Evidence map›Paper›PMID 39152481›Full record

ArticleMalaria journal2024

Application of multivariate binary logistic regression grouped outlier statistics and geospatial logistic model to identify villages having unusual health-seeking habits for childhood malaria in Malawi.

Gracious A Hamuza, Emmanuel Singogo, Tsirizani M Kaombe

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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 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Gracious A HamuzaNational Statistical Office of Malawi, Zomba, Malawi. gahamuza@gmail.com.
Emmanuel SingogoUniversity of North Carolina Project, Lilongwe, Malawi.
Tsirizani M KaombeDepartment of Mathematical Sciences, School of Natural and Applied Sciences, University of Malawi, Zomba, Malawi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly diagnosis and prompt treatment of malaria in young children are crucial for preventing the serious stages of the disease. If delayed treatment-seeking habits are observed in certain areas, targeted campaigns and interventions can be implemented to improve the situation.

methodsThis study applied multivariate binary logistic regression model diagnostics and geospatial logistic model to identify traditional authorities in Malawi where caregivers have unusual health-seeking behaviour for childhood malaria. The data from the 2021 Malawi Malaria Indicator Survey were analysed using R software version 4.3.0 for regressions and STATA version 17 for data cleaning.

resultsBoth models showed significant variability in treatment-seeking habits of caregivers between villages. The mixed-effects logit model residual identified Vuso Jere, Kampingo Sibande, Ngabu, and Dzoole as outliers in the model. Despite characteristics that promote late reporting of malaria at clinics, most mothers in these traditional authorities sought treatment within twenty-four hours of the onset of malaria symptoms in their children. On the other hand, the geospatial logit model showed that late seeking of malaria treatment was prevalent in most areas of the country, except a few traditional authorities such as Mwakaboko, Mwenemisuku, Mwabulambya, Mmbelwa, Mwadzama, Zulu, Amidu, Kasisi, and Mabuka.

conclusionsThese findings suggest that using a combination of multivariate regression model residuals and geospatial statistics can help in identifying communities with distinct treatment-seeking patterns for childhood malaria within a population. Health policymakers could benefit from consulting traditional authorities who demonstrated early reporting for care in this study. This could help in understanding the best practices followed by mothers in those areas which can be replicated in regions where seeking care is delayed.

Indexed as

MalariaPatient Acceptance of Health CareAdolescentAdultChildChild, PreschoolFemaleHumansInfantLogistic ModelsMalawiMaleYoung AdultCaregiver treatment-seeking habitChildhood malariaGeoSpatial statisticsMalawi malaria indicator survey dataMixed-effects logistic regression diagnosticsOutlier traditional authorities

Identifiers

PMID39152481
PMCPMC11328507

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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.