Estimates of foodborne illness are important for setting food safety priorities and making public health policies. The objective of this analysis is to estimate domestically acquired, foodborne illness in Canada, while identifying data gaps and areas for further research. Estimates of illness due to 30 pathogens and unspecified agents were based on data from the 2000-2010 time period from Canadian surveillance systems, relevant international literature, and the Canadian census population for 2006. The modeling approach required accounting for under-reporting and underdiagnosis and to estimate the proportion of illness domestically acquired and through foodborne transmission. To account for uncertainty, Monte Carlo simulations were performed to generate a mean estimate and 90% credible interval. It is estimated that each year there are 1.6 million (1.2-2.0 million) and 2.4 million (1.8-3.0 million) episodes of domestically acquired foodborne illness related to 30 known pathogens and unspecified agents, respectively, for a total estimate of 4.0 million (3.1-5.0 million) episodes of domestically acquired foodborne illness in Canada. Norovirus, Clostridium perfringens, Campylobacter spp., and nontyphoidal Salmonella spp. are the leading pathogens and account for approximately 90% of the pathogen-specific total. Approximately one in eight Canadians experience an episode of domestically acquired foodborne illness each year in Canada. These estimates cannot be compared with prior crude estimates in Canada to assess illness trends as different methodologies were used.
Foodborne illness estimates help to set food safety priorities and create public health policies. The Public Health Agency of Canada estimates that 4 million episodes of foodborne illness occur each year in Canada due to 30 known pathogens and unspecified agents. The main objective of this study was to estimate the number of domestically acquired foodborne illness–related hospitalizations and deaths. Using the estimates of foodborne illness for Canada along with data from the Canadian Hospitalization Morbidity Database (for years 2000–2010) and relevant international literature, the number of hospitalizations and deaths for 30 pathogens and unspecified agents were calculated. Analysis accounted for under-reporting and underdiagnosis. Estimates of the proportion foodborne and the proportion travel-related were incorporated for each pathogen. Monte Carlo simulations were performed to account for uncertainty generating mean estimates and 90% probability intervals. It is estimated that each year there are 4000 hospitalizations (range 3200–4800) and 105 (range 75–139) deaths associated with domestically acquired foodborne illness related to 30 known pathogens and 7600 (range 5900–9650) hospitalizations and 133 (range 77–192) deaths associated with unspecified agents, for a total estimate of 11,600 (range 9250–14,150) hospitalizations and 238 (range 155–323) deaths associated with domestically acquired foodborne illness in Canada. Key pathogens associated with these hospitalizations or deaths include norovirus, nontyphoidal Salmonella spp., Campylobacter spp., VTEC O157 and Listeria monocytogenes. This is the first time Canada has established pathogen-specific estimates of domestically acquired foodborne illness–related hospitalizations and deaths. This information illustrates the substantial burden of foodborne illness in Canada.
Salmonella is an important human pathogen, and production animals as well as water are known potential sources. This study helped provide insight into the epidemiology of Salmonella by comparing Salmonella strains found in humans to those detected in production animals and water in the same geographic area and time frame. Salmonella was found in 55% of broiler, 30% of swine, 13% of dairy, and 10% of beef manure samples and 23% of water samples. At the farm level, Salmonella was found on 93% of broiler, 81% of swine, 32% of beef and 30% of dairy farms. Salmonella strains of importance to public health were found in all sources tested; however, they appeared to be more common in the broilers. A number of the farms in this study were mixed farms, in that they had more than one production animal species on the farm. At both the sample and farm levels, beef-only farms had a significantly lower Salmonella prevalence (5% and 7%, respectively) than beef farms with additional production animal species (e.g. poultry) (12% and 42%, respectively) (P ≤ 0.05). Additionally, a number of mixed farms had more than one commodity sampled for this study and similar Salmonella strains by phage type and PFGE were found in the poultry and the other sampled commodity on the farm. This information can help inform the evidence base needed to help target interventions and modify best practices in production agriculture.
BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the COVID-19 pandemic, is capable of infecting a variety of wildlife species. Wildlife living in close contact with humans are at an increased risk of SARS-CoV-2 exposure and if infected have the potential to become a reservoir for the pathogen, making control and management more difficult.ObjectiveTo conduct SARS-CoV-2 surveillance in urban wildlife from Ontario and Québec, Canada, increasing our knowledge of the epidemiology of the virus and our chances of detecting spillover from humans into wildlife.MethodsUsing a One Health approach, we leveraged activities of existing research, surveillance, and rehabilitation programs among multiple agencies to collect samples from 776 animals from 17 different wildlife species between June 2020 and May 2021. Samples from all animals were tested for the presence of SARS-CoV-2 viral RNA, and a subset of samples from 219 animals across 3 species (raccoons, Procyon lotor; striped skunks, Mephitis mephitis; and mink, Neovison vison) were also tested for the presence of neutralizing antibodies.ResultsNo evidence of SARS-CoV-2 viral RNA or neutralizing antibodies was detected in any of the tested samples.ConclusionAlthough we were unable to identify positive SARS-CoV-2 cases in wildlife, continued research and surveillance activities are critical to better understand the rapidly changing landscape of susceptible animal species. Collaboration between academic, public and animal health sectors should include experts from relevant fields to build coordinated surveillance and response capacity.
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