community-driven assessment of antimicrobial misuse and resistance risks in underserved rural communities of northern nigeria
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1 Department of Microbiology, Modibbo Adama University, Yola, Nigeria, NextGen Health Squad, Yola South, Nigeria
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
INTRODUCTION:
Antimicrobial resistance (AMR) is a growing global public health threat, with disproportionate impact in low-resource and underserved communities. In northern Nigeria, limited access to accurate health information, weak regulation of antibiotics, and poor community engagement increase the risk of antimicrobial misuse and resistant infections. Evidence from rural and peri-urban settings remains scarce.
METHODS:
A mixed-method community-based assessment was conducted between 2024 and 2025 in underserved communities in Adamawa State, Nigeria. Data were collected through structured questionnaires, community dialogue sessions, and awareness workshops conducted during World Antimicrobial Awareness Week. Participants included students, community members, and informal healthcare users. Descriptive analysis was used to assess knowledge, attitudes, and practices related to antimicrobial use.
RESULTS:
Findings revealed widespread antimicrobial misuse, including self-medication, incomplete dosage, and antibiotic use without prescription. Awareness of AMR was generally low, particularly in rural communities, despite high exposure to antibiotics. Many participants believed antibiotics could treat viral and non-specific illnesses. Community engagement activities, including peer-led education and student-led AMR clubs, improved short-term awareness and willingness to adopt safer practices.
CONCLUSIONS:
AMR risks in northern Nigeria are amplified by information gaps, weak community-level interventions, and limited surveillance in underserved populations. Community-driven, youth-led approaches offer a scalable pathway to improve antimicrobial awareness and promote responsible use. Strengthening grassroots education, integrating AMR into public health programming, and prioritizing rural data generation are critical to reducing AMR burden in similar low-resource settings.