A risk assessment of antibiotic pan-drug-resistance in the UK: Bayesian analysis of an expert elicitation study

Daniel Carter, Andre Charlett, Stefano Conti, Julie Robotham, Alan Johnson*, David Livermore, Tom Fowler, Mike Sharland, Susan Hopkins, Neil Woodford, Philip Burgess, Stephen Dobra

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

To inform the UK antimicrobial resistance strategy, a risk assessment was undertaken of the likelihood, over a five-year time-frame, of the emergence and widespread dissemination of pan-drug-resistant (PDR) Gram-negative bacteria that would pose a major public health threat by compromising effective healthcare delivery. Subsequent impact over five- and 20-year time-frames was assessed in terms of morbidity and mortality attributable to PDR Gram-negative bacteraemia. A Bayesian approach, combining available data with expert prior opinion, was used to determine the probability of the emergence, persistence and spread of PDR bacteria. Overall probability was modelled using Monte Carlo simulation. Estimates of impact were also obtained using Bayesian methods. The estimated probability of widespread occurrence of PDR pathogens within five years was 0.2 (95% credibility interval (CrI): 0.07–0.37). Estimated annual numbers of PDR Gram-negative bacteraemias at five and 20 years were 6800 (95% CrI: 400–58,600) and 22,800 (95% CrI: 1500–160,000), respectively; corresponding estimates of excess deaths were 1900 (95% CrI: 0–23,000) and 6400 (95% CrI: 0–64,000). Over 20 years, cumulative estimates indicate 284,000 (95% CrI: 17,000–1,990,000) cases of PDR Gram-negative bacteraemia, leading to an estimated 79,000 (95% CrI: 0–821,000) deaths. This risk assessment reinforces the need for urgent national and international action to tackle antibiotic resistance.

Original languageEnglish
Article number9
JournalAntibiotics
Volume6
Issue number1
DOIs
Publication statusPublished - 7 Mar 2017

Bibliographical note

Publisher Copyright:
© 2017 by the authors.

Keywords

  • Antibiotic resistance
  • Bayesian modelling
  • Risk assessment

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