Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Quantitative Framework for Evaluating the Societal Impact of Antimicrobial Use Reduction in Agriculture

Version 1 : Received: 10 August 2022 / Approved: 12 August 2022 / Online: 12 August 2022 (11:28:08 CEST)

How to cite: Emes, E.T. A Quantitative Framework for Evaluating the Societal Impact of Antimicrobial Use Reduction in Agriculture. Preprints 2022, 2022080237 (doi: 10.20944/preprints202208.0237.v1). Emes, E.T. A Quantitative Framework for Evaluating the Societal Impact of Antimicrobial Use Reduction in Agriculture. Preprints 2022, 2022080237 (doi: 10.20944/preprints202208.0237.v1).

Abstract

Antimicrobial resistance (AMR) is an increasingly pressing threat to human, animal, and environmental health. Reducing the use of antibiotics in agriculture has been identified as a key way to curb the spread of AMR. However, the effect of such policies on AMR prevalence, and their broader impacts on agricultural, health, and economic outcomes at the population level have proven very difficult to estimate and compare. This paper draws on and formalises ideas presented at the JPIAMR New Perspectives on Bacterial Drug Resistance workshop in June of 2022. With reference to emerging literature on the topic, it proposes a quantitative framework for estimating the relevant causal relationships needed to quantify the cross-sectoral impacts of AMR policies in agriculture, and for comparing these outcomes in like terms in a way which can feed directly into policy decision-making, notably without prohibitive data requirements. The ability of researchers to apply frameworks such as this will be increasingly necessary in order to holistically capture the impacts of AMR policies and to situate them in the broader policy context; especially where the mechanisms of transmission are opaque or complex, where data availability is limited; and where policymakers must allocate scarce resources among many competing objectives.

Keywords

AMR; agriculture; One Health; health economics; policy; modelling

Subject

LIFE SCIENCES, Other

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.

We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.