Progress on implementing the WHO-GLASS recommendations on priority pathogen-antibiotic sensitivity testing in Africa: A .

INTRODUCTION

The World Health Organization global antimicrobial resistance surveillance system (GLASS) was rolled out in 2015 to guide antimicrobial resistance (AMR) surveillance. However, its implementation in Africa has not been fully evaluated. We conducted a scoping review to establish the progress of implementing the WHO 2015 GLASS manual in Africa.

METHODS

We used MeSH terms to comprehensively search electronic databases (MEDLINE and Embase) for articles from Africa published in English between January 2016 and December 2023. The Arksey and O'Malley's methodological framework for scoping reviews was employed. Data were collected on compliance with WHO GLASS recommendations for AMR surveillance-priority samples, pathogens, and pathogen-antibiotic combinations and analysed using Microsoft Excel.

RESULTS

Overall, 13,185 articles were identified. 7,409 were duplicates, and 5,141 articles were excluded based on titles and abstracts. 609 full-text articles were reviewed, and 147 were selected for data extraction. Of the 147 selected articles, 78.9% had been published between 2020 and 2023; 57.8% were from Eastern Africa. 93.9% of articles were on cross-sectional studies. 96.6% included only one priority sample type; blood (n=56), urine (n=64), and stool (n=22). Of the 60 articles that focused on blood as a priority sample type, 71.7%, 68.3%, 68.3%, 36.7%, 30%, and 10% reported recovery of , , , species and respectively. and species were reported to have been recovered from 91.3% and 73.9% of the 23 articles that focused on stool. and recoveries were also reported from 94.2% and 68.1% of the 69 articles that focused on urine. No article in this review reported having tested all the recommended WHO GLASS pathogen-antibiotic combinations for specific pathogens.

CONCLUSION

Progress has been made in implementing the GLASS recommendations in Africa, but adoption varies across countries limiting standardisation and comparability of data.