Gender and antimicrobial resistance: a conceptual framework for researchers working in livestock systems

To promote gender mainstreaming in future AMR research projects and policy implementation within livestock and other systems, researchers need to embrace gender-responsive research methodologies. Ignoring gender considerations can lead to unsustainable interventions and exacerbate existing equity gaps. Incorporating gender analysis is crucial for identifying data collection needs and opportunities to develop gender-responsive research programs and policies.

We have developed a conceptual framework and a set of research questions designed to enhance the gender-responsiveness of AMR research in livestock systems.

A narrative review previously identified three key entry points for gender dynamic impacting AMR in agricultural systems: gendered antimicrobial resistance exposure, gendered antimicrobial use and gendered outcomes of antimicrobial resistance infections. This information was then analyzed using a health system gender framework. Combining these insights, we developed a comprehensive list of research questions.

We developed comprehensive list of gender-related questions. Given the limited understanding of how gender dynamics and norms influence AMR, we have primarily proposed qualitative, exploratory questions. These questions are categorized into two types: integrated and strategic. Integrated questions offer a deeper understanding of gender dynamics and norms in livestock systems with the aim of improving them, while strategic questions focus on gender-related issues in livestock as entry points, highlighting some of the mechanisms behind these gender issues to progress towards gender equality.

As gender-analysis in livestock research gains prominence, there is an increasing expectation for AMR researchers to integrate gender considerations into their work. This framework provides a starting point for researchers aiming to enhance gender inclusivity and considerations in AMR research within livestock systems. The next phase of our project will involve applying this framework in the field, where a real-life application will enable its validation and further refinement.