What do women in the highest malaria burden country know about ways to prevent malaria? A multi-level analysis of the 2021 Nigeria Malaria Indicator Survey data DOI Creative Commons
Chimezie Igwegbe Nzoputam, Oluwakemi Christie Ogidan, Amadou Barrow

et al.

Malaria Journal, Journal Year: 2024, Volume and Issue: 23(1)

Published: Nov. 28, 2024

Language: Английский

Application of Machine Learning Models in Predicting Malaria Prevalence in Nigeria: An Analysis of the 2015-2020 Demographic and Health Surveys DOI
Thecla Okeahunwa Ayoka, Charles O. Nnadi

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Malaria is a major public health problem, especially in sub-Saharan Africa and other developing countries, where majority of malaria cases deaths occur. This study developed machine learning (ML) model to accurately diagnose rural communities Nigeria, based on patients’ symptoms clinical information, using low-cost readily available diagnostic tools. The was trained 2020 Nigerian Demographic Health Surveys (NDHS) Program Geospatial Covariate datasets containing information patients Nigeria. ML approaches were preferred over traditional statistical methods due their ability handle high-dimensional, non-linear relationships interactions among diverse set variables. Regression based-algorithms used identify predict patterns as continuous outcome allowing finer-grained spatial demographic insights than binary classification would predict. models underwent rigorous validation cross holdout testing assess generalizability minimize overfitting. closeness the predicted incidence scores experimental indicates robustness model. coefficient determination Random Forest Regressor (RFR), Multiple Linear (MLR), Ridge 0.9937, 0.9916, 0.9924 respectively for test set. demonstrates competence models' prediction abilities. RFR model's curve results showed recurring pattern. performance dataset consistently improved volume data increased. By shifting from reactive diagnostics proactive risk prediction, authorities can more effectively allocate resources, improve intervention timing, reach underserved with precision.

Language: Английский

Citations

0

What do women in the highest malaria burden country know about ways to prevent malaria? A multi-level analysis of the 2021 Nigeria Malaria Indicator Survey data DOI Creative Commons
Chimezie Igwegbe Nzoputam, Oluwakemi Christie Ogidan, Amadou Barrow

et al.

Malaria Journal, Journal Year: 2024, Volume and Issue: 23(1)

Published: Nov. 28, 2024

Language: Английский

Citations

0