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Mathematical modelling for antibiotic resistance control policy: do we know enough?

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Version 2 2023-06-12, 09:15
Version 1 2023-06-09, 19:45
journal contribution
posted on 2023-06-12, 09:15 authored by Gwenan M Knight, Nicholas G Davies, Caroline Colijn, Fransesc Coll, Tjibbe Donker, Danna R Gifford, Rebecca E Glover, Mark Jit, Elizabeth Klemm, Sonja Lehtinen, Jodi A Lindsay, Marc Lipstich, Martin LlewelynMartin Llewelyn, Ana L P Mateus, Julie V Robotham, Mike Sharland, Dov Stekel, Laith Yakob, Katherine E Atkins
Background: Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base. Main text: One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy. Conclusions: We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.

History

Publication status

  • Published

File Version

  • Published version

Journal

BMC Infectious Diseases

ISSN

1471-2334

Publisher

BMC

Issue

19

Page range

1-9

Department affiliated with

  • Global Health and Infection Publications

Research groups affiliated with

  • Brighton and Sussex Centre for Global Health Research Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2019-11-26

First Open Access (FOA) Date

2019-11-26

First Compliant Deposit (FCD) Date

2019-11-25

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