Evidence map›Paper›PMID 38395876›Full record

ArticleMalaria journal2024

Bayesian spatio-temporal analysis of malaria prevalence in children between 2 and 10 years of age in Gabon.

Fabrice Mougeni, Bertrand Lell, Ngianga-Bakwin Kandala, Tobias Chirwa

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Article in Malaria journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Fabrice MougeniDivision of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg, 2193, South Africa. fabricemougeni@gmail.com.
Bertrand LellCentre de Recherches Médicales de Lambaréné, P.O. Box 242, Lambaréné, Gabon.
Ngianga-Bakwin KandalaDivision of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg, 2193, South Africa.
Tobias ChirwaDivision of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg, 2193, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGabon still bears significant malaria burden despite numerous efforts. To reduce this burden, policy-makers need strategies to design effective interventions. Besides, malaria distribution is well known to be related to the meteorological conditions. In Gabon, there is limited knowledge of the spatio-temporal effect or the environmental factors on this distribution. This study aimed to investigate on the spatio-temporal effects and environmental factors on the distribution of malaria prevalence among children 2-10 years of age in Gabon.

methodsThe study used cross-sectional data from the Demographic Health Survey (DHS) carried out in 2000, 2005, 2010, and 2015. The malaria prevalence was obtained by considering the weighting scheme and using the space-time smoothing model. Spatial autocorrelation was inferred using the Moran's I index, and hotspots were identified with the local statistic Getis-Ord General Gi. For the effect of covariates on the prevalence, several spatial methods implemented in the Integrated Nested Laplace Approximation (INLA) approach using Stochastic Partial Differential Equations (SPDE) were compared.

resultsThe study considered 336 clusters, with 153 (46%) in rural and 183 (54%) in urban areas. The prevalence was highest in the Estuaire province in 2000, reaching 46%. It decreased until 2010, exhibiting strong spatial correlation (P < 0.001), decreasing slowly with distance. Hotspots were identified in north-western and western Gabon. Using the Spatial Durbin Error Model (SDEM), the relationship between the prevalence and insecticide-treated bed nets (ITNs) coverage was decreasing after 20% of coverage. The prevalence in a cluster decreased significantly with the increase per percentage of ITNs coverage in the nearby clusters, and per degree Celsius of day land surface temperature in the same cluster. It slightly increased with the number of wet days and mean temperature per month in neighbouring clusters.

conclusionsIn summary, this study showed evidence of strong spatial effect influencing malaria prevalence in household clusters. Increasing ITN coverage by 20% and prioritizing hotspots are essential policy recommendations. The effects of environmental factors should be considered, and collaboration with the national meteorological department (DGM) for early warning systems is needed.

Indexed as

Insecticide-Treated BednetsMalariaBayes TheoremChildCross-Sectional StudiesGabonHumansPrevalenceSpatio-Temporal AnalysisBayesian analysisEnvironmental factorsINLASmall areaSPDE

Identifiers

PMID38395876
PMCPMC10893641

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.