseases of poverty · 2024Article
- Modeling the shared risks of malaria and anemia in Rwanda.PloS one · 2024Article
- Comparison of new computational methods for spatial modelling of malaria.Malaria journal · 2023Article
- Spatio-Temporal Bayesian Models for Malaria Risk Using Survey and Health Facility Routine Data in Rwanda.International journal of environmental research and public health · 2023Article
- Climate variability, socio-economic conditions and vulnerability to malaria infections in Mozambique 2016-2018: a spatial temporal analysis.Frontiers in public health · 2023Article
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Abstract
backgroundMalaria has continued to be a life-threatening disease among under-five children in sub-Saharan Africa. Recent data indicate rising cases in Rwanda after some years of decline. We aimed at estimating the spatial variations in malaria prevalence at a continuous spatial scale and to quantify locations where the prevalence exceeds the thresholds of 5% and 10% across the country. We also consider the effects of some socioeconomic and climate variables.
methodsUsing data from the 2014-2015 Rwanda Demographic and Health Survey, a geostatistical modeling technique based on stochastic partial differential equation approach was used to analyze the geospatial prevalence of malaria among under-five children in Rwanda. Bayesian inference was based on integrated nested Laplace approximation.
resultsThe results demonstrate the uneven spatial variation of malaria prevalence with some districts including Kayonza and Kirehe from Eastern province; Huye and Nyanza from Southern province; and Nyamasheke and Rusizi from Western province having higher chances of recording prevalence exceeding 5%. Malaria prevalence was found to increase with rising temperature but decreases with increasing volume for rainfall. The findings also revealed a significant association between malaria and demographic factors including place of residence, mother's educational level, and child's age and sex.
conclusionsPotential intervention programs that focus on individuals living in rural areas, lowest wealth quintile, and the locations with high risks should be reinforced. Variations in climatic factors particularly temperature and rainfall should be taken into account when formulating malaria intervention programs in Rwanda.
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