Strengthening a One Health approach to emerging zoonoses

Given the enormous global impact of the COVID-19 pandemic, outbreaks of highly pathogenic avian influenza in Canada, and manifold other zoonotic pathogen activity, there is a pressing need for a deeper understanding of the human-animal-environment interface and the intersecting biological, ecological, and societal factors contributing to the emergence, spread, and impact of zoonotic diseases. We aim to apply a One Health approach to pressing issues related to emerging zoonoses, and propose a functional framework of interconnected but distinct groups of recommendations around strategy and governance, technical leadership (operations), equity, education and research for a One Health approach and Action Plan for Canada. Change is desperately needed, beginning by reorienting our approach to health and recalibrating our perspectives to restore balance with the natural world in a rapid and sustainable fashion. In Canada, a major paradigm shift in how we think about health is required. All of society must recognize the intrinsic value of all living species and the importance of the health of humans, other animals, and ecosystems to health for all

Wild Bird Influenza Survey, Canada, 2005

Of 4,268 wild ducks sampled in Canada in 2005, real-time reverse transcriptase–PCR detected influenza A matrix protein (M1) gene sequence in 37% and H5 gene sequence in 5%. Mallards accounted for 61% of samples, 73% of M1-positive ducks, and 90% of H5-positive ducks. Ducks hatched in 2005 accounted for 80% of the sample

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of ‘omics’ techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR

Factors impacting antimicrobial resistance in the South East Asian food system and potential places to intervene: A participatory, one health study

BackgroundWith AMU projected to increase, South East Asia (SEA) is at high risk of experiencing disproportionate health, social, and economic burdens due to antimicrobial resistance (AMR). Our objective was to identify factors influencing AMR in SEA’s food system and places for intervention by integrating the perspectives of experts from the region to inform policy and management decisions.Materials and methodsWe conducted two 6.5 h workshops and two 90-min interviews involving 18 AMR and other disciplinary experts from human, animal, and environment sectors who brainstormed the factors influencing AMR and identified leverage points (places) for intervention. Transcripts and workshop materials were coded for factors and their connections and transcribed into a causal loop diagram (CLD). Thematic analysis described AMR dynamics in SEA’s food system and leverage points for intervention. The CLD and themes were confirmed via participant feedback.ResultsParticipants constructed a CLD of AMR in the SEA food system that contained 98 factors interlinked by 362 connections. CLD factors reflected eight sub-areas of the SEA food system (e.g., government). Seven themes [e.g., antimicrobial and pesticide use and AMR spread (n = 40 quotes)], six “overarching factors” that impact the entire AMR system [e.g., the drive to survive (n = 12 quotes)], and 10 places for intervention that target CLD factors (n = 5) and overarching factors (n = 2) emerged from workshop discussions.ConclusionThe participant derived CLD of factors influencing AMR in the SEA food system demonstrates that AMR is a product of numerous interlinked actions taken across the One Health spectrum and that finding solutions is no simple task. Developing the model enabled the identification of potentially promising leverage points across human, animal, and environment sectors that, if comprehensively targeted using multi-pronged interventions, could evoke system wide changes that mitigate AMR. Even targeting some leverage points for intervention, such as increasing investments in research and capacity building, and setting and enforcing regulations to control antimicrobial supply, demand, and use could, in turn, shift mindsets that lead to changes in more difficult to alter leverage points, such as redefining the profit-driven intent that drives system behavior in ways that transform AMU and sustainably mitigate AMR

Identifying non-traditional stakeholders with whom to engage, when mitigating antimicrobial resistance in foodborne pathogens (Canada)

Abstract Objective Antimicrobial resistance (AMR) is a critical public health issue that involves interrelationships between people, animals, and the environment. Traditionally, interdisciplinary efforts to mitigate AMR in the food chain have involved public health, human and veterinary medicine, and agriculture stakeholders. Our objective was to identify a more diverse range of stakeholders, beyond those traditionally engaged in AMR mitigation efforts, via diagramming both proximal and distal factors impacting, or impacted by, use and resistance along the Canadian food chain. Results We identified multiple stakeholders that are not traditionally engaged by public health when working to mitigate AMR in the food chain, including those working broadly in the area of food (e.g., nutrition, food security, international market economists) and health (e.g., health communication, program evaluation), as well as in domains as diverse as law, politics, demography, education, and social innovation. These findings can help researchers and policymakers who work on issues related to AMR in the food chain to move beyond engaging the ‘traditional’ agri-food stakeholders (e.g., veterinarians, farmers), to also engage those from the wider domains identified here, as potential stakeholders in their AMR mitigation efforts

Data from: The ecology of avian influenza viruses in wild dabbling ducks (Anas spp.) in Canada

Avian influenza virus (AIV) occurrence and transmission remain important wildlife and human health issues in much of the world, including in North America. Through Canada's Inter-Agency Wild Bird Influenza Survey, close to 20,000 apparently healthy, wild dabbling ducks (of seven species) were tested for AIV between 2005 and 2011. We used these data to identify and evaluate ecological and demographic correlates of infection with low pathogenic AIVs in wild dabbling ducks (Anas spp.) across Canada. Generalized linear mixed effects model analyses revealed that risk of AIV infection was higher in hatch-year birds compared to adults, and was positively associated with a high proportion of hatch-year birds in the population. Males were more likely to be infected than females in British Columbia and in Eastern Provinces of Canada, but more complex relationships among age and sex cohorts were found in the Prairie Provinces. A species effect was apparent in Eastern Canada and British Columbia, where teal (A. discors and/or A. carolinensis) were less likely to be infected than mallards (A. platyrhynchos). Risk of AIV infection increased with the density of the breeding population, in both Eastern Canada and the Prairie Provinces, and lower temperatures preceding sampling were associated with a higher probability of AIV infection in Eastern Canada. Our results provide new insights into the ecological and demographic factors associated with AIV infection in waterfowl

The ecology of avian influenza viruses in wild dabbling ducks (<i>Anas</i> spp.) in Canada

<div><p>Avian influenza virus (AIV) occurrence and transmission remain important wildlife and human health issues in much of the world, including in North America. Through Canada’s Inter-Agency Wild Bird Influenza Survey, close to 20,000 apparently healthy, wild dabbling ducks (of seven species) were tested for AIV between 2005 and 2011. We used these data to identify and evaluate ecological and demographic correlates of infection with low pathogenic AIVs in wild dabbling ducks (<i>Anas</i> spp.) across Canada. Generalized linear mixed effects model analyses revealed that risk of AIV infection was higher in hatch-year birds compared to adults, and was positively associated with a high proportion of hatch-year birds in the population. Males were more likely to be infected than females in British Columbia and in Eastern Provinces of Canada, but more complex relationships among age and sex cohorts were found in the Prairie Provinces. A species effect was apparent in Eastern Canada and British Columbia, where teal (<i>A</i>. <i>discors</i> and/or <i>A</i>. <i>carolinensis</i>) were less likely to be infected than mallards (<i>A</i>. <i>platyrhynchos</i>). Risk of AIV infection increased with the density of the breeding population, in both Eastern Canada and the Prairie Provinces, and lower temperatures preceding sampling were associated with a higher probability of AIV infection in Eastern Canada. Our results provide new insights into the ecological and demographic factors associated with AIV infection in waterfowl.</p></div

The ecology of avian influenza viruses in wild dabbling ducks (<i>Anas</i> spp.) in Canada - Fig 2

<p>Predicted probability (solid line) and 95% CI (dashed lines) of AIV infection in dabbling ducks in the Prairie Provinces (a) and Eastern Canada (b) as a function of population density. Probabilities were estimated based on the best-approximating model (Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176297#pone.0176297.t001" target="_blank">1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176297#pone.0176297.t002" target="_blank">2</a>), with other variables set to their model reference category over the dataset as shown in the reported tables (HY male ducks (Prairie) or mallards (East) in Aug 2007) and at their mean values for temperature and percent HY. The distributions of data points are presented as rug plots along x axes (i.e., a vertical bar represents each sample) with different scales because duck density is higher in the Prairie Provinces than in Eastern Canada.</p

Maximum likelihood estimates (with 95% CI) of covariate parameters in the best-approximating model fitted to estimate the variation in AIV infection probability in dabbling ducks (<i>Anas</i> spp.) in Eastern Canada.

<p>Maximum likelihood estimates (with 95% CI) of covariate parameters in the best-approximating model fitted to estimate the variation in AIV infection probability in dabbling ducks (<i>Anas</i> spp.) in Eastern Canada.</p