This game presents the daily portrait of the number of confirmed cases of COVID-19 in Quebec. Important note: As of April 12, 2023, the data source for COVID-19 deaths has changed. Data is updated on a weekly basis. Cases and deaths that occurred on the Sunday, Monday and Tuesday before the Wednesday went online are not available. Please refer to the methodology notes for more details.

Ce jeu présente le portrait quotidien du nombre de cas confirmés de COVID-19 au Québec. Note importante : Depuis le 12 avril 2023, la source de données des décès attribuables à la COVID-19 a été modifiée. Les données sont mises à jour hebdomadairement. Les cas et décès ayant eu lieu le dimanche, lundi et mardi précédent la mise en ligne du mercredi ne sont pas disponibles. Veuillez consulter les notes méthodologiques pour plus de détails.

As of April 15, 2023, there had been a total of around 51,921 deaths attributed to COVID-19 in Canada. As of this time, every province and territory has reported deaths, with Quebec and Ontario reporting the highest numbers.

COVID-19 in Canada Canada has recorded almost 4.65 million coronavirus cases since the first infection in the country was confirmed on January 25, 2020. The number of cases by province shows that Ontario and Quebec have been the most severely affected. The number of daily new cases reached record highs at the end of 2021 and began to decrease as spring arrived in 2022.

COVID-19 vaccinations in Canada Seven COVID-19 vaccines have now been approved for use in Canada and vaccines are widely available. As of January 1, 2023 around 83 percent of the Canadian population had received at least one dose of a COVID-19 vaccine. The provinces with the highest share of people fully vaccinated against COVID-19 are Newfoundland and Labrador and Nova Scotia. However, Ontario and Quebec are the provinces with the highest total number of people vaccinated.

Important note - July 6, 2022: Update stopped. Considering the changes in the vaccination recommendations issued on June 20, 2022 by the Committee on Immunization of Quebec, an adaptation of the indicators to assess and monitor vaccination coverage during the fall 2022 campaign is in progress. Since the monitoring of the indicators as they were disseminated up to now is no longer possible, the dataset will no longer be updated for the time being. The files from the last update remain available. This game presented the daily portrait of the vaccination status of new cases and new hospitalizations of COVID-19 in Quebec. The most up-to-date data presented is from the day before.

SARS-CoV-2 wastewater surveillance data and metadata in the Open Data Model format. Part 1: Québec City Authors

• Therrien, J-D¹
• Maere, T.¹
• Sanchez-Quete, F.²
• Tsitouras, A.²
• Goitom, E.³
• Cloutier, F.⁴
• Dufour, D.⁴
• Proulx, F. ⁴
• Nicolaï, N.¹
• Philippe, R.¹
• Tohidi, M.¹
• Dorner, S.³
• Frigon, D.²
• Vanrolleghem, P.A.¹

Affiliations

• ¹ modelEAU, Département de génie civil et de génie des eaux, Université Laval
• ² Microbial Community Engineering Lab (MiCEL), Department of Civil Engineering, McGill University
• ³ Polytechnique Montréal
• ⁴ Ville de Québec

General Remarks

Wastewater-based surveillance of SARS-CoV-2 virus can detect between 1 and 30 infected individuals per 100,000 (including asymptomatic ones) by analyzing the population's sewage. As such, this method is very attractive since it costs only a fraction of clinical testing (as low as 1%). Human faeces may contain the virus a few days before a person becomes ill. Thus, this approach allows for detection of outbreaks 2-7 days before the increase in reported cases stemming from clinical screening tests (Bibby et al., 2021). Wastewater-based surveillance complements clinical testing by geolocating outbreaks, which may help targeting intensive screening programs. Moreover, it provides a quick indication of whether new public health measures (e.g., masks, social distancing, confinement, and curfew) are effective.

Sampling

The reported dataset contains open data collected in the province of Québec as part of the SARS-CoV-2 wastewater-based surveillance program CentrEau-COVID. Four of the largest cities in the province (Montréal, Laval, Québec City, and Trois-Rivières), as well as the municipalities of four rural regions (Mauricie, Centre-du-Québec, Bas-St-Laurent, and Gaspésie) participated in the program. The entire dataset includes 31 sampling sites covering approximately half the population of the province of Québec (population size of 8.5 million). The timeframe covered by the dataset varies for each site. The earliest surveillance program was launched in March 2020, others followed soon after. Samples were collected using various methods, such as 24h composite samples, grab samples, and passive sampling using variations on the Moore swab method (Schang et al., 2020)

Analysis

Prior to the analysis of the samples for SARS-CoV-2, physiochemical parameters such as total suspended solids (TSS), turbidity, conductivity, ammonium concentration, and pH were measured. The samples were subsequently concentred by filtration using a MEC filter (0.45 um), followed by total RNA extraction using the Qiagen AllPrep PowerViral DNA/RNA Kit (Qiagen, USA) with some modifications (beta-mercaptoethanol concentration raised to 10% and lysis performed at 55 °C for 30 minutes) (Ahmed et al., 2020). SARS-CoV-2 viral RNA was detected by a one-step RT-qPCR. To assess the RNA recovery rate of the procedure, samples were spiked before extraction with a known concentration of Bovine Respiratory Syncytial Virus (BRSV) using the Zoetis INFORCE 3 vaccine (Zoetis, USA). In addition to SARS-CoV-2, samples were assessed for Pepper Mild Mottle Virus (PMMoV), the daily load of which is hypothesized to represent the fecal load contributions to the samples at a given site and time. PCR conditions and primer used to collect viral data are described in the files primers.md and PCR conditions.md.

Compilation

The measurements on wastewater samples carried out by the participating laboratories of this study are found in the WWMeasure table. The values provided by municipalities come from laboratories accredited by the Centre d'expertise en analyse environnementale du Québec (CEAEQ), in compliance with the latter's quality assurance protocols. The COVID-19-related public health data found in the CPHD table were collected from the Institut National de Santé Publique du Québec (INSPQ)'s public reports. Wastewater data taken in-situ at the sampling sites (e.g., the flow at pumping stations or water resource recovery facilities (WRRFs)) are found in the SiteMeasure table and were taken by the institutions responsible for managing the sites. All of the data, stemming from multiple sources, were combined into the Open Data Model (ODM) standard format using the ODM-Import python package (see also Structure).

Validation

Wastewater and sample data were manually assessed for quality by our research collaborators. Data points for which the quality appeared to be uncertain were tagged with the value True in the qualityFlag column. Conversely, data deemed of good quality have a quality flag of False. Data that were not checked have a quality flag of NA. Textual comments describing the issues with the data points in more detail are also included in the dataset using the notes column of the relevant tables. Note that data validation was carried out by the data custodians responsible for each city in the dataset according to available resources. As the project continues and data validation is undertaken on more sections of the dataset, data may be re-analyzed, flagged, or commented as needed. Revisions to the dataset will be reported to the best of our ability.

Structure

The data contained in this dataset has been structured according to the Open Data Model (ODM) for Wastewater-Based Surveillance. This model provides a standardized dictionary to collect and share data and metadata stemming from wastewater-based surveillance programs. By convention, it splits all data into 10+ thematic tables with each record representing a unique measurement, i.e., long format. For convenience, the wide folder presents the data found in all the other tables in a wide format, i.e., multiple measurements are aligned by timestamp, with each column representing a different parameter.

Acknowledgements

The authors would like to acknowledge that this dataset was collected thanks to the financial support of the Fonds de Recherche du Québec, the Molson Foundation, the Trottier Family Foundation, CentrEau and NSERC. The authors would also like to acknowledge the efforts of Douglas Manuel (Ottawa Hospital) and Howard Swerdfeger (Public Health Agency of Canada) for their original idea for the Open Data Model and continued development.

References

1. Ahmed, W., Bertsch, P.M., Bivins, A., Bibby, K., Farkas, K., Gathercole, A., Haramoto, E., Gyawali, P., Korajkic, A., McMinn, B.R., Mueller, J.F., Simpson, S.L., Smith, W.J.M., Symonds, E.M., Thomas, K. v., Verhagen, R., Kitajima, M., 2020. Comparison of virus concentration methods for the RT-qPCR-based recovery of murine hepatitis virus, a surrogate for SARS-CoV-2 from untreated wastewater. Science of the Total Environment 739. https://doi.org/10.1016/j.scitotenv.2020.139960

2. Bibby, K., Bivins, A., Wu, Z., North, D., 2021. Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19. Water Research 202, 117438. https://doi.org/10.1016/j.watres.2021.117438

3. Schang, C., Crosbie, N., Nolan, M., Poon, R., Wang, M., Jex, A., Scales, P., Schmidt, J., Thorley, B.R., Henry, R., Kolotelo, P., Langeveld, J., Schilperoort, R., Shi, B., Einsiedel, S., Thomas, M., Black, J., Wilson, S., McCarthy, D.T., 2020. Passive sampling of viruses for wastewater-based epidemiology: a case-study of SARS-CoV-2 [WWW Document]. URL https://www.researchgate.net/publication/347103410\_Passive\_sampling\_of\_viruses\_for\_wastewater-based\_epidemiology\_a\_case-study\_of\_SARS-CoV-2?channel=doi&linkId=5fd800f392851c13fe892393&showFulltext=true (accessed 1.18.21).

Introduction: Chloroquine (CQ) and hydroxychloroquine (HCQ) are currently used for the prevention/treatment of malaria, and treatment of systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA). Although present data do not show their efficacy to treat COVID-19, they have been used as potential treatments for COVID-19. Given that pregnant women are excluded from randomized controlled trials, and present evidence are inconsistent and inconclusive, we aimed to investigate the safety of CQ or HCQ use in a large pregnancy cohort using real-world evidence.Methods: Using Quebec Pregnancy Cohort, we identified women who delivered a singleton liveborn, 1998–2015, (n = 233,748). The exposure time window for analyses on prematurity and low birth weight (LBW) was the second/third trimesters; was any time during pregnancy; only first trimester exposure was considered for analyses on major congenital malformations (MCM). The risk of prematurity, LBW, and MCM (overall and organ-specific) were quantified using generalized estimation equations.Results: We identified 288 pregnancies (0.12%) exposed to CQ (183, 63.5%) or HCQ (105, 36.5%) that resulted in liveborn singletons; CQ/HCQ was used for RA (17.4%), SLE (16.3%) or malaria (0.7%). CQ/HCQ was used for 71.8 days on average [standard-deviation (SD) 70.5], at a dose of 204.3 mg/d (SD, 155.6). We did not observe any increased risk related to CQ/HCQ exposure for prematurity (adjusted odds ratio [aOR] 1.39, 95%CI 0.84–2.30), LBW (aOR 1.11, 95%CI 0.59–2.06), or MCM (aOR 1.01, 95%CI 0.67–1.52).Conclusion: in this large CQ/HCQ exposed pregnancy cohort, we saw no clear increased risk of prematurity, LBW, or MCM, although number of exposed cases remained low.

This dataset includes tweets from provincial and territorial government officials. In cases when a health official does not use Twitter (e.g. Dr. Bonnie Henry), other official accounts for the province or territory have been substituted. The dataset does not include tweets from federal government officials. The tweet IDs were collected using Documenting the Now's Twarc library (https://github.com/DocNow/twarc). The date of the earliest available tweet is different for each handle. The date of the latest available tweet will not be later than the upload date for each file. See the file-level information below. The tweet ids were extracted from the raw JSON files retrieved from Twitter using Twarc. However, Twitter's terms of use do not permit the sharing of the raw JSON files for this dataset. The raw JSON files can be retrieved from Twitter, provided the content is still available, using the 'hydrate' command within Twarc. The researchers retained the source JSON files and may be contacted by other researchers if they wish to access them. The files of tweet ids will be updated over time and this metadata, the files and this readme.txt file will be updated accordingly. Raw JSON files were harvested using Twarc's 'timeline' command. The 'timeline' command retrieves the most recent tweets from the specified handle, to a maximum of approximately 3,300 tweets. The data for each handle was collected approximately weekly, starting in January 2021. In order not to lose earlier tweets, we concatenated the JSON for each new 'timeline' crawl to the earlier crawls and de-duplicated the combined JSON using Twarc's 'deduplicate' command. We then used Twarc's 'dehydrate' command to extract just the tweet ids from the deduplicate JSON file. Finally, we sorted the tweet ids numerically so that they would appear in ascending date order. The basic workflow looks like: twarc timeline --> concatenate JSON files --> deduplicate resulting JSON file --> dehydrate tweet ids --> sort tweet ids. The Twitter handles include: @ArrudaHoracio: Dr. Horacio Arruda, Directeur national de santé publique et SMA en santé publique MSSS Québec. Tweets in this file start on 2013-03-11. @CMOH_Alberta: Dr. Deena Hinshaw, Alberta’s Chief Medical Officer of Health. Tweets in this file start on 2020-03-26. @CMOH_NL: Dr. Janice Fitzgerald, Newfoundland and Labrador's Chief Medical Officer of Health. Tweets in this file start on 2020-04-27. @GOVofNUNAVUT: Government of Nunavut. Tweets in this file start on 2018-08-20. @GlavineLeo: Leo Glavine, MLA Kings West, Nova Scotia, Minister of Health and Wellness, Minister of Seniors. Tweets in this file start on 2017-04-17. @HealthNS: Nova Scotia Health. Tweets in this file start on 2019-05-D8. @Johnrockdoc: John Haggie, Newfoundland and Labrador's Minister, Health & Community Services. Tweets in this file start on 2020-01-19. @IainTRankin: Iain Rankin, Premier of Nova Scotia from 2021-02-23. MLA for Timberlea-Prospect. Tweets in this file start on 2012-08-08. @MLAStefanson: Heather Stefanson, Manitoba's Minister of Health and Seniors Care, MLA for Tuxedo Tweets in this file start on 2012-02-11. @MerrimanPaul: Paul Merriman. Saskatchewan's Minister of Social Services. Tweets in this file start on 2018-11-18. @MinistreMcCann: Danielle McCann. Députée de Sanguinet - Ministre de l'Enseignement supérieur. Tweets in this file start on 2019-03-14. @NBHealth: New Brunswick Department of Health. Tweets in this file start on 2013-02-26. @NWT_CPHO: Kami Kandola, Northwest Territories Chief Public Officer of Health. Tweets in this file start on 2013-10-16. @PFrostOldCrow: Pauline Frost Yukon MLA for Vuntut Gwich'in. Minister of Health and Social Services, Environment and Minister responsible for the Yukon Housing Corporation. Tweets in this file start on 2016-08-05. @SaskHealth: Saskatchewan Health Authority official twitter account. Tweets in this file start on 2020-03-15. @ShephardDorothy: Dorothy Shephard, Minister of Health for New Brunswick. Tweets in this file start on 2016-04-16. @StephenMcNeil: Stephen McNeil, Premier of Nova Scotia from 2013-10-23 to 2021-02-23. MLA for Annapolis. Tweets in this file start on 2017-05-05. @adriandix: Adrian Dix, MLA for Vancouver-Kingsway and BC Minister of Health. Tweets in this file start on 2019-09-20. @celliottability: Christine Elliott, Deputy Premier of Ontario and Minister of Health, MPP for Newmarket-Aurora. Tweets in this file start on 2018-02-24. @epdevilla: Dr. Eileen de Villa, Toronto's Medical Officer of Health. Tweets in this file start on 2013-02-21. @jsjaylward: James Aylward, Minister for Transportation & Infrastructure for PEI. MLA for District 6 Stratford-Keppoch. Tweets in this file start on 2015-03-30. @juliegreenMLA: Julie Green, NWT Minister of Health and Social Services, Minister Responsible for Persons wit... Visit https://dataone.org/datasets/sha256%3A6926de50d5ad28e6d3b4820345ba4dc1b5dd549afa67117940a8819dd53b98cf for complete metadata about this dataset.

Footnotes:1Gender refers to an individual's personal and social identity as a man, woman or non-binary person (a person who is not exclusively a man or a woman). Gender includes the following concepts: gender identity, which refers to the gender that a person feels internally and individually; gender expression, which refers to the way a person presents their gender, regardless of their gender identity, through body language, aesthetic choices or accessories (e.g., clothes, hairstyle and makeup), which may have traditionally been associated with a specific gender. A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport or driver's licence. A person's gender may change over time. Some people may not identify with a specific gender.2Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses provided. In these cases, individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol.3Age' refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well-defined reference date).4This category includes men and boys, as well as some non-binary persons.5The median income of a specified group is the amount that divides the income distribution of that group into two halves, i.e., the incomes of half of the units in that group are below the median, while those of the other half are above the median. Median incomes of individuals are calculated for those with income (positive or negative).6Average income of a specified group is calculated by dividing the aggregate income of that group by the number of units in that group. Average incomes are calculated for those with income (positive or negative).7Total income refers to the sum of certain incomes (in cash and, in some circumstances, in kind) of the statistical unit during a specified reference period. The components used to calculate total income vary between: – Statistical units of social statistical programs such as persons, private households, census families and economic families; – Statistical units of business statistical programs such as enterprises, companies, establishments and locations; and – Statistical units of farm statistical programs such as farm operator and farm family. In the context of persons, total income refers to receipts from certain sources, before income taxes and deductions, during a specified reference period. In the context of census families, total income refers to receipts from certain sources of all of its family members, before income taxes and deductions, during a specified reference period. In the context of economic families, total income refers to receipts from certain sources of all of its family members, before income taxes and deductions, during a specified reference period. In the context of households, total income refers to receipts from certain sources of all household members, before income taxes and deductions, during a specified reference period. The monetary receipts included are those that tend to be of a regular and recurring nature. Receipts that are included as income are: * employment income from wages, salaries, tips, commissions and net income from self-employment (for both unincorporated farm and non-farm activities); * income from investment sources, such as dividends and interest on bonds, accounts, guaranteed investment certificates (GICs) and mutual funds; * income from employer and personal pension sources, such as private pensions and payments from annuities and registered retirement income funds (RRIFs); * other regular cash income, such as child support payments received, spousal support payments (alimony) received and scholarships; * income from government sources, such as social assistance, child benefits, Employment Insurance benefits, Old Age Security benefits, COVID-19 benefits and Canada Pension Plan and Québec Pension Plan benefits and disability income. Receipts excluded from this income definition are: * one-time receipts, such as lottery winnings, gambling winnings, cash inheritances, lump-sum insurance settlements and tax-free savings account (TFSA) or registered retirement savings plan (RRSP) withdrawals; * capital gains because they are not by their nature regular and recurring. It is further assumed that they are more relevant to the concept of wealth than the concept of income; * employers' contributions to registered pension plans, Canada Pension Plan, Québec Pension Plan and Employment Insurance; * voluntary inter-household transfers, imputed rent, goods and services produced for barter and goods produced for own consumption.8The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.9The sum of employment income (wages, salaries and commissions, net self-employment income from farm or non-farm unincorporated business and/or professional practice), investment income, private retirement income (retirement pensions, superannuation and annuities, including those from registered retirement savings plans [RRSPs] and registered retirement income funds [RRIFs]) and other money income from market sources during the reference period. It is equivalent to total income minus government transfers. It is also referred to as income before transfers and taxes.10The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.11All income received as wages, salaries and commissions from paid employment and net self-employment income from farm or non-farm unincorporated business and/or professional practice during the reference period.12The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.13Gross wages and salaries before deductions for such items as income taxes, pension plan contributions and employment insurance premiums during the reference period. While other employee remuneration such as security options benefits, board and lodging and other taxable allowances and benefits are included in this source, employer's contributions to pension plans and employment insurance plans are excluded. Other receipts included in this source are military pay and allowances, tips, commissions and cash bonuses associated with paid employment, benefits from wage-loss replacement plans or income-maintenance insurance plans, supplementary unemployment benefits from an employer or union, research grants, royalties from a work or invention with no associated expenses and all types of casual earnings during the reference period.14The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.15Net income (gross receipts minus cost of operation and capital cost allowance) received during the reference period from self-employment activities, either on own account or in partnership. In the case of partnerships, only the person's share of income is included. Net partnership income of a limited or non-active partner is excluded. It includes farming income, fishing income and income from unincorporated business or professional practice. Commission income for a self-employed commission salesperson and royalties from a work or invention with expenses associated are also included in this source.16The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.17All cash benefits received from federal, provincial, territorial or municipal governments during the reference period. It includes: * Old Age Security pension, Guaranteed Income Supplement, Allowance or Allowance for the Survivor; * retirement, disability and survivor benefits from Canada Pension Plan and Québec Pension Plan; * benefits from Employment Insurance and Québec parental insurance plan; * child benefits from federal and provincial programs; * social assistance benefits; * workers' compensation benefits; * Canada workers benefit (CWB); * Goods and services tax credit and harmonized sales tax credit; * other income from government sources. For the 2021 Census, this includes various benefits from new and existing federal, provincial and territorial government income programs intended to provide financial support to individuals affected by the COVID-19 pandemic and the public health measures implemented to minimize the spread of the virus.18The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.19Refers to the sum of payments received from COVID-19 - Emergency and recovery benefits and Employment Insurance (EI) benefits.20The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars. In 2019, earning replacement benefits is equal to Employment Insurance (EI) benefits.21All Employment Insurance (EI) benefits received during the reference period, before income tax deductions. It includes benefits for unemployment, sickness, maternity, paternity, adoption, compassionate