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Background: Cardiovascular disease is a leading cause of death in Canada, but how the major cardiovascular risk factors vary across ethnicity and immigration status has yet to be examined. Methods: Using data from the Canadian Community Health Surveys, national trends in health conditions (hypertension, diabetes, high blood cholesterol level, and obesity) and health behaviours (smoking, activity levels, and alcohol consumption) were estimated for the period 2001-2018. In this cross-sectional study, the trends were then compared across sex, age, ethnicity, and immigration status. Results: A total of 1,065,391 respondents were examined, for the period 2001-2018. During the study period, the prevalence of the following risk factors increased in Canada over time, as follows: diabetes by 54.5%; hypertension by 23.4%; and obesity by 32.3%. For health behaviours, smoking prevalence decreased overall, especially in racialized populations. Heavy drinking was most prevalent for nonracialized and non-Indigenous Canadian-born populations, and was of lowest prevalence among racialized immigrants. Physical inactivity was most prevalent for racialized immigrant populations. The prevalence of self-reported heart disease decreased by 21.0%, except for racialized established immigrants (≥ 10 years since immigration to Canada), who had a 4.2% increase. Conclusions: During this study period, decreases occurred in the prevalences of smoking and physical inactivity, along with increases in obesity, diabetes, and hypertension prevalences. By migration-group status, established immigrants in Canada had a higher prevalence of cardiovascular disease risk factors compared to that among their Canadian-born counterparts. Migration gaps should be considered in future interventions targeted at reducing these cardiovascular risk factors in Canada.
Contexte: Les maladies cardiovasculaires sont une cause majeure de décès au Canada, mais la manière dont les principaux facteurs de risque cardiovasculaire varient en fonction de l'origine ethnique et du statut d'immigration n'a encore jamais été évaluée. Méthodologie: Des tendances nationales dans certains problèmes de santé (hypertension, diabète, hypercholestérolémie et obésité) et certains comportements liés à la santé (tabagisme, niveaux d'activité et consommation d'alcool) ont été dégagées à partir des données de l'Enquête sur la santé dans les collectivités canadiennes pour la période de 2001 à 2018. Ces tendances ont ensuite été comparées en fonction du sexe, de l'âge, de l'origine ethnique et du statut d'immigration dans le cadre de la présente étude transversale. Résultats: Au total, 1 065 391 répondants ont été examinés pour la période de 2001 à 2018. Durant la période de l'étude, la prévalence des facteurs de risque suivants a graduellement augmenté au Canada : diabète, de 54,5 %; hypertension, de 23,4 %; obésité, de 32,3 %. Dans le cas des comportements liés à la santé, la prévalence du tabagisme a globalement diminué, surtout dans les populations racialisées. La consommation excessive d'alcool était plus fréquente dans les populations non racialisées et non autochtones d'origine canadienne, et moins fréquente chez les immigrants racialisés. L'inactivité physique était particulièrement répandue dans les populations immigrantes racialisées. La prévalence des maladies cardiaques auto-déclarées a diminué de 21,0 %, sauf chez les immigrants établis racialisés (≥ 10 ans depuis l'arrivée au Canada), qui a connu une hausse de 4,2 %. Conclusions: Durant la période de l'étude, la prévalence du tabagisme et de l'inactivité physique a diminué tandis que celle de l'obésité, du diabète et de l'hypertension a augmenté. D'après le statut du groupe de migration, la prévalence des facteurs de risque de maladies cardiovasculaires était plus élevée chez les immigrants établis au Canada que chez leurs homologues nés au Canada. Il convient de prendre en considération les différences liées à la migration dans les interventions futures visant à réduire ces facteurs de risque cardiovasculaire au Canada.
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BACKGROUND: Day-to-day variation in the measurement of SARS-CoV-2 in wastewater can challenge public health interpretation. We assessed a Bayesian smoothing and forecasting method previously used for surveillance and short-term projection of COVID-19 cases, hospitalizations, and deaths. METHODS: SARS-CoV-2 viral measurement from the sewershed in Ottawa, Canada, sampled at the municipal wastewater treatment plant from July 1, 2020, to February 15, 2022, was used to assess and internally validate measurement averaging and prediction. External validation was performed using viral measurement data from influent wastewater samples from 15 wastewater treatment plants and municipalities across Ontario. RESULTS: Plots of SARS-CoV-2 viral measurement over time using Bayesian smoothing visually represented distinct COVID-19 "waves" described by case and hospitalization data in both initial (Ottawa) and external validation in 15 Ontario communities. The time-varying growth rate of viral measurement in wastewater samples approximated the growth rate observed for cases and hospitalization. One-week predicted viral measurement approximated the observed viral measurement throughout the assessment period from December 23, 2020, to August 8, 2022. An uncalibrated model showed underprediction during rapid increases in viral measurement (positive growth) and overprediction during rapid decreases. After recalibration, the model showed a close approximation between observed and predicted estimates. CONCLUSION: Bayesian smoothing of wastewater surveillance data of SARS-CoV-2 allows for accurate estimates of COVID-19 growth rates and one- and two-week forecasting of SARS-CoV-2 in wastewater for 16 municipalities in Ontario, Canada. Further assessment is warranted in other communities representing different sewersheds and environmental conditions.
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Teorema de Bayes , COVID-19 , SARS-CoV-2 , Aguas Residuales , Aguas Residuales/virología , COVID-19/epidemiología , Ontario/epidemiología , Humanos , Predicción , Monitoreo Epidemiológico Basado en Aguas Residuales , Monitoreo del Ambiente/métodosRESUMEN
The effective reproduction number, [Formula: see text], is an important epidemiological metric used to assess the state of an epidemic, as well as the effectiveness of public health interventions undertaken in response. When [Formula: see text] is above one, it indicates that new infections are increasing, and thus the epidemic is growing, while an [Formula: see text] is below one indicates that new infections are decreasing, and so the epidemic is under control. There are several established software packages that are readily available to statistically estimate [Formula: see text] using clinical surveillance data. However, there are comparatively few accessible tools for estimating [Formula: see text] from pathogen wastewater concentration, a surveillance data stream that cemented its utility during the COVID-19 pandemic. We present the [Formula: see text] package ern that aims to perform the estimation of the effective reproduction number from real-world wastewater or aggregated clinical surveillance data in a user-friendly way.
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COVID-19 , Programas Informáticos , Aguas Residuales , Humanos , COVID-19/epidemiología , SARS-CoV-2/aislamiento & purificación , Pandemias , Número Básico de Reproducción , Monitoreo EpidemiológicoRESUMEN
Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered 'low risk' when the per capita viral load was 85 × 106 N2 gc/pd. A 'medium risk' occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a 'medium-high' risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a 'high risk' occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.
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COVID-19 , Humanos , COVID-19/epidemiología , SARS-CoV-2 , Ciudades/epidemiología , Pradera , Aguas Residuales , Monitoreo Epidemiológico Basado en Aguas Residuales , Saskatchewan/epidemiologíaRESUMEN
SETTING: The Canadian Community Health Survey (CCHS) is one of the world's largest ongoing cross-sectional population health surveys, with over 130,000 respondents every two years or over 1.1 million respondents since its inception in 2001. While the survey remains relatively consistent over the years, there are differences between cycles that pose a challenge to analyze the survey over time. INTERVENTION: A program package called cchsflow was developed to transform and harmonize CCHS variables to consistent formats across multiple survey cycles. An open science approach was used to maintain transparency, reproducibility and collaboration. OUTCOMES: The cchsflow R package uses CCHS survey data between 2001 and 2014. Worksheets were created that identify variables, their names in previous cycles, their category structure, and their final variable names. These worksheets were then used to recode variables in each CCHS cycle into consistently named and labelled variables. Following, survey cycles can be combined. The package was then added as a GitHub repository to encourage collaboration with other researchers. IMPLICATION: The cchsflow package has been added to the Comprehensive R Archive Network (CRAN) and contains support for over 160 CCHS variables, generating a combined data set of over 1 million respondents. By implementing open science practices, cchsflow aims to minimize the amount of time needed to clean and prepare data for the many CCHS users across Canada.
RéSUMé: CONTEXTE: L'Enquête sur la santé dans les collectivités canadiennes (ESCC) est l'une des plus grandes enquêtes transversales sur la santé de la population, avec plus de 130 000 sondés tous les deux ans et plus de 1,1 million de sondés depuis son début en 2001. Tant que l'enquête reste relativement cohérent, il y a des différences entre des cycles qui posent une challenge majeure pour analyser l'enquête au fil du temps. INTERVENTION: Un paquet de programme appelé cchsflow a été développé pour transformer et harmoniser les variables CCHS aux formats cohérents à travers plusieurs cycles de sondage. Une approche de science ouverte était utilisée pour maintenir la transparence, la reproductibilité et la collaboration. RéSULTATS: Le paquet cchsflow R développé utilisait les données d'enquête de l'ESCC entre 2001 et 2014. Les feuilles de calcul ont été créées pour identifier des variables, leurs noms dans des cycles précédents, leurs structures de catégories et leurs noms de variables finales. Ces feuilles de calcul ont ensuite été utilisées pour recoder les variables dans chaque cycle de l'ESCC pour générer les ensembles de données harmonisés qui peuvent être combiner dans un ensemble de données constamment étiqueté pour l'analyse. Le paquet a ensuite été ajouté comme un entrepôt de GitHub pour encourager la collaboration avec les autres chercheurs. IMPLICATION: Le paquet cchsflow a été ajouté au Comprehensive R Archive Network (CRAN) et contient un appui pour plus de 160 variables de l'ESCC, générant un ensemble de données de plus d'un million de sondés. En exécutant les pratiques de sciences ouvertes, cchsflow vise à minimiser le temps requis pour nettoyer et préparer les données pour les plusieurs utilisateurs du CCHS à travers le Canada.