Comparison of ARIMA and FB-Prophet time series models for the prediction of national and regional malaria incidence in Uganda
Time series models accurately predicted malaria incidence on a national and regional scale in Uganda. Both the ARIMA and FB-Prophet models have the potential to guide malaria resource allocation and response efforts among other malaria control interventions deployed in Uganda and possibly in other malaria endemic settings.
Authors
- Andrew Bakainaga
- Josh M. Colston (ORCID: https://orcid.org/0000-0003-4567-5813)
- Benjamin Fuller (ORCID: https://orcid.org/0000-0001-6450-0088)
- Richard Ssekitoleko (ORCID: https://orcid.org/0000-0001-7631-6122)
- Issa Makumbi (ORCID: https://orcid.org/0000-0003-3579-2485)
- Christopher C. Moore (ORCID: https://orcid.org/0000-0003-4649-0511)
- Caroline Kyozira
- Herbert Isabirye Kiirya
Institutions
- University of Virginia Health System (US)
- Ministry of Health (UG)
- Infectious Diseases Institute (UG)
- World Health Organization - Uganda (UG)
- University of Virginia (US)
Publication Details
- Journal
- Malaria Journal
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1186/s12936-025-05547-8
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00