Attitudes, subjective norms and perceived behavioural control factors influencing Canadian secondary school students' milk and milk alternatives consumption.

OBJECTIVE: The research objectives were to evaluate factors that influence Canadian secondary school students' milk and milk alternatives (MMA) consumption and to explore associations through age and gender lenses. DESIGN: A qualitative design was used, consisting of semi-structured interviews and photo-elicitation methods. Analysis was guided by the Theory of Planned Behaviour (TPB). Deductive and inductive thematic analyses were used to generate themes, charting data based on attributes such as gender and age. SETTING: Interviews were held virtually or via telephone. PARTICIPANTS: Participants were twenty-eight high school students from Ontario, Canada, diverse in terms of gender and age. RESULTS: Both desirable and undesirable beliefs about the health outcomes of consuming MMA were commonly discussed. These included health benefits such as strong bones, muscular strength, and growth, and health consequences like unwanted skin conditions, weight gain, and diseases. While boys and girls associated MMA consumption with muscular strength, boys predominantly considered this favourable, while girls discussed outcomes like unwanted skin conditions and weight gain more often. Adolescents' perspectives on taste/perceived enjoyment, environmentally friendly choices and animal welfare also influenced their MMA preferences. Parental influences were most cited among social factors, which appeared to be stronger during early adolescence. Factors involving cost, time and accessibility affected adolescents' beliefs about how difficult it was to consume MMA. CONCLUSIONS: Recommendations for shifting attitudes towards MMA are provided to address unfavourable beliefs towards these products. Interventions to increase MMA consumption among adolescents should include parents and address cost barriers.

Revealing the Mysteries of Population Mobility Amid the COVID-19 Pandemic in Canada: Comparative Analysis With Internet of Things-Based Thermostat Data and Google Mobility Insights.

BACKGROUND: The COVID-19 pandemic necessitated public health policies to limit human mobility and curb infection spread. Human mobility, which is often underestimated, plays a pivotal role in health outcomes, impacting both infectious and chronic diseases. Collecting precise mobility data is vital for understanding human behavior and informing public health strategies. Google's GPS-based location tracking, which is compiled in Google Mobility Reports, became the gold standard for monitoring outdoor mobility during the pandemic. However, indoor mobility remains underexplored. OBJECTIVE: This study investigates in-home mobility data from ecobee's smart thermostats in Canada (February 2020 to February 2021) and compares it directly with Google's residential mobility data. By assessing the suitability of smart thermostat data, we aim to shed light on indoor mobility patterns, contributing valuable insights to public health research and strategies. METHODS: Motion sensor data were acquired from the ecobee "Donate Your Data" initiative via Google's BigQuery cloud platform. Concurrently, residential mobility data were sourced from the Google Mobility Report. This study centered on 4 Canadian provinces-Ontario, Quebec, Alberta, and British Columbia-during the period from February 15, 2020, to February 14, 2021. Data processing, analysis, and visualization were conducted on the Microsoft Azure platform using Python (Python Software Foundation) and R programming languages (R Foundation for Statistical Computing). Our investigation involved assessing changes in mobility relative to the baseline in both data sets, with the strength of this relationship assessed using Pearson and Spearman correlation coefficients. We scrutinized daily, weekly, and monthly variations in mobility patterns across the data sets and performed anomaly detection for further insights. RESULTS: The results revealed noteworthy week-to-week and month-to-month shifts in population mobility within the chosen provinces, aligning with pandemic-driven policy adjustments. Notably, the ecobee data exhibited a robust correlation with Google's data set. Examination of Google's daily patterns detected more pronounced mobility fluctuations during weekdays, a trend not mirrored in the ecobee data. Anomaly detection successfully identified substantial mobility deviations coinciding with policy modifications and cultural events. CONCLUSIONS: This study's findings illustrate the substantial influence of the Canadian stay-at-home and work-from-home policies on population mobility. This impact was discernible through both Google's out-of-house residential mobility data and ecobee's in-house smart thermostat data. As such, we deduce that smart thermostats represent a valid tool for facilitating intelligent monitoring of population mobility in response to policy-driven shifts.

Temporal, spatial and space-time distribution of infections caused by five major enteric pathogens, Ontario, Canada, 2010-2017.

AIMS: In Canada, enteric diseases pose substantial health and economic burdens. The distribution of these diseases is uneven across both geography and time and understanding these patterns is therefore important for the prevention of future outbreaks. We evaluated temporal, spatial and space-time clustering of laboratory-confirmed cases of Campylobacter spp. (n = 28,728), non-typhoidal Salmonella spp. (n = 22,640), Shiga toxin-producing Escherichia coli (STEC; n = 1340), Yersinia spp. (n = 1674) and Listeria monocytogenes (n = 471) infections, reported between 2010 and 2017 inclusive in Ontario, the most populous province in Canada (population ~ 13,500,000 in 2016). METHODS AND RESULTS: For each enteric pathogen, we calculated the mean incidence rates (IRs) for Ontario's 35 public health unit (PHU) areas and visualized them using choropleth maps. We identified temporal, spatial and space-time high infection rate clusters using retrospective Poisson scan statistics. Campylobacter and Salmonella infections had the highest IRs, while Listeria infections had the lowest. Campylobacter, Salmonella, STEC and Listeria mostly clustered temporally in the spring/summer and sometimes extended into fall, while Yersinia showed a less clear seasonal pattern. The IR visualizations and spatial and space-time scan statistics showed geographic heterogeneity of infection rates with high infection rate clusters detected mainly in PHUs across the southwestern and central-western regions of Ontario for Campylobacter, Salmonella and STEC infections, and mainly in PHUs located in the central-eastern regions for Yersinia and Listeria. A high proportion of cases in some of the significant Salmonella, STEC and Listeria infection clusters were linked to disease outbreaks. CONCLUSIONS: Results from this study will inform heightened public health surveillance, and prevention and control programmes, in populations and regions of high infection rates. Further research is needed to determine the pathogen-specific socioeconomic, environmental and agricultural risk factors that may be related to the temporal and spatial disease patterns we observed in our study.

Hexachlorobenzene and omega-3 fatty acid intake from traditional foods in the northern Yukon: A risk and benefit analysis.

A human biomonitoring study was conducted in the community of Old Crow, Yukon, in 2019, finding that levels of hexachlorobenzene (HCB) in plasma were elevated in the community relative to the general Canadian population. The aim of this study was to estimate dietary intake of both hexachlorobenzene, and the nutrient omega-3 fatty acids from locally harvested traditional foods in Old Crow, with the aim of identifying possible regional sources of exposure. A stochastic model was constructed to estimate intake of both hexachlorobenzene and the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Average predicted hexachlorobenzene exposure levels from traditional food consumption in Old Crow were below the tolerable daily intake of 1600-1700 ng/kg body weight/day in both average (18 ng/kg body weight/day) and short-term maximum (27 ng/kg body weight/day) exposure models. The primary contributors to average hexachlorobenzene intake were caribou fat, bone marrow, ribs, and kidneys, and Chinook salmon muscle. Average estimated dietary EPA + DHA intake levels from traditional foods were below the recommendation of 2.1 to 3.2 g of EPA + DHA per week in the average (1.6 g/week) exposure model, but above this recommendation in the short-term maximum model (3.3 g/week). The primary contributors to average EPA + DHA intake were the meat of Chinook, coho, and, chum salmon muscle, and whitefish muscle and eggs. The results of this study support the message that traditional foods continue to be an important source of nutrients and other health benefits and that the health benefits of traditional foods generally outweigh contaminant risks.

Exploring the factors that contribute to the successful implementation of antimicrobial resistance interventions: a comparison of high-income and low-middle-income countries.

Introduction: Antimicrobial resistance (AMR) is a challenge to modern medicine. Interventions have been applied worldwide to tackle AMR, but these actions are often not reported to peers or published, leading to important knowledge gaps about what actions are being taken. Understanding factors that influence the implementation of AMR interventions and what factors are relevant in low-middle-income countries (LMICs) and high-income countries (HICs) were the key objectives of this exploratory study, with the aim to identifying which priorities these contexts need. Methods: A questionnaire was used to explore context, characteristics, and success factors or obstacles to intervention success based on participant input. The context was analyzed using the AMR-Intervene framework, and success factors and obstacles to intervention success were identified using thematic analysis. Results: Of the 77 interventions, 57 were implemented in HICs and 17 in LMICs. Interventions took place in the animal sector, followed by the human sector. Public organizations were mainly responsible for implementation and funding. Nine themes and 32 sub-themes emerged as important for intervention success. The themes most frequently reported were 'behavior', 'capacity and resources', 'planning', and 'information'. Five sub-themes were key in all contexts ('collaboration and coordination', 'implementation', 'assessment', 'governance', and 'awareness'), two were key in LMICs ('funding and finances' and 'surveillance, antimicrobial susceptibility testing and preventive screening'), and five were key in HICs ('mandatory', 'multiple profiles', 'personnel', 'management', and 'design'). Conclusion: LMIC sub-themes showed that funding and surveillance were still key issues for interventions, while important HIC sub-themes were more specific and detailed, including mandatory enforcement, multiple profiles, and personnel needed for good management and good design. While behavior is often underrated when implementing AMR interventions, capacity and resources are usually considered, and LMICs can benefit from sub-themes captured in HICs if tailored to their contexts. The factors identified can improve the design, planning, implementation, and evaluation of interventions.

Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research.

BACKGROUND: Antimicrobial Resistance (AMR) is a global problem with large health and economic consequences. Current gaps in quantitative data are a major limitation for creating models intended to simulate the drivers of AMR. As an intermediate step, expert knowledge and opinion could be utilized to fill gaps in knowledge for areas of the system where quantitative data does not yet exist or are hard to quantify. Therefore, the objective of this study was to identify quantifiable data about the current state of the factors that drive AMR and the strengths and directions of relationships between the factors from statements made by a group of experts from the One Health system that drives AMR development and transmission in a European context. METHODS: This study builds upon previous work that developed a causal loop diagram of AMR using input from two workshops conducted in 2019 in Sweden with experts within the European food system context. A secondary analysis of the workshop transcripts was conducted to identify semi-quantitative data to parameterize drivers in a model of AMR. MAIN FINDINGS: Participants spoke about AMR by combining their personal experiences with professional expertise within their fields. The analysis of participants' statements provided semi-quantitative data that can help inform a future of AMR emergence and transmission based on a causal loop diagram of AMR in a Swedish One Health system context. CONCLUSION: Using transcripts of a workshop including participants with diverse expertise across the system that drives AMR, we gained invaluable insight into the past, current, and potential future states of the major drivers of AMR, particularly where quantitative data are lacking.

Scope and applicability of social-ecological resilience to antimicrobial resistance.

Social-ecological systems conceptualise how social human systems and ecological natural systems are intertwined. In this Personal View, we define the scope and applicability of social-ecological resilience to antimicrobial resistance. Resilience to antimicrobial resistance corresponds to the capacity to maintain the societal benefits of antimicrobial use and One Health systems' performance in the face of the evolutionary behaviour of microorganisms in response to antimicrobial use. Social-ecological resilience provides an appropriate framework to make sense of the disruptive impacts resulting from the emergence and spread of antimicrobial resistance; capture the diversity of strategies needed to tackle antimicrobial resistance and to live with it; understand the conditions that underpin the success or failure of interventions; and appreciate the need for adaptive and coevolutionary governance. Overall, resilience thinking is essential to improve understanding of how human societies dynamically can cope with, adapt, and transform to the growing global challenge of antimicrobial resistance.

Estimating the Under-ascertainment of COVID-19 cases in Toronto, Ontario, March to May 2020.

Background: Public health surveillance data do not always capture all cases, due in part to test availability and health care seeking behaviour. Our study aimed to estimate under-ascertainment multipliers for each step in the reporting chain for COVID-19 in Toronto, Canada. Design and methods: We applied stochastic modeling to estimate these proportions for the period from March 2020 (the beginning of the pandemic) through to May 23, 2020, and for three distinct windows with different laboratory testing criteria within this period. Results: For each laboratory-confirmed symptomatic case reported to Toronto Public Health during the entire period, the estimated number of COVID-19 infections in the community was 18 (5th and 95th percentile: 12, 29). The factor most associated with under-reporting was the proportion of those who sought care that received a test. Conclusions: Public health officials should use improved estimates to better understand the burden of COVID-19 and other similar infections.

"We need to talk to each other": Crossing traditional boundaries between public health and occupational health to address COVID-19.

Introduction: This study examined how public health (PH) and occupational health (OH) sectors worked together and separately, in four different Canadian provinces to address COVID-19 as it affected at-risk workers. In-depth interviews were conducted with 18 OH and PH experts between June to December 2021. Responses about how PH and OH worked across disciplines to protect workers were analyzed. Methods: We conducted a qualitative analysis to identify Strengths, Weakness, Opportunities and Threats (SWOT) in multisectoral collaboration, and implications for prevention approaches. Results: We found strengths in the new ways the PH and OH worked together in several instances; and identified weaknesses in the boundaries that constrain PH and OH sectors and relate to communication with the public. Threats to worker protections were revealed in policy gaps. Opportunities existed to enhance multisectoral PH and OH collaboration and the response to the risk of COVID-19 and potentially other infectious diseases to better protect the health of workers. Discussion: Multisectoral collaboration and mutual learning may offer ways to overcome challenges that threaten and constrain cooperation between PH and OH. A more synchronized approach to addressing workers' occupational determinants of health could better protect workers and the public from infectious diseases.

Patterns of enteric infections in a population-wide cohort study of sequelae, British Columbia, Canada.

We assessed patterns of enteric infections caused by 14 pathogens, in a longitudinal cohort study of sequelae in British Columbia (BC) Canada, 2005-2014. Our population cohort of 5.8 million individuals was followed for an average of 7.5 years/person; during this time, 40 523 individuals experienced 42 308 incident laboratory-confirmed, provincially reported enteric infections (96.4 incident infections per 100 000 person-years). Most individuals (38 882/40 523; 96%) had only one, but 4% had multiple concurrent infections or more than one infection across the study. Among individuals with more than one infection, the pathogens and combinations occurring most frequently per individual matched the pathogens occurring most frequently in the BC population. An additional 298 557 new fee-for-service physician visits and hospitalisations for enteric infections, that did not coincide with a reported enteric infection, also occurred, and some may be potentially unreported enteric infections. Our findings demonstrate that sequelae risk analyses should explore the possible impacts of multiple infections, and that estimating risk for individuals who may have had a potentially unreported enteric infection is warranted.

Systematic literature review of SARS-CoV-2 seroprevalence surveys in Canada through April 2021.

Objectives: To estimate the proportion of the population infected by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Canada through April 2021, 16 months into the coronavirus disease 2019 (COVID-19) pandemic and 4 months after COVID-19 vaccines became available. Methods: Publication databases, preprint servers, public health databases and the grey literature were searched for seroprevalence surveys conducted in Canada from 1 November 2019 to 10 July 2021. Studies were assessed for bias using the Joanna Briggs Checklist. Numbers of infections derived from seroprevalence estimates were compared with reported cases to estimate under-ascertainment ratios. Results: In total, 12 serosurveys with 210,321 participants were identified. Three (25%) serosurveys were conducted at national level, one (8.3%) was conducted at provincial level, and eight (66.7%) were conducted at local level. All 12 serosurveys had moderate or high risk of bias. The proportion of the population infected by April 2021 was low (2.6%). The proportion of the population infected was higher in surveys of residents of long-term care facilities (43.0-86%), workers at long-term care facilities (22.4-32.4%), and workers in healthcare institutions (1.4-14%). Conclusions: As of April 2021, the proportion of the population infected by SARS-CoV-2 was low in the overall population of Canada, but was high in healthcare facilities, particularly long-term care facilities, supporting the need for vaccines.

Practicalities of implementing burden of disease research in Africa: lessons from a population survey component of our multi-partner FOCAL research project.

BACKGROUND: Collaborative research is being increasingly implemented in Africa to study health-related issues, for example, the lack of evidence on disease burden, in particular for the presumptive high load of foodborne diseases. The FOCAL (Foodborne disease epidemiology, surveillance, and control in African LMIC) Project is a multi-partner study that includes a population survey to estimate the foodborne disease burden in four African low- and middle-income countries (LMICs). Our multi-partner study team had members from seven countries, all of whom contributed to the project from the grant application stage, and who play(ed) specific roles in designing and implementing the population survey. MAIN TEXT: In this paper, we applied Larkan et al.'s framework for successful research partnerships in global health to self-evaluate our project's collaboration, management, and implementation process. Our partnership formation considered the interplay and balance between operations and relations. Using Larkan et al.'s seven core concepts (i.e., focus, values, equity, benefit, communication, leadership, and resolution), we reviewed the process stated above in an African context. CONCLUSION: Through our current partnership and research implementing a population survey to study disease burden in four African LMICs, we observed that successful partnerships need to consider these core concepts explicitly, apply the essential leadership attributes, perform assessment of external contexts before designing the research, and expect differences in work culture. While some of these experiences are common to research projects in general, the other best practices and challenges we discussed can help inform future foodborne disease burden work in Africa.

Studying Factors Affecting Success of Antimicrobial Resistance Interventions through the Lens of Experience: A Thematic Analysis.

Antimicrobial resistance (AMR) affects the environment, and animal and human health. Institutions worldwide have applied various measures, some of which have reduced antimicrobial use and AMR. However, little is known about factors influencing the success of AMR interventions. To address this gap, we engaged health professionals, designers, and implementers of AMR interventions in an exploratory study to learn about their experience and factors that challenged or facilitated interventions and the context in which interventions were implemented. Based on participant input, our thematic analysis identified behaviour; institutional governance and management; and sharing and enhancing information as key factors influencing success. Important sub-themes included: correct behaviour reinforcement, financial resources, training, assessment, and awareness of AMR. Overall, interventions were located in high-income countries, the human sector, and were publicly funded and implemented. In these contexts, behaviour patterns strongly influenced success, yet are often underrated or overlooked when designing AMR interventions. Improving our understanding of what contributes to successful interventions would allow for better designs of policies that are tailored to specific contexts. Exploratory approaches can provide encouraging results in complex challenges, as made evident in our study. Remaining challenges include more engagement in this type of study by professionals and characterisation of themes that influence intervention outcomes by context.

Incidence, Demographic, and Seasonal Risk Factors of Infections Caused by Five Major Enteric Pathogens, Ontario, Canada, 2010-2017.

In Canada, enteric infections cause significant health and economic burden. We evaluated the individual characteristics of laboratory-confirmed cases of Campylobacter spp. (n = 28,728), non-typhoidal Salmonella spp. (n = 22,640), Yersinia spp. (n = 1674), Verotoxin-producing Escherichia coli (VTEC; n = 1340), and Listeria monocytogenes (n = 471), reported between 2010 and 2017 inclusive, in Ontario, Canada (population ∼13,500,000). We calculated overall and pathogen-specific annual and mean incidence rates (IRs) for Ontario. We used multivariable Poisson and negative binomial regression models to estimate incidence rate ratios (IRRs) for years, seasons, age groups, and sexes, and we included two-way age and sex interaction terms in the models. Campylobacter and Salmonella infections had the highest IRs whereas Listeria infections had the lowest IRs. None of the infections showed long-term trends over the 8-year study period; however, rates of all five infections were elevated in the summer. More Salmonella, VTEC, and Listeria infections were linked to disease outbreaks than were Campylobacter and Yersinia infections. Overall, mean IRs of Campylobacter, Salmonella, Yersinia, and VTEC infections were highest in children 0-4 years old, whereas Listeria IRs peaked in adults 60 years and older. Higher mean IRs of Campylobacter were observed in males. No other differences by sex were statistically significant. The same mean rate was observed in both sexes for Listeria. Adjusting for all other factors, significant age- and sex-specific differences in IRs were observed in Campylobacter, Salmonella, and VTEC infection rates. No significant interactions of age and sex were found for Yersinia and Listeria infections. Future research should focus on the pathogen-specific socioeconomic, environmental, or agricultural risk factors that might be responsible for these infections.

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

Background: With 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 methods: We 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. Results: Participants 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. Conclusion: The 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.

NextGen Public Health Surveillance and the Internet of Things (IoT).

Recent advances in technology have led to the rise of new-age data sources (e.g., Internet of Things (IoT), wearables, social media, and mobile health). IoT is becoming ubiquitous, and data generation is accelerating globally. Other health research domains have used IoT as a data source, but its potential has not been thoroughly explored and utilized systematically in public health surveillance. This article summarizes the existing literature on the use of IoT as a data source for surveillance. It presents the shortcomings of current data sources and how NextGen data sources, including the large-scale applications of IoT, can meet the needs of surveillance. The opportunities and challenges of using these modern data sources in public health surveillance are also explored. These IoT data ecosystems are being generated with minimal effort by the device users and benefit from high granularity, objectivity, and validity. Advances in computing are now bringing IoT-based surveillance into the realm of possibility. The potential advantages of IoT data include high-frequency, high volume, zero effort data collection methods, with a potential to have syndromic surveillance. In contrast, the critical challenges to mainstream this data source within surveillance systems are the huge volume and variety of data, fusing data from multiple devices to produce a unified result, and the lack of multidisciplinary professionals to understand the domain and analyze the domain data accordingly.

Characterizing social-ecological context and success factors of antimicrobial resistance interventions across the One Health spectrum: analysis of 42 interventions targeting E. coli.

BACKGROUND: Antimicrobial resistance (AMR) is among the most pressing One Health issues. While interventions and policies with various targets and goals have been implemented, evidence about factors underpinning success and failure of interventions in different sectors is lacking. The objective of this study is to identify characteristics of AMR interventions that increase their capacity to impact AMR. This study focuses on AMR interventions targeting E. coli. METHODS: We used the AMR-Intervene framework to extract descriptions of the social and ecological systems of interventions to determine factors contributing to their success. RESULTS: We identified 52 scientific publications referring to 42 unique E. coli AMR interventions. We mainly identified interventions implemented in high-income countries (36/42), at the national level (16/42), targeting primarily one sector of society (37/42) that was mainly the human sector (25/42). Interventions were primarily funded by governments (38/42). Most intervention targeted a low leverage point in the AMR system, (36/42), and aimed to change the epidemiology of AMR (14/42). Among all included publications, 55% (29/52) described at least one success factor or obstacle (29/52) and 19% (10/52) identified at least one success factor and one obstacle. Most reported success factors related to communication between the actors and stakeholders and the role of media, and stressed the importance of collaboration between disciplines and external partners. Described obstacles covered data quality, access to data and statistical analyses, and the validity of the results. CONCLUSIONS: Overall, we identified a lack of diversity regarding interventions. In addition, most published E. coli interventions were poorly described with limited evidence of the factors that contributed to the intervention success or failure. Design and reporting guidelines would help to improve reporting quality and provide a valuable tool for improving the science of AMR interventions.

Burden of foodborne diseases: think global, act local.

National burden of foodborne disease (FBD) studies are essential to establish food safety as a public health priority, rank diseases, and inform interventions. In recent years, various countries have taken steps to implement them. Despite progress, the current burden of disease landscape remains scattered, and researchers struggle to translate findings to input for policy. We describe the current knowledge base on burden of FBDs, highlight examples of well-established studies, and how results have been used for decision-making. We discuss challenges in estimating burden of FBD in low-resource settings, and the experience and opportunities deriving from a large-scale research project in these settings. Lastly, we highlight the role of international organizations and initiatives in supporting countries to develop capacity and conduct studies.

Area-Level Clustering of Shiga Toxin-Producing Escherichia coli Infections and Their Socioeconomic and Demographic Factors in Ontario, Canada: An Ecological Study.

Shiga toxin-producing Escherichia coli (STEC) infections are an important health burden for human populations in Ontario and worldwide. We assessed 452 STEC cases that were reported to Ontario's reportable disease surveillance system between 2015 and 2017. A retrospective scan statistic using a Poisson model was used to detect high-rate STEC clusters at the forward sortation area (FSA; the first three digits of a postal code) level. A significant spatial cluster in the southwest region of Ontario was identified. A case-case logistic regression analysis was applied to compare FSA-level socioeconomic and demographic characteristics among STEC cases included inside the spatial cluster with cases outside of the cluster. Cases included in the spatial cluster had higher odds of living in FSAs with a low median family income, low proportion of lone-parent families, and low proportion of the visible minority population. In addition, STEC cases inside the cluster had higher odds of coming from rural FSAs. Our study demonstrated that STEC cases were spatially clustered in Ontario and their clustering was associated with FSA-level socioeconomic and demographic determinants of cases.