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Psychosocial factors are related to immune, viral, and vaccination outcomes. Yet, this knowledge has been poorly represented in public health initiatives during the COVID-19 pandemic. This review provides an overview of biopsychosocial links relevant to COVID-19 outcomes by describing seminal evidence about these associations known prepandemic as well as contemporary research conducted during the pandemic. This focuses on the negative impact of the pandemic on psychosocial health and how this in turn has likely consequences for critically relevant viral and vaccination outcomes. We end by looking forward, highlighting the potential of psychosocial interventions that could be leveraged to support all people in navigating a postpandemic world and how a biopsychosocial approach to health could be incorporated into public health responses to future pandemics.

Leishmania spp. are zoonotic parasites transmitted by phlebotomine sand flies, including those of the Lutzomyia genus, which can cause leishmaniases in both humans and dogs. Lutzomyia spp. are established in many countries in South and Central America and some areas of the southern United States, with suspected potential of these vectors to undergo further range expansion due to climate change. A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses Extensions for Scoping Reviews (PRISMA‐ScR) guidelines to describe the current state of knowledge on the key ecological factors associated with Lutzomyia spp. survival, reproduction and establishment. The following electronic databases were searched for eligible studies published from 1 January 1990, to the date of search, 26 April 2023: CAB Direct (CABI), MEDLINE (via Ovid), Biological Sciences Database and Environmental Sciences Database. Primary research articles that were available in English and focused on ecological factors associated with Lutzomyia spp., such as climatic and habitat factors, geographic range, seasonality and temporality, and host abundance, were eligible for inclusion in the study. Following de‐duplication, a total of 167 studies were included in Level 1 screening, 64 studies were included in Level 2 screening and 31 studies met the criteria for data extraction. Study locations included Argentina, Brazil, Colombia, Peru, Venezuela, the United States, Mexico and Canada, with some studies including multiple regions. A total of 31 different Lutzomyia spp. were assessed across these studies, with most (51.6%) of the studies focused on Lutzomyia longipalpis. Eligible studies investigated factors such as seasonality (n = 5), temperature (n = 19), precipitation (n = 13), humidity (n = 2), vegetation presence or requirements (n = 13), ecotypes (n = 7), and/or community type (i.e., urban, suburban, rural) (n = 5). Lutzomyia spp. activity was found to be higher during the rainy season, and peak when temperatures were between 20 and 25°C. Lutzomyia spp. were also found to preferentially reside in tropical or subtropical forests, which are characterised by their lack of a distinct dry season and high precipitation. This scoping review summarised the current state of the literature on the ecological factors associated with the survival, activity and reproduction of Lutzomyia spp. While there appears to be some consensus in the literature regarding some ecological requirements (such as seasonality, temperature and habitat features), overall, there is a lack of published research in this topic. This poses a significant challenge for future studies, which aim to predict the future distribution of Lutzomyia spp. in the context of climate and land use changes. Additional ecological research is urgently needed on Lutzomyia spp. given their relevance to both human and animal health. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Veterinary Journal / Revue Vétérinaire Canadienne is the property of Canadian Veterinary Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Public health preparedness is based on timely and accurate information. Time series forecasting using disease surveillance data is an important aspect of preparedness. This study compared two approaches of time series forecasting: seasonal auto‐regressive integrated moving average (SARIMA) modelling and the artificial neural network (ANN) algorithm. The goal was to model weekly seasonal influenza activity in Canada using SARIMA and compares its predictive accuracy, based on root mean square prediction error (RMSE) and mean absolute prediction error (MAE), to that of an ANN. Methods: An initial SARIMA model was fit using automated model selection by minimizing the Akaike information criterion (AIC). Further inspection of the autocorrelation function and partial autocorrelation function led to 'manual' model improvements. ANNs were trained iteratively, using an automated process to minimize the RMSE and MAE. Results: A total of 378, 462 cases of influenza was reported in Canada from the 2010–2011 influenza season to the end of the 2019–2020 influenza season, with an average yearly incidence risk of 20.02 per 100,000 population. Automated SARIMA modelling was the better method in terms of forecasting accuracy (per RMSE and MAE). However, the ANN correctly predicted the peak week of disease incidence while the other models did not. Conclusion: Both the ANN and SARIMA models have shown to be capable tools in forecasting seasonal influenza activity in Canada. It was shown that applying both in tandem is beneficial, SARIMA better forecasted overall incidence while ANN correctly predicted the peak week. [ABSTRACT FROM AUTHOR]

Simple Summary: The use of antibiotics by veterinarians can be reduced by providing them with periodic feedback on their antibiotic use. This strategy was evaluated among veterinarians in Canada and Israel by using an interrupted time-series study design. The veterinarians were provided with three feedback reports at an interval. The report contained a visualization comparing their prescribing with their peers. The report was supplemented with a guideline on antibiotic prescribing. It was found that the antibiotic prescribing of the veterinarians reduced significantly with some strong indication of geographical variation in the reduction in antibiotic prescribing due to the periodic feedback. This strategy is highly recommended in a veterinary clinic to reduce the unnecessary use of antibiotics. An interrupted time-series study design was implemented to evaluate the impact of antibiotic stewardship interventions on antibiotic prescribing among veterinarians. A total of 41 veterinarians were enrolled in Canada and Israel and their prescribing data between 2019 and 2021 were obtained. As an intervention, veterinarians periodically received three feedback reports comprising feedback on the participants' antibiotic prescribing and prescribing guidelines. A change in the level and trend of antibiotic prescribing after the administration of the intervention was compared using a multi-level generalized linear mixed-effect negative-binomial model. After the receipt of the first (incidence rate ratios [IRR] = 0.88; 95% confidence interval (CI): 0.79, 0.98), and second (IRR = 0.85; 95% CI: 0.75, 0.97) feedback reports, there was a reduced prescribing rate of total antibiotic when other parameters were held constant. This decline was more pronounced among Israeli veterinarians compared to Canadian veterinarians. When other parameters were held constant, the prescribing of critical antibiotics by Canadian veterinarians decreased by a factor of 0.39 compared to that of Israeli veterinarians. Evidently, antibiotic stewardship interventions can improve antibiotic prescribing in a veterinary setting. The strategy to sustain the effect of feedback reports and the determinants of differences between the two cohorts should be further explored. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Veterinary Research / Revue Canadienne de Recherche Vétérinaire is the property of Canadian Veterinary Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Background: Public health guidelines for chlamydia testing are not sex specific, but young females test at a disproportionally higher rate than males and other age groups. This study aims to describe testing trends across age and sex subgroups, then estimate a test-adjusted incidence of chlamydia in these subgroups to identify gaps in current testing practices. Methods: We used a population-based study to examine observed chlamydia rates by age and sex subgroups: 15–19 years, 20–29 years, 30–39 years and older than 40 years. The study included diagnostic test results recorded by Public Health Ontario Laboratories between Jan. 1, 2010, and Dec. 31, 2018, for individuals living in Peel region, Ontario. We then employed meta-regression models as a method of standardization to estimate the effect of sex and age on standardized morbidity ratio, testing ratio and test positivity, then calculate a test-adjusted incidence of chlamydia for each subgroup. Results: Over the study period, infection, testing and test positivity varied across age and sex subgroups. Observed incidence and testing were highest in females aged 20–29 years, whereas males had the highest standardized test positivity across all age groups. After estimating test-adjusted incidence for each age–sex subgroup, males in the 15–19-year and 30–39-year age groups had an increase in incidence of 60.2% and 9.7%, respectively, compared with the observed incidence. Interpretation: We found that estimated test-adjusted incidence was higher than observed incidence in males aged 15–19 years and 30–39 years. This suggests that infections in males are likely being missed owing to differential testing, and this may be contributing to the persistent increase in reported cases in Canada. Public health programming that targets males, especially in high-risk settings and communities, and use of innovative partner notification methods could be critical to curbing overall rates of chlamydia. [ABSTRACT FROM AUTHOR]

Campylobacter is the second leading cause of foodborne illness in the United States. Although many food production animals carry Campylobacter as commensal bacteria, consumption of poultry is the main source of human infection. Previous research suggests that the biology of Campylobacter results in complete flock colonization within days. However, a recent systematic review found that the on‐farm prevalence of Campylobacter varies widely, with some flocks reporting low prevalence. We hypothesized that the low prevalence of Campylobacter in some flocks may be driven by a delayed introduction of the pathogen. The objectives of this study were to (a) develop a deterministic compartmental model that represents the biology of Campylobacter, (b) identify the parameter values that best represent the natural history of the pathogen in poultry flocks and (c) examine the possibility that a delayed introduction of the pathogen is sufficient to replicate the observed low prevalence examples documented in the literature. A deterministic compartmental model was developed to examine the dynamics of Campylobacter in chicken flocks over a 56‐day time period prior to movement to the abattoir. The model outcome of interest was the final population prevalence of Campylobacter at day 56. The resulting model that incorporated a high transmission rate (β = 1.04) was able to reproduce the wide range of prevalence estimates observed in the literature when pathogen introduction time is varied. Overall, we established that the on‐farm transmission rate of Campylobacter in chickens is likely high and can result in complete colonization of a flock when introduced early. However, delaying the time at which the pathogen enters the flock can reduce the prevalence observed at 56 days. These results highlight the importance of enforcing strict biosecurity measures to prevent or delay the introduction of the bacteria to a flock. [ABSTRACT FROM AUTHOR]

Cyclospora cayetanensis is an emerging food- and waterborne pathogen that causes cyclosporiasis, a gastrointestinal disease in humans. The parasite is endemic in tropical and subtropical regions; however, its prevalence is largely dependent on environmental factors, such as climate and rainfall patterns. The objective of this paper was to conduct a systematic review and meta-analysis to determine the prevalence of C. cayetanensis in water and to determine if geography, water source and other variables influence this prevalence. A literature search was performed using search terms relating to water and C. cayetanensis in MEDLINE®, CAB Direct, Food Science and Technology Abstracts, Agricola databases and Environmental Science Index. Observational studies published in English after 1979 were eligible. Screening, data extraction and risk-of-bias assessment were performed independently by two reviewers. A multi-level random-effects meta-analysis was completed to determine the prevalence of C. cayetanensis in water and subgroup meta-analyses were performed to explore between-study heterogeneity. The search identified 828 unique articles, and after the screening, 33 articles were included in the review. The pooled prevalence of C. cayetanensis in water was 6.90% [95% confidence interval (CI) 2.25%–13.05%, I2 = 84.38%]. Subgroup meta-analyses revealed significant differences in the prevalence between continents. Additionally, laboratory methods between studies were highly variable and these findings highlight the need for further environmental research on C. cayetanensis in water using detection methods that include PCR and sequencing to accurately identify the organism. The results of this study can be used to help assess the risk of waterborne cyclosporiasis. [ABSTRACT FROM AUTHOR]

Background: Despite expected initial universal susceptibility to a novel pandemic pathogen like SARS-CoV-2, the pandemic has been characterized by higher observed incidence in older persons and lower incidence in children and adolescents.Objective: To determine whether differential testing by age group explains observed variation in incidence.Design: Population-based cohort study.Setting: Ontario, Canada.Participants: Persons diagnosed with SARS-CoV-2 and those tested for SARS-CoV-2.Measurements: Test volumes from the Ontario Laboratories Information System, number of laboratory-confirmed SARS-CoV-2 cases from the Integrated Public Health Information System, and population figures from Statistics Canada. Demographic and temporal patterns in incidence, testing rates, and test positivity were explored using negative binomial regression models and standardization. Sources of variation in standardized ratios were identified and test-adjusted standardized infection ratios (SIRs) were estimated by metaregression.Results: Observed disease incidence and testing rates were highest in the oldest age group and markedly lower in those younger than 20 years; no differences in incidence were seen by sex. After adjustment for testing frequency, SIRs were lowest in children and in adults aged 70 years or older and markedly higher in adolescents and in males aged 20 to 49 years compared with the overall population. Test-adjusted SIRs were highly correlated with standardized positivity ratios (Pearson correlation coefficient, 0.87 [95% CI, 0.68 to 0.95]; P < 0.001) and provided a case identification fraction similar to that estimated with serologic testing (26.7% vs. 17.2%).Limitations: The novel methodology requires external validation. Case and testing data were not linkable at the individual level.Conclusion: Adjustment for testing frequency provides a different picture of SARS-CoV-2 infection risk by age, suggesting that younger males are an underrecognized group at high risk for SARS-CoV-2 infection.Primary Funding Source: Canadian Institutes of Health Research. [ABSTRACT FROM AUTHOR]

Background: Norovirus is the most common cause of acute gastroenteritis in Canada. The illness causes great morbidity and high societal costs. The objective of this article is to describe the epidemiology of norovirus in the province of Ontario, Canada from 2009 to 2014.Methods: To assess activity of norovirus and viral gastroenteritis (VGE) in Ontario, three datasets were acquired from the provincial government: two traditional surveillance datasets (outbreak and laboratory) and syndromic surveillance data (telehealth), all spanning 2009-2014. All outbreaks, laboratory submissions and telehealth calls were first assessed for total VGE. Norovirus and norovirus-like illness totals were calculated as a proportion of VGE to estimate agent-specific activity levels. Affected institution types, sexes and age groups were also analyzed.Results: Between 2009 and 2014, 41.5% of VGE outbreaks, 63.4% of VGE laboratory submissions and 36.6% of all acute gastroenteritis-related (not restricted to viral causes) telehealth calls were attributed to norovirus and norovirus-like illness in Ontario. The most commonly affected institution type was long-term care homes and the most commonly affected age groups were younger (younger than five years) and older (older than 65 years) individuals. Females were slightly more frequently affected than males.Conclusion: Norovirus and norovirus-like illnesses were the leading cause of VGE in Ontario between 2009 and 2014. They comprised the greatest percentage of VGE when compared with all other VGE-associated viruses. Additional work is needed to determine all component costs and necessary public health actions to reduce the burden of disease. [ABSTRACT FROM AUTHOR]

Abstract Background The norovirus group (NVG) of caliciviruses are the etiological agents of most institutional outbreaks of gastroenteritis in North America and Europe. Identification of NVG is complicated by the non-culturable nature of this virus, and the absence of a diagnostic gold standard makes traditional evaluation of test characteristics problematic. Methods We evaluated 189 specimens derived from 440 acute gastroenteritis outbreaks investigated in Ontario in 2006–07. Parallel testing for NVG was performed with real-time reverse-transcriptase polymerase chain reaction (RT2-PCR), enzyme immunoassay (EIA) and electron microscopy (EM). Test characteristics (sensitivity and specificity) were estimated using latent class models and composite reference standard methods. The practical implications of test characteristics were evaluated using binomial probability models. Results Latent class modelling estimated sensitivities of RT2-PCR, EIA, and EM as 100%, 86%, and 17% respectively; specificities were 84%, 92%, and 100%; estimates obtained using a composite reference standard were similar. If all specimens contained norovirus, RT2-PCR or EIA would be associated with > 99.9% likelihood of at least one test being positive after three specimens tested. Testing of more than 5 true negative specimens with RT2-PCR would be associated with a greater than 50% likelihood of a false positive test. Conclusion Our findings support the characterization of EM as lacking sensitivity for NVG outbreaks. The high sensitivity of RT2-PCR and EIA permit identification of NVG outbreaks with testing of limited numbers of clinical specimens. Given risks of false positive test results, it is reasonable to limit the number of specimens tested when RT2-PCR or EIA are available.

Copyright of Canadian Veterinary Journal / Revue Vétérinaire Canadienne is the property of Canadian Veterinary Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Veterinary Research / Revue Canadienne de Recherche Vétérinaire is the property of Canadian Veterinary Medical Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a high-mortality global pandemic. The clinical spectrum of disease caused by this virus is broad, ranging from asymptomatic infection to organ failure and death. Risk stratification of individuals with coronavirus disease 2019 (COVID-19) is desirable for management, and prioritization for trial enrollment. We developed a prediction rule for COVID-19 mortality in a population-based cohort in Ontario, Canada. Methods Data from Ontario's provincial iPHIS system were extracted for the period from January 23 to May 15, 2020. Logistic regression–based prediction rules and a rule derived using a Cox proportional hazards model were developed and validated using split-halves validation. Sensitivity analyses were performed, with varying approaches to missing data. Results Of 21 922 COVID-19 cases, 1734 with complete data were included in the derivation set; 1796 were included in the validation set. Age and comorbidities (notably diabetes, renal disease, and immune compromise) were strong predictors of mortality. Four point-based prediction rules were derived (base case, smoking excluded, long-term care excluded, and Cox model–based). All displayed excellent discrimination (area under the curve for all rules > 0.92) and calibration (P  > .50 by Hosmer-Lemeshow test) in the derivation set. All performed well in the validation set and were robust to varying approaches to replacement of missing variables. Conclusions We used a public health case management data system to build and validate 4 accurate, well-calibrated, robust clinical prediction rules for COVID-19 mortality in Ontario, Canada. While these rules need external validation, they may be useful tools for management, risk stratification, and clinical trials. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Medical Association Journal (CMAJ) is the property of CMA Impact Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)