Abstract / Summary
Background: Epidemiologic surveillance is one pillar in the global efforts to stop the spread of antibiotic-resistant bacteria (ARB) and increasingly includes whole genome sequencing (WGS). However, no review systematically examined the characteristics of such surveillance systems until February 2025. We conducted a systematic review to identify and describe routine surveillance systems of ARB, that integrate WGS and epidemiological information.
Methods: A protocol was developed and published on PROSPERO. We searched 8 databases and Google. Included articles needed to report on a national or subnational surveillance system and include epidemiological data as well as WGS of carbapenem-resistant or carbapenemase-producing Enterobacterales (CRE) or Acinetobacter spp., methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococci (VRE). Surveillance system characteristics were analysed narratively.
Results: From 13,142 searched articles, 41 were included. The publications were stratified by pathogen. The strata demonstrated similar WGS approaches with a predominance of short-read sequencing platforms. Typing methods mostly included multilocus sequence typing and single nucleotide polymorphism -based analyses for higher discrimination. Reported cluster thresholds showed a wide range of values within and between species. Across strata, there was often a low level of epidemiological data collection, such as exposure of cases, and integration in cluster analyses. WGS surveillance complemented with at least basic epidemiological data has been reported from all six WHO regions for CRE. However, fewer studies and no studies at all for MRSA and VRE were included from the African, Eastern Mediterranean and South-East Asian regions. The national coverage of surveillance ranged from 36% for MRSA to 56% for CRE.
Conclusion: WGS-based surveillance on ARB is employed worldwide with predominant use of short-read technology and largely consistent typing methods. Substantial variation in genomic clustering thresholds underscores the need for internationally harmonized standards for data analysis. Insufficient epidemiological information or lacking integration in the analysis of WGS data may reduce the ability to infer transmission pathways and identify outbreaks. To fully exploit the potential of WGS-based surveillance systems in this context for public health and contain current and prevent future outbreaks, we thus call for a routine collection of detailed epidemiological data.