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

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.

Using Wastewater Surveillance to Monitor Gastrointestinal Pathogen Infections in the State of Oklahoma

During the COVID-19 pandemic, wastewater surveillance was widely used to monitor temporal and geographical infection trends. Using this as a foundation, a statewide program for routine wastewater monitoring of gastrointestinal pathogens was established in Oklahoma. The results from 18 months of surveillance showed that wastewater concentrations of Salmonella, Campylobacter, and norovirus exhibit similar seasonal patterns to those observed in reported human cases (F = 4-29, p < 0.05) and that wastewater can serve as an early warning tool for increases in cases, offering between one- and two-weeks lead time. Approximately one third of outbreak alerts in wastewater correlated in time with confirmed outbreaks of Salmonella or Campylobacter and our results further indicated that several outbreaks are likely to go undetected through the traditional surveillance approach currently in place. Better understanding of the true distribution and burden of gastrointestinal infections ultimately facilitates better disease prevention and control and reduces the overall socioeconomic and healthcare related impact of these pathogens. In this respect, wastewater represents a unique opportunity for monitoring infections in real-time, without the need for individual human testing. With increasing demands for sustainable and low-cost disease surveillance, the usefulness of wastewater as a long-term method for tracking infectious disease transmission is likely to become even more pronounced.

Comparison of antimicrobial resistance among Salmonella enterica serovars isolated from Canadian turkey flocks, 2013-2021

The emergence of antimicrobial resistance (AMR) in Salmonella from turkeys has raised a food safety concern in Canada as certain serovars have been implicated in human salmonellosis outbreaks in recent years. While several studies evaluated AMR in broiler chickens in Canada, there are limited studies that assess AMR in turkey flocks. This study analyzed data collected between 2013 and 2021 by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) farm turkey surveillance program to determine the prevalence of AMR and differences in resistance patterns among Salmonella serovars recovered from turkey flocks. Salmonella isolates were tested for susceptibility to 14 antimicrobials using a microbroth dilution method. Hierarchical clustering dendrograms were constructed to compare the individual AMR status of Salmonella serovars. Differences in the probability of resistance between Salmonella serovars were determined using generalized estimating equation logistic regression models to account for farm-level clustering. Of the 1,367 Salmonella isolates detected, 55.3% were resistant to at least one antimicrobial and 25.3% were multidrug resistant (MDR) (resistant to ≥3 antimicrobial classes). The Salmonella isolates exhibited high resistance to tetracycline (43.3%), streptomycin (47.2%), and sulfisoxazole (29.1%). The 3 most frequently occurring serovars were S. Uganda (22.9%), S. Hadar (13.5%), and S. Reading (12.0%). Streptomycin-sulfisoxazole-tetracycline (n = 204) was the most frequent MDR pattern identified. Heatmaps showed that S. Reading exhibited coresistance to the quinolone class antimicrobials, ciprofloxacin, and nalidixic acid; S. Heidelberg to gentamicin and sulfisoxazole; and S. Agona to ampicillin and ceftriaxone. Salmonella Hadar isolates had higher odds of resistance to tetracycline (OR: 152.1, 95% CI: 70.6-327.4) while the probability of being resistant to gentamicin and ampicillin was significantly higher in S. Senftenberg than in all the other serovars. Moreover, S. Uganda had the highest odds of being MDR (OR: 4.7, 95% CI: 3.7-6.1). The high resistance observed warrants a reassessment of the drivers for AMR, including AMU strategies and other production factors. Differences in AMR patterns highlight the need to implement serovar-specific mitigation strategies.

The Evolutionary Game Analysis of Low Carbon Production Behaviour of Farmers, Government and Consumers in Food Safety Source Governance

Whether the quality of agricultural products is safe or not is related to issues of food safety and low carbon production in agriculture. Based on evolutionary game theory, this paper establishes a game model among government, farmers and consumers and analyzes the dynamic evolutionary process and evolutionary stable strategies of the major stakeholders. The results show that: (i) government subsidy coefficient, farmers' penalty coefficient for not producing, consumer trust coefficient and willingness to pay carbon labelled agricultural products premium are positively related to farmers' adoption of low-carbon production behaviour, and fraud penalty coefficient and farmers' cost of adopting low-carbon production technology are negatively related; (ii) farmers' sensitivity to government regulation policies is: fraud penalty coefficient = farmers' cost of adopting low-carbon production technology > government subsidy The sensitivity of farmers to government regulation policies is: fraud penalty coefficient = cost of low-carbon production technology > government subsidy > penalty coefficient for non-production, and the sensitivity of farmers to direct market stimulation is: consumer trust coefficient > coefficient of willingness to pay premium for carbon labelled agricultural products, and the additional benefit coefficient has no significant effect on farmers' decision-making; (iii) In the early stage, the source control of food safety mainly depends on the government's policy intervention. In the later stage, the establishment of carbon label agricultural products market incentive mechanism can achieve long-term stable and effective source control of food safety.