Advancing antimicrobial stewardship in Africa through responsible artificial intelligence implementation
- 1Department of Pharmacy, Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC)
Abstract
Antimicrobial resistance (AMR) continues to pose a serious threat to global public health, with African healthcare systems carrying a disproportionate burden. Although antimicrobial stewardship programs have been recommended as an important strategy for improving antimicrobial use and slowing the emergence of resistance, implementation across many African healthcare systems continues to face several challenges, including workforce shortages, weak laboratory infrastructure, and poor surveillance systems. Artificial intelligence (AI) and machine learning (ML) have shown promising potential in strengthening antimicrobial stewardship through clinical decision support, resistance prediction, automated surveillance, and data extraction from weak health information systems. However, the application of AI in antimicrobial stewardship across Africa is still at an early stage, with most systems remaining at pilot or research stages. This commentary discusses current opportunities, examines major barriers affecting implementation, and proposes recommendations that may support sustainable integration of AI into antimicrobial stewardship programs across Africa.
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BibTeX
@article{animashaun2026advancing,
title = {{Advancing antimicrobial stewardship in Africa through responsible artificial intelligence implementation}},
author = {Suzan Fikayo Animashaun},
journal = {Discover Public Health},
year = {2026},
month = oct,
doi = {10.1186/s12982-026-03022-6},
url = {https://doi.org/10.1186/s12982-026-03022-6},
note = {CC BY},
}
RIS
TY - JOUR
TI - Advancing antimicrobial stewardship in Africa through responsible artificial intelligence implementation
AU - Suzan Fikayo Animashaun
PY - 2026
DA - 2026/10/25
JO - Discover Public Health
DO - 10.1186/s12982-026-03022-6
UR - https://doi.org/10.1186/s12982-026-03022-6
AB - Antimicrobial resistance (AMR) continues to pose a serious threat to global public health, with African healthcare systems carrying a disproportionate burden. Although antimicrobial stewardship programs have been recommended as an important strategy for improving antimicrobial use and slowing the emergence of resistance, implementation across many African healthcare systems continues to face several challenges, including workforce shortages, weak laboratory infrastructure, and poor surveillance systems. Artificial intelligence (AI) and machine learning (ML) have shown promising potential in strengthening antimicrobial stewardship through clinical decision support, resistance prediction, automated surveillance, and data extraction from weak health information systems. However, the application of AI in antimicrobial stewardship across Africa is still at an early stage, with most systems remaining at pilot or research stages. This commentary discusses current opportunities, examines major barriers affecting implementation, and proposes recommendations that may support sustainable integration of AI into antimicrobial stewardship programs across Africa.
SN - 3005-0774
ER -