Impact of the COVID-19 Pandemic on Food Safety Inspection Outcomes in Toronto, Canada: A Bayesian Interrupted Time Series Analysis.

The coronavirus (COVID-19) pandemic resulted in major disruptions to the food service industry and regulatory food inspections. The objective of this study was to conduct an interrupted time series analysis to investigate the impact of the COVID-19 pandemic on food safety inspection trends in Toronto, Canada. Inspection data for restaurants and take-out establishments were obtained from 2017 to 2022 and summarized as weekly counts of inspections, pass ratings, and total infractions. Bayesian segmented regression was conducted to evaluate the impact of the pandemic on weekly infraction and inspection pass rates. On average, a 0.31-point lower weekly infraction rate (95% credible interval [CI]: 0.23, 0.40) and a 2.0% higher probability of passing inspections (95% CI: 1.1%, 3.0%) were predicted in the pandemic period compared to prepandemic. Models predicted lower infraction rates and higher pass rates immediately following the pandemic, with additional variability compared to the prepandemic period, that were regressing back toward pre-pandemic levels in 2022. Seasonal effects were also identified, with infraction rates highest in April and pass rates lowest in August. The COVID-19 pandemic resulted in an initial positive effect on food safety outcomes in restaurants and take-out food establishments in Toronto, but this effect appears to be temporary. This finding could be due to the beneficial impact of COVID-19 protection measures in these establishments or other factors such as less volume of customers. Additional research is needed to investigate causes of the identified differences as well as seasonal and long-term inspection trends postpandemic. Results can inform future food safety inspection planning, outreach, and pandemic preparedness.

Recreational water exposures and illness outcomes at a freshwater beach in Toronto, Canada: A prospective cohort pilot study.

BACKGROUND: Swimming and other recreational water activities in surface waters are popular in Canada during the summer. However, these activities can also increase the risk of recreational water illness. While routine monitoring of beach water quality is conducted by local authorities each summer, little research is available in Canada about beach exposures and illness risks. METHODS: We conducted a pilot of a prospective cohort study at a popular beach in Toronto, Ontario, Canada, in 2022 to determine characteristics of beachgoers, common water and sand exposures, the incidence of recreational water illness, and the feasibility for a larger, national cohort study. We enrolled beachgoers on-site and surveyed about their exposures at the beach and conducted a follow-up survey 7 days following their beach visit to ascertain acute gastrointestinal, respiratory, skin, ear, and eye illness outcomes. We descriptively tabulated and summarized the collected data. RESULTS: We enrolled 649 households, consisting of 831 beachgoers. Water contact activities were reported by 56% of beachgoers, with swimming being the most common activity (44% of participants). Similarly, 56% of beachgoers reported digging in the sand or burying themselves in the sand. Children (≤14 years) and teenagers (15-19 years) were most likely to report engaging in water contact activities and swallowing water, while children were most likely to report sand contact activities and getting sand in their mouth. Boys and men were more likely than women and girls to report swallowing water (15.2% vs. 9.4%). Water and sand exposures also differed by household education level and participant ethno-racial identity. E. coli levels in beach water were consistently low (median = 20 CFU/100 mL, range = 10-58). The incidence of illness outcomes was very low (0.3-2.8%) among the 287 participants that completed the follow-up survey. CONCLUSIONS: The identified beach exposure patterns can inform future risk assessments and communication strategies. Excellent water quality was observed at the studied beach, likely contributing to the low incidence of illnesses. A larger, national cohort study is needed in Canada to examine risks of illness at beaches at higher risk of fecal contamination.

Environmental Health Services and Professionals Level of Engagement in Different Sectors in Eastern Ethiopia: A Mixed Methods Study Design.

INTRODUCTION: Environmental health (EH) services have a long history in Ethiopia, but data on environmental health services quality and the magnitude of environmental health professionals' engagement has never been addressed. This study was conducted to assess the quality of environmental health services in different sectors and professionals' level of engagement in Eastern Ethiopia. METHODS: Institution based cross-sectional mixed study design was implemented. A cluster sampling technique was employed to select 83 participants. Data were collected using a pretested questionnaire and an interview guide. Descriptive, bivariate, multivariate, and thematic analysis was carried out. RESULTS: Professionals' performance in most services were reported to be average or low. Only 19.5% of participants responded as having good satisfaction in their job. The multiple logistic regression analysis showed factors associated with selected environmental health services. The odds of identifying environmental problems was associated with profession (adjusted odds ratio (AOR): 4.1; 95% confidence interval (CI): 1.3-7.6) and level of education (AOR: 3.1; 95%CI: 0.9-5.9). The factors contributing to introducing innovative solutions to EH problems were type of institution (AOR: 3.1, 95%CI = 1.6-9.3), profession (AOR: 3.4, 95%CI = 1.1-12.2), and level of support and emphasis offered (OR: 5.6, 95% CI = 2.2-11.9). Level of job satisfaction was also associated with the above-mentioned independent variables. CONCLUSION: The current study showed low level of professionals' engagement and factors associated with the quality of environmental health services in different sectors. Therefore, Ethiopian Federal Ministry of Health and other concerned ministries, agencies, and authorities should intervene accordingly to improve the service and level of professionals' engagement.

The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review.

BACKGROUND: Self-diagnosis is the process of diagnosing or identifying a medical condition in oneself. Artificially intelligent digital platforms for self-diagnosis are becoming widely available and are used by the general public; however, little is known about the body of knowledge surrounding this technology. OBJECTIVE: The objectives of this scoping review were to (1) systematically map the extent and nature of the literature and topic areas pertaining to digital platforms that use computerized algorithms to provide users with a list of potential diagnoses and (2) identify key knowledge gaps. METHODS: The following databases were searched: PubMed (Medline), Scopus, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers, Google Scholar, Open Grey, and ProQuest Dissertations and Theses. The search strategy was developed and refined with the assistance of a librarian and consisted of 3 main concepts: (1) self-diagnosis; (2) digital platforms; and (3) public or patients. The search generated 2536 articles from which 217 were duplicates. Following the Tricco et al 2018 checklist, 2 researchers screened the titles and abstracts (n=2316) and full texts (n=104), independently. A total of 19 articles were included for review, and data were retrieved following a data-charting form that was pretested by the research team. RESULTS: The included articles were mainly conducted in the United States (n=10) or the United Kingdom (n=4). Among the articles, topic areas included accuracy or correspondence with a doctor's diagnosis (n=6), commentaries (n=2), regulation (n=3), sociological (n=2), user experience (n=2), theoretical (n=1), privacy and security (n=1), ethical (n=1), and design (n=1). Individuals who do not have access to health care and perceive to have a stigmatizing condition are more likely to use this technology. The accuracy of this technology varied substantially based on the disease examined and platform used. Women and those with higher education were more likely to choose the right diagnosis out of the potential list of diagnoses. Regulation of this technology is lacking in most parts of the world; however, they are currently under development. CONCLUSIONS: There are prominent research gaps in the literature surrounding the use of artificially intelligent self-diagnosing digital platforms. Given the variety of digital platforms and the wide array of diseases they cover, measuring accuracy is cumbersome. More research is needed to understand the user experience and inform regulations.