Antimicrob Resist Infect Control. 2025 Apr 12;14(1):29. doi: 10.1186/s13756-025-01530-9.
ABSTRACT
BACKGROUND: Good quality data is essential in optimising containment strategies for antimicrobial resistance, a global public health threat estimated to cause around 10 million deaths yearly and up-to 5% loss in GDP by 2050 if left unaddressed. The laboratory system plays an important role in the collection of high-quality data as well as ensuring validity, reliability and timeliness of data. However, in many low-medium income countries including Nigeria, the technical capacity of the laboratory for fulfilling these responsibilities is unknown. This paucity of information limits piloting of strategies to complement existing surveillance and planning improvement of subsequent laboratory iterations into the surveillance system. The focus of this study was to assess the gaps, vulnerabilities and enablers of laboratory strengthening processes in the scope of technical capacity for clinical and public health functions and to provide a roadmap for improved surveillance of antimicrobial resistance in Nigeria.
METHODS: A cross-sectional study design utilising structured questionnaire administered online via Qualtrics and reported in accordance with strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Data analysis involved descriptive and inferential statistics as well as bivariate and multivariate logistics to test predictive analysis of relationship between variables.
RESULTS: A total of 302 laboratories completed the questionnaire, 107 (53.4%) government laboratories and 195 (64.6%) private sector laboratories. 18.2% reported excellent knowledge, 25.5% has excellent capacity, 7.3% are fully ready for surveillance, 12.3% are participating in some surveillance, and 1.0% record important microbiological data that correlates with epidemiological information.
CONCLUSION: Tertiary laboratories reported highest performance across all surveillance quality indicators (SQIs). AMR surveillance is skewed toward government and tertiary laboratories, leaving lower-level and rural facilities underutilized despite their potential. This results in missing community-level data and undermines the representativeness of surveillance. The study identifies gaps in recruitment, assessment, and oversight but also offers strategies to address these issues.
PMID:40221775 | DOI:10.1186/s13756-025-01530-9
