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A Web-Based Tool to Identify Interventions to Reduce Transmission of Antimicrobial Resistance

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HCI International 2022 Posters (HCII 2022)

Abstract

Antimicrobial resistance (AMR) is widely recognized as one of the greatest threats to public health in the 21st century. Microbial pathogens including bacteria, viruses, parasites, and fungi are rapidly evolving to become resistant to antimicrobial drugs. Analysis from 2016 reported that at least 700,000 people die every year due to drug-resistant infections; if no action is taken, this number is expected to jump to 10 million human lives per year by 2050 (https://amr-review.org/). Proven methods to help slow the transmission of antimicrobial resistance, such as infection prevention and control practices, and stewardship against misuse and overuse of antimicrobials, are often not effectively implemented due to economic considerations, system inefficiencies, or human behaviour complexities.

In response, our team is developing an online and interactive knowledge translation tool intended to accurately represent complex systems and effectively identify intervention opportunities. Using qualitative research methods, we are mapping out the sociotechnical system of the Canadian beef cattle industry from a One Health perspective. We are engaging with system stakeholders to ensure accuracy and completeness of our information, and consulting potential users to identify the most effective functions and interface characteristics of the tool. We believe that making important system information accessible is crucial to inform opportunities for new products, services and technologies, spark research and business collaborations, prompt consumer awareness and action, and inform policy. Our aim is to create a model that can be emulated to create similar tools in other fields to identify opportunities to help slow the transmission of AMR.

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Acknowledgements

This research is part of the AMR – One Health Consortium, funded by the Major Innovation Fund program of the Ministry of Jobs, Economy and Innovation, Government of Alberta. Our thanks to Dr. Herman Barkema, Golsa Kafili, and Samantha Larose. We would also like to acknowledge the significant contributions from our advisors and past team members, including Michelle Cheng, Dr. Rebecca Malott, Dr. Cindy Hutchison, Johanna Blaak, Dr. Jaime Kaufman, Dr. Michele Anholt, Dr. Danielle Julien, Dana Jelinski, Dr. Mike Jelinski, Dr. Craig Dorin, Julia Kupis, Kumel Amjad, Kathy Liu, Dr. Sarah Simmons, and Greg Hallihan. We would also like to thank all participants who have shared their expertise of the beef cattle industry with us, as well as all participants and advisors who have shared their knowledge of AMR.

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Correspondence to Courtney MacDonald .

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MacDonald, C., Bradford, A., MacGregor, J., Flemons, K., Traynor, B., Conly, J.M. (2022). A Web-Based Tool to Identify Interventions to Reduce Transmission of Antimicrobial Resistance. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1580. Springer, Cham. https://doi.org/10.1007/978-3-031-06417-3_44

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  • DOI: https://doi.org/10.1007/978-3-031-06417-3_44

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