A systematic review of economic evaluations of whole-genome sequencing for the surveillance of bacterial pathogens

Microb Genom. 2023 Feb;9(2):mgen000947. doi: 10.1099/mgen.0.000947.

Abstract

Whole-genome sequencing (WGS) has unparalleled ability to distinguish between bacteria, with many public health applications. The generation and analysis of WGS data require significant financial investment. We describe a systematic review summarizing economic analyses of genomic surveillance of bacterial pathogens, reviewing the evidence for economic viability. The protocol was registered on PROSPERO (CRD42021289030). Six databases were searched on 8 November 2021 using terms related to 'WGS', 'population surveillance' and 'economic analysis'. Quality was assessed with the Drummond-Jefferson checklist. Following data extraction, a narrative synthesis approach was taken. Six hundred and eighty-one articles were identified, of which 49 proceeded to full-text screening, with 9 selected for inclusion. All had been published since 2019. Heterogeneity was high. Five studies assessed WGS for hospital surveillance and four analysed foodborne pathogens. Four were cost-benefit analyses, one was a cost-utility analysis, one was a cost-effectiveness analysis, one was a combined cost-effectiveness and cost-utility analysis, one combined cost-effectiveness and cost-benefit analyses and one was a partial analysis. All studies supported the use of WGS as a surveillance tool on economic grounds. The available evidence supports the use of WGS for pathogen surveillance but is limited by marked heterogeneity. Further work should include analysis relevant to low- and middle-income countries and should use real-world effectiveness data.

Keywords: antimicrobial resistance; economic evaluation; foodborne pathogens; infection prevention and control; systematic review; whole-genome sequencing.

Publication types

  • Systematic Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria* / genetics
  • Cost-Benefit Analysis
  • Cost-Effectiveness Analysis*
  • Genomics
  • Whole Genome Sequencing