iAM.AMR Sep 01, 2021 Welcome 1 Background 3 2 Project 5 3 Scope 7 i ii iAM.AMR Welcome 1 iAM.AMR 2 Welcome CHAPTER 1 Background Antimicrobial resistance (AMR) refers to the ability of microorganisms to withstand the effects of antimicrobials (to which they were formerly susceptible). In short, AMR reduces (or eliminates) our ability to treat certain types of infections. While the primary driver (cause) of AMR is human antimicrobial use (AMU), we’re also concerned with animal AMU in the agri-food production system; AMU may increase AMR in zoonotic pathogens, and Canadians may be exposed to these pathogens through the consumption of microbially-contaminated foods. 3 iAM.AMR 4 Chapter 1. Background CHAPTER 2 Project The goal of the iAM.AMR project is to quantify the relative contribution of each bug-drug-commodity combination to Canadians’ overall exposure to resistant pathogens arising from the agri-food production system. To that end, we searched the literature to identify factors affecting resistance, and used these factors in an integrated assessment model (IAM) framework to characterize the prevalence of AMR along the farm-to-fork continuum. Ulti- mately, we describe the number of servings at risk for each bug-drug-commodity combination. This framework allows us to acheive a secondary objective: to understand how broad changes (e.g. encouraging a practice, or withdrawing an antimicrobial) can influence the entire agri-food system. 5 iAM.AMR 6 Chapter 2. Project CHAPTER 3 Scope The iAM.AMR project focuses on four [food-animal species | commodities]: • broiler chicken | chicken • swine | pork • dairy cattle or beef cattle | beef • turkey | turkey The iAM.AMR project focuses on four microbes: • E.coli • Salmonella Spp. • Campylobacter Spp. • Enterococcus Spp. The iAM.AMR project focuses on resistance to drugs of human importance, including: • macrolides • tetracyclines • fluoroquinolones • third-generation cephalosporins See the Model Directory repository for an up-to-date list of models and locations. 3.1 Getting Started Welcome to the iAM.AMR project! The first step in getting started is to explore this documentation; get to know the project in-depth here! 7 iAM.AMR Then, check out our Start-Here GitHub repository. GitHub is where we host our models, store more of our documen- tation, and do our model development. Finally, fetch and run the models! For the Public For New Collaborators 3.1.1 For the Public At present, the models are not being openly circulated. Please contact Brennan Chapman to be granted access to the model repositories. See the Model Directory repository for an up-to-date list of models and locations. 3.1.2 For New Collaborators The first step is to complete the on-boarding survey. Then, access the iAM.AMR GitHub Organization (requires approval, and login). If you can’t access these links, contact Brennan Chapman. Note, it may take up to 48h after completing the onboarding survey to be added – before you reach out, ensure you’ve accepted all invites at our GitHub Organization’s invite page and checked the Notifications section. See our Start Here repository for more information. See the Model Directory repository for an up-to-date list of models and locations. 3.1.3 Important Links See the public and private iAM.AMR directories. 3.2 Background 3.2.1 Antimicrobial Resistance (AMR) Antimicrobial resistance (AMR) refers to the ability of microorganisms, such as bacteria, fungi, or viruses, to withstand (or partially withstand) the effects of an antimicrobial to which they were formerly susceptible. While AMR may occur naturally as a result of the evolutionary process, the development and spread of AMR in microbial populations has been accelerated by the sustained anthropogenic use of antimicrobials. At present, an estimated 700,000 persons die each year as a result of antimicrobial resistant infections1 – a number which is expected to grow as the prevalence of resistance continues to increase at a rate that far outpaces our ability to develop new antimicrobial therapies. 3.2.2 AMR and the Agri-food Production System In addition to human and veterinary medicine, antimicrobials are used in livestock and agricultural production (to- gether, agri-food production) to reduce the occurrence of disease and increase yield. While antimicrobial use (AMU) in human medicine is recognized as the primary driver of anthropogenic resistance development, AMU and other resistance-promoting practices in the agri-food production system are of particular concern with respect to human health, given the ease with which resistant pathogens may transfer between animals, humans, and their environments 1 O’Neill, J. Tackling drug-resistant infections globally: final report and recommendations. Rev. Antimicrob. Resist. 84 (2016). doi:10.1016/j.jpha.2015.11.005 8 Chapter 3. Scope iAM.AMR along the farm-to-fork continuum. Despite the risk posed by these pathogens, there remain a number of significant knowledge gaps in our understanding of the processes governing the development and persistence of AMR in the agri-food production system. 3.2.3 Integrated Assessment Modelling Integrated assessment modelling differs from traditional risk modelling approaches in that it (generally) does not seek to develop numerical answers to specific questions; while integrated assessment models (iAMs) are simplifications of reality, they are not designed to simplify systems to the point of solution. Rather, iAMs are designed to integrate vastly different forms and scales of information, from traditional and non-traditional stakeholders, into a single framework through which users can address broad and complex questions. The output of an iAM, while often unrealistic or nonsensical in terms of a specific numerical value, is designed to increase the users’ understanding of the direction and magnitude of changes resulting from perturbations to a large, complex system. In the context of integrated assessment modeling’s original application – climate change science – these perturbations are often characterized as inadvertent consequences of human actions. In the context of generalized risk assessment, these perturbations may also take the form of strategic interventions, designed to achieve risk reductions throughout (or more commonly, within a manageable subsection of) the system. 3.3 Project Structure 3.3.1 Goals The overall goal of the iAM.AMR project is to elucidate and quantify the relative contributions of specific agri-food commodities and related environmental exposure pathways to Canadians’ overall exposure to antimicrobial resistant bacteria arising from the agri-food production system. To meet this goal, we endeavor to: • create a conceptual model describing the agri-food production system, the drivers of AMR within this system, and the effects of AMR within this system (and beyond) on human, animal, and environmental health. • collect data from national AMR and AMU surveillance programmes, associated research projects, and the sci- entific literature to describe the ecology and epidemiology of AMR in this system historically, and at present. • quantify the individual effect of each driver of resistance – and identify omitted drivers – through a comprehen- sive literature search. • integrate the conceptual model, epidemiological data, and the effect of each driver within a standardized mod- elling framework. • use the developed mathematical model(s) to understand how drivers, such as AMU and Canadian production practices affect human exposure to antimicrobial resistant bacteria arising from the agri-food production system. • engage industry stakeholders to inform identified knowledge gaps, communicate high-risk practices, and provide recommendations considering each human, animal, and environmental health. • use these findings to inform broader AMR human risk-reduction initiatives. 3.3.2 Overview An overview of the entire project can be accessed via Kumu via the AMR Org Chart, embedded below. To edit or contribute, please contact Brennan Chapman. 3.3. Project Structure 9 iAM.AMR Scope To reduce the scope of the project to a manageable size, the three most common food-animal species and the three most commonly isolated enteric bacteria from those species were selected as the core areas of focus. These include chicken, cattle, and swine, and E. coli, Salmonella Spp. and Campylobacter Spp. for host species and bacterial species respectively. While the primary human exposure route is assumed to be consumption of the corresponding agri-food products (chicken, beef, and pork), additional focus has been placed on environmental exposure routes (e.g. through the consumption of leafy greens or root vegetables, grown in manure-amended soils). Additional food-animal and bacterial species of interest include turkeys and Enterococcus Spp., which may be explored later as the project progresses. Organization via stories The models are organized primarily by ‘stories’, or bug-drug-host combinations of particular interest. Existing stories and their corresponding models are available in the iAM.AMR GitHub repository. Literature Search The iAM.AMR models are informed by a single, all-encompassing literature search. A description of the literature search and associated products is provided on the literature search main page. The CEDAR database CEDAR, the Collection of Epidemiologically Derived Associations with Resistance, is a Microsoft Access database, designed to house data extracted in support of the iAM.AMR project and associated activities. The studies identified through the