Data Sheet 1_Antimicrobial resistance and microbiological gap analysis for central nervous system-assocaited bacterial pathogens in Nigeria.docx

Background

Despite extensive vaccination efforts, central nervous system (CNS) infections remain a significant cause of morbidity and mortality in the African meningitis belt. This burden is increasingly complicated by the rising antimicrobial resistance (AMR) in pathogens not covered by the available vaccines. We mapped pathogen-specific AMR profiles and diagnostic gaps in CNS bacterial pathogens to inform precise microbiology-based interventions for improved surveillance and empiric therapy in Nigeria.

Methods

We conducted a retrospective analysis of a three-year national AMR surveillance data, focusing on CNS bacterial pathogens. Data from 25 sentinel laboratories were extracted, analysed and interpreted per CLSI/GLASS standards. AMR profiles and diagnostic gaps were assessed using descriptive statistics and Chi-square tests for demographic and temporal comparisons.

Results

Among 84,548 valid cultures from over 26,000 patients, culture positivity rate was higher in females (35.1%) compared to males (28.3%, p < 0.001) and higher among older adults (>65 years, 40.0%, p < 0.001). CSF specimens were underrepresented, while species-level ambiguity was high for CNS-associated infections. Staphylococcus aureus (31.3%), Escherichia coli (20%), and Klebsiella species (12%) were the dominant isolates, while Pseudomonas aeruginosa (3.5%) and Acinetobacter species (0.6%) showed persistent low-level presence. High levels of penicillin resistance were observed in Streptococcus pneumoniae across the study years, culminating at 100% in 2018. Other pathogens, including Klebsiella species, E. coli, and P. aeruginosa, showed high AMR across multiple drug classes. Gap analysis scored all CNS-associated bacterial pathogens at maximum clinical risk (5/5), with major deficits in detection and the laboratory capacity. A precision-targeted recommendation map proposed tailored microbiological interventions, such as neonatal antimicrobial susceptibility testing (AST) protocols for E. coli and intensive care unit infection registries for Pseudomonas species.

Conclusion

Species-level identification gaps and high AMR in CNS bacterial pathogens demand targeted microbiological-led diagnostics, including expanded cerebrospinal fluid testing and AST-guided empiric therapy in resource-limited settings.