ArticleScientific reports2019
Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers.
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30 citing papers in PubMed.
- Bayesian modelling of spatio-temporal dynamics for early-warning and control of severe malaria in Cameroon.Parasite epidemiology and control · 2026Article
- Modelling the impact of climate variability on malaria morbidity in the Tamale Metropolitan Area: a time series analysis.BMC infectious diseases · 2026Article
- Climate change and malaria control in Africa: country experiences and strategic responses.Malaria journal · 2026Article
- Hydroclimatic extremes indexed by SPI and malaria case dynamics in Oyo State, Nigeria: evidence for lagged, site-specific effects.Journal of water and health · 2026Article
- Spatio-temporal modelling and prediction of Anopheles mosquito abundance in Tanga and Unguja, Tanzania: climatic drivers and insights for malaria early warning and vector control strategies.Malaria journal · 2026Article
- Application of a Temporal Fusion Transformer and Long-Term Climate and Disease Data to Assess the Predictive Power and Understand the Drivers for Malaria and Dengue.International journal of environmental research and public health · 2026Article
- Climate-driven malaria mortality among children in malaria-endemic areas of Uganda.BMC public health · 2025Article
- Potential of coconut oil as a mosquito repellent.Tropical medicine and health · 2025Article
- Artificial intelligence in epidemic watch: revolutionizing infectious diseases surveillance.Frontiers in digital health · 2025Review
- Advancing Early Warning Systems for Malaria: Progress, challenges, and future directions - A scoping review.PLOS global public health · 2025Article
- Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso.International journal of environmental research and public health · 2024Article
- Host Preferences and Impact of Climate on Blood Feeding inTropical medicine and infectious disease · 2024Article
- Spatiotemporal patterns and association with climate for malaria elimination in Lao PDR: a hierarchical modelling analysis with two-step Bayesian model selection.Malaria journal · 2024Article
- Fine-Scale Spatial Prediction on the Risk ofJournal of Korean medical science · 2024Article
- Exploring malaria prediction models in Togo: a time series forecasting by health district and target group.BMJ open · 2024Article
- Utilizing a novel high-resolution malaria dataset for climate-informed predictions with a deep learning transformer model.Scientific reports · 2023Article
- Nonlinear and Multidelayed Effects of Meteorological Drivers on Human Respiratory Syncytial Virus Infection in Japan.Viruses · 2023Article
- Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province.Parasitology research · 2023Article
- Machine learning based efficient prediction of positive cases of waterborne diseases.BMC medical informatics and decision making · 2023Article
- Climate variability, socio-economic conditions and vulnerability to malaria infections in Mozambique 2016-2018: a spatial temporal analysis.Frontiers in public health · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r > 0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r > 0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.
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