Spatial prediction of malaria prevalence in Papua New Guinea: a comparison of Bayesian decision network and multivariate regression modelling approaches for improved accuracy in prevalence prediction.

Cleary, Eimear; Hetzel, Manuel W; Siba, Peter M; Lau, Colleen L; Clements, Archie C A

Cleary, Eimear; Hetzel, Manuel W; Siba, Peter M; Lau, Colleen L; Clements, Archie C A.

Affiliation

Cleary E; Research School of Population Health, Australian National University, Canberra, Australia. eimear.cleary@nuigalway.ie.
Hetzel MW; Swiss Tropical and Public Health Institute, Basel, Switzerland. manuel.hetzel@swisstph.ch.
Siba PM; University of Basel, Basel, Switzerland. manuel.hetzel@swisstph.ch.
Lau CL; Papua New Guinea Institute of Medical Research, Goroka, Papua New Guinea.
Clements ACA; Centre for Health Research and Diagnostics, Divine Word University, Madang, Papua New Guinea.

Malar J ; 20(1): 269, 2021 Jun 13.

Article in En | MEDLINE | ID: mdl-34120604

Subject(s)

Data Accuracy; Malaria, Falciparum/epidemiology; Malaria, Vivax/epidemiology; Spatial Analysis; Bayes Theorem; Decision Support Techniques; Humans; Multivariate Analysis; Papua New Guinea/epidemiology; Plasmodium vivax; Prevalence; Regression Analysis

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Full text: 1 Database: MEDLINE Main subject: Malaria, Vivax / Malaria, Falciparum / Spatial Analysis / Data Accuracy Type of study: Diagnostic_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Malar J Journal subject: MEDICINA TROPICAL Year: 2021 Type: Article Affiliation country: Australia

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