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

Considerable progress towards controlling malaria has been made in Papua New Guinea through the national malaria control programme's free distribution of long-lasting insecticidal nets, improved diagnosis with rapid diagnostic tests and improved access to artemisinin combination therapy. Predictive prevalence maps can help to inform targeted interventions and monitor changes in malaria epidemiology over time as control efforts continue.

Citation:
Cleary E, Hetzel MW, Siba P, Lau CL, Clements ACA. 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. Malar J. 2021;20(1)

Keywords:
Papua New Guinea; malaria; mapping; Bayesian decision network

Abstract:
Considerable progress towards controlling malaria has been made in Papua New Guinea through the national malaria control programme's free distribution of long-lasting insecticidal nets, improved diagnosis with rapid diagnostic tests and improved access to artemisinin combination therapy. Predictive prevalence maps can help to inform targeted interventions and monitor changes in malaria epidemiology over time as control efforts continue.