The SEFASI project aims to create a range of outputs which can be used by future researchers and policymakers in the interest of open-source science. Aside from the creation of the SEFASI Knowledge Hubs, we aim to form a library of up-to-date literature on agriculture and AMR, and to make available the data used in our research so that it can be repurposed for future research. Among our most important outputs are the reusable models that we create as part of the project, and the journal articles that will be published as part of our research. 

Publications

How does antibiotic consumption in humans and animals link to AMR at the national level? And how best to estimate this relationship? - an opinion piece with recommendations for future research

This paper argues that we do not know enough about the relationship between antibiotic use and antibiotic resistance, at the population level, to inform health-economic decision making. We emphasise the need to estimate an actual number of resistant infections averted from a given change in national antibiotic use, and that this concern has been given insufficient attention in the literature. We highlight the potential of regression models using population-level data to bridge this gap, and outline a robust methodology for doing so in future research. 

[upcoming] Creating a better framework for understanding how antimicrobial use affects society across all sectors

This paper (in preprint) creates a theoretical framework which can be used to estimate the health-economic effect of antimicrobial use on all sectors of society. This includes all of the effects considered in AHHME (with some tweaks and improvements), as well as the indirect effects on population health via food security, economic security, and constrained healthcare resources. This framework proposes a mixture of statistical and mathematical models with much lower data requirements than previous models. It can be applied to a range of AMR issues outside of agriculture, and we hope to work with collaborators in Zambia and Malawi in the coming months to estimate the national impact of AMR in these countries using this framework. 

[upcoming] Cross-Sectoral Cost-Effectiveness of Interventions to Control Antimicrobial Resistance in Livestock Production - A One Health Modelling Exercise Using AHHME

This paper (in preprint) performs a range of modelling exercises using our Agricultural Human-Health Micro Economic (AHHME) model (see Models for information and resources on the model itself). We explore the hypothetical impact of reducing antibiotic use in livestock production in hypothetical countries of various income levels, exploring uncertainty in our parameters and assumptions. We also apply the model to the case of present-day Vietnam, simulating national-level rollout of an intervention that was trialled in 2020. Our results showed that national rollout of antimicrobial stewardship interventions in farms can provide a societal benefit equivalent to millions or billions of $USD per year, and highlighted that farm productivity and macroeconomic outcomes can be just as significant as the direct effect on human health.

[upcoming] country case study: drug-resistant Campylobacter infections and antibiotic use in English poultry farms

Campylobacter is a bacterium which infects humans and can cause debilitating gastrointestinal infections. Infections with Campylobacter have grown more prevalent over time in England, with surges during the summer months. It is thought that the bug reaches humans primarily through the consumption of domestically-produced poultry, with antibiotic-resistant strains being particularly dangerous. We plan to use recent changes in the antibiotic use patterns in English poultry farms as a natural experiment to see if these antibiotics contribute to the spread of such 'superbugs'. 

[upcoming] country case study: using Danish data to tease apart the relationship between agricultural antibiotic use and AMR in humans 

Denmark is a world leader in antibiotic stewardship, with programmes like the ‘yellow card initiative’ discouraging farmers from overusing and misusing antibiotics in livestock production. The wealth of data collected on antibiotics used in farms across Denmark, as well as on the incidence of antibiotic-resistant infections in humans, will allow us to investigate in detail how antibiotic use and antibiotic resistance relate to each other. Beyond simply establishing the existence of a connection between antibiotic use and AMR, we will use regression methods to look at the size and shape of this relationship. This will help us to understand the health-economic implications of each additional dose of antibiotics, and will inform cost-effectiveness analysis of future policies concerning antibiotic use in agriculture. 

[upcoming] country case study: what drives antibiotic use in poultry production? The case of Dakar and Thiès' peri-urban chicken farms

In order to manage or reduce antibiotic use in farms, we first must understand why farmers use antibiotics in the first place, and if there are any strategies which can reduce reliance on them. Better vaccination, better biosecurity, and better awareness of AMR issues have all been proposed as ways of reducing the need for antibiotics in farms. Using survey data from semi-intensive poultry farms in Dakar and Thiès, we investigate the extent to which these factors drive antibiotic use, and if they can help to mitigate any productivity loss from reducing antibiotic use. 

Conference and workshop outputs

SEFASI consortium outputs are regularly shared with researchers, policymakers and stakeholders, and engaging this participatory process is one of our main objectives. So far, this has meant that:

• The framework presented in this preprint was presented and discussed at the JPIAMR New Perspectives on Bacterial Drug Resistance workshop on 9 June 2022
• From 26-27 September 2022, the SEFASI consortium hosted a workshop in Dakar where we presented our ongoing work to a range of researchers, policymakers and stakeholders from across the One Health - AMR spectrum, starting a two-way conversation with stakeholders about priority-setting in AMR research and policy

Models

The SEFASI GitHub Page

The SEFASI GitHub page is currently under construction, and when completed will contain all coding resources from the numerous projects which make up SEFASI.

The Agriculture Human Health MicroEconomic (AHHME) Model

The purpose of the model

Antimicrobial stewardship policies in agriculture affect every sector of society. Reducing antibiotic use in farms may reduce farm productivity and hurt farmers’ incomes, and this effect could be mitigated by improving farming practices in tandem. Implementing these interventions will incur a cost to the public sector. If reducing antibiotic use in agriculture reduces the number of people infected by drug-resistant bacteria, then this will prevent illness. Few illnesses also means fewer long-term sequelae, and fewer deaths. This, in turn, reduces the burden on the healthcare system, and means that fewer people are left unable to work (both in paid and unpaid work). 

The Agriculture-Human-Health-Micro-Economic (AHHME) model takes all of these outcomes into account, and compares them in like terms. This gives us the cross-sectoral cost-effectiveness of hypothetical antimicrobial stewardship policies in agriculture. Depending on the information available, this can take the form of net monetary benefit of a proposed policy, or a threshold price (the maximum amount that we should be willing to pay to implement that policy).

Applications of the model

The AHHME model is flexible to a number of different methodological assumptions, types of intervention, and country characteristics. By customising these parameters, the model can be applied to any antimicrobial stewardship policy in any setting, and with various scopes of analysis.

In an upcoming paper, we apply the model to a range of hypothetical antimicrobial use interventions in high-, middle- and low-income contexts (see ‘Publications’ for information on this and other SEFASI outputs). 

On our public GitHub repository, we have included the code used to create and run the AHHME model in R. It also includes an example of how to adapt the model to any context and purpose. Our hope is that researchers and policymakers can use AHHME to model the cost-effectiveness of prospective agricultural antimicrobial stewardship policies in their own countries. Comparing outcomes in like terms across sectors will allow AMR policies to be compared to other, unrelated policy alternatives, allowing AMR to be correctly prioritised on the national policy agenda.

We have also created an interactive Shiny App which allows users to edit model inputs in a more straightforward way. This is intended to allow researchers to familiarise themselves with the model, and for exploratory analysis of potential interventions.