Evidence map›Paper›PMID 34098626›Full record

ArticleEpidemiology and health2021

Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior.

Oluyemi A Okunlola, Oyetunde T Oyeyemi, Adewale F Lukman

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Article in Epidemiology and health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

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11citing papers in PubMed, 1 pooled it
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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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11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Oluyemi A OkunlolaDepartment of Mathematics, University of Medical Sciences, Ondo, Nigeria.
Oyetunde T OyeyemiDepartment of Biological Sciences, University of Medical Sciences, Ondo, Nigeria.
Adewale F LukmanDepartment of Physical Sciences, Landmark University, Omu-Aran, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate malaria transmission in relation to insecticide-treated net (ITN) coverage in Nigeria.

methodsWe used an exploratory analysis approach to evaluate variation in malaria transmission in relation to ITN distribution in 1,325 Demographic and Health Survey clusters in Nigeria. A Bayesian spatial generalized linear mixed model with a Leroux conditional autoregressive prior for the random effects was used to model the spatial and contextual variation in malaria prevalence and ITN distribution after adjusting for environmental variables.

resultsSpatial smoothed maps showed the nationwide distribution of malaria and ITN. The distribution of ITN varied significantly across the 6 geopolitical zones (p<0.05). The North-East had the least ITN distribution (0.196±0.071), while ITN distribution was highest in the South-South (0.309±0.075). ITN coverage was also higher in rural areas (0.281±0.074) than in urban areas (0.240±0.096, p<0.05). The Bayesian hierarchical regression results showed a non-significant negative relationship between malaria prevalence and ITN coverage, but a significant spatial structured random effect and unstructured random effect. The correlates of malaria transmission included rainfall, maximum temperature, and proximity to water.

conclusionsReduction in malaria transmission was not significantly related to ITN coverage, although much could be achieved in attempts to curtail malaria transmission through enhanced ITN coverage. A multifaceted and integrated approach to malaria control is strongly advocated.

Indexed as

Bayes TheoremChild, PreschoolDemographyFemaleHumansInfantInsecticide-Treated BednetsLinear ModelsMalariaMaleNigeriaPrevalenceSpatial AnalysisBayesian hierarchical regressionInsecticide-treated netMalaria transmission controlNigeriaSpatial smoothed maps

Identifiers

PMID34098626
PMCPMC8510838

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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.