Machine learning insights on the effectiveness of non-pharmaceutical interventions against COVID-19 in Nigeria
Public transport restrictions and workplace closures correlated with reductions in the number of cases and deaths. These findings can guide future pandemic responses to enhance favourable public health outcomes.
Authors
- Afolabi Owoloye (ORCID: https://orcid.org/0000-0003-2446-4769)
- Kolapo Oyebola (ORCID: https://orcid.org/0000-0002-1003-2570)
- Blessing Erinwusi (ORCID: https://orcid.org/0000-0002-3920-7610)
- Funmilayo C. Ligali (ORCID: https://orcid.org/0009-0007-6114-6715)
- Babatunde Lawal Salako (ORCID: https://orcid.org/0000-0002-0963-7302)
- Adesola Z. Musa (ORCID: https://orcid.org/0009-0006-6331-0040)
- Oluwagbemiga O Aina
Institutions
- Mountain Top University (NG)
- Institute for Biomedicine (IT)
- Nigerian Institute of Medical Research (NG)
Publication Details
- Journal
- International Health
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1093/inthealth/ihae065
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Bill and Melinda Gates Foundation
- African Academy of Sciences
- National Institutes of Health
- Fogarty International Center