https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario.
Effective April 13, 2023, this dataset will be discontinued. The public can continue to access the data within this dataset in the following locations updated weekly on the Ontario Data Catalogue:
For information on Long-Term Care Home COVID-19 Data, please visit: Long-Term Care Home COVID-19 Data.
Data includes:
This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.
**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool **
The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the columns “Deaths”, “Deaths_Data_Cleaning” and “newly_reported_deaths” starting with data for March 11, 2022. A new column has been added to the file “Deaths_New_Methodology” which represents the methodological change.
The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1, 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred.
On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. A small number of COVID deaths (less than 20) do not have recorded death date and will be excluded from this file.
CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario.
Data includes:
This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.
This data is no longer available on this page. Information about COVID-19, and other respiratory viruses, is available through Public Health Ontario’s “Ontario Respiratory Virus Tool".
On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. This impacts data captured in the column ‘Outcome1’.
Due to changes in data availability, the following variables will be removed from this file, effective Thursday April 13, 2023: ‘Case_AcquisitionInfo’, ‘Outbreak_Related’. Also due to changes in data availability, the variable ‘Outcome1’ will be equal to ‘Fatal’ (deaths due to COVID-19) or blank (all other cases)
The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the column ‘‘Outcome1’ starting with data posted to the catalogue on March 11, 2022.
CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) outbreaks in Ontario. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak Data includes: * Summary of cases associated with outbreaks, by outbreak setting and date * Summary of ongoing outbreaks by outbreak setting * Summary of ongoing outbreaks by Public Health Unit (PHU) As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm Effective March 25, 2022: Due to changes in testing, it is no longer possible to accurately track the total number of cases of COVID-19 associated with outbreaks in education, recreational, workplace, and unknown/other settings. This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.
As of April 15, 2023, there had been over 4.65 million confirmed cases of COVID-19 in Canada. As of this date, the coronavirus had been confirmed in every province and territory, with the province of Ontario having the highest number of confirmed cases.
COVID-19 vaccinations in Canada There have now been seven COVID-19 vaccines approved for use in Canada, the most widely distributed of which is manufactured by Pfizer and BioNTech. Around 63 million doses of the Pfizer/BioNTech vaccine have been distributed across Canada. As of January 1, 2023, around 83 percent of the population in Canada had received at least one COVID-19 vaccination dose.
This dataset compiles daily snapshots of reported data on 2019 Novel Coronavirus (COVID-19) testing of inmates in Ontario's Provincial Correctional Institutions. ## Data includes: * reporting date * region * tests completed * test outcomes Staff data is not included. This dataset is subject to change. Please review the technical notes for information on variables, methodology, caveats, and other considerations. *Effective January 17 2022, the ministry is no longer reporting testing data (including number of tests completed and test outcomes). For the latest COVID-19 data, please visit the Public Health Ontario Data Tool. ### Related dataset(s) * Status of COVID-19 cases in Ontario’s Provincial Correctional Institutions * Ontario’s Provincial Correctional Institution locations
https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0
Effective June 7th, 2024, this dataset will no longer be updated.This file contains data for the last 6 weeks on: Weekly counts and rates of Ottawa residents with laboratory-confirmed COVID-19 by episode date (i.e. the earliest of symptom onset, testing or reported date) and age. Weekly counts and rates of Ottawa residents with laboratory-confirmed COVID-19 by reported date. Data are from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM).
Accuracy: Points of consideration for interpretation of the data: Data are entered into and extracted by Ottawa Public Health from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM). The COD is a dynamic disease reporting system that allows for ongoing updates; data represent a snapshot at the time of extraction and may differ from previous or subsequent reports.As the cases are investigated and more information is available, the dates are updated. A person’s exposure may have occurred up to 14 days prior to onset of symptoms. Symptomatic cases occurring in approximately the last 14 days are likely under-reported due to the time for individuals to seek medical assessment, availability of testing, and receipt of test results.Confirmed cases are those with a confirmed COVID-19 laboratory result as per the Ministry of Health Public health management of cases and contacts of COVID-19 in Ontario. March 25, 2020 version 6.0.Counts will be subject to varying degrees of underreporting due to a variety of factors, such as disease awareness and medical care seeking behaviours, which may depend on severity of illness, clinical practice, changes in laboratory testing, and reporting behaviours.Surveillance testing for COVID-19 began in long term care facilities on April 25, 2020. Update Frequency: Tuesdays and Fridays
Attributes: Data fields: Week – Date of the first day of the episode week (i.e. the week during which the case first developed symptom, got tested or was reported to OPH – whichever was earliest). Date in format YYYY-MM-DD H:MM. Weekly Rate of COVID-19 by 20-year Age Groupings (per 100,000 pop) and Episode Date – The number of Ottawa residents with confirmed COVID-19 within an age group (e.g. 0-9 years) divided by the total Ottawa population for that age group. This fraction is then multiplied by 100,000 to get a rate of COVID-19 per 100,000 population for that age group.Weekly Total of Cases by Episode Date - number of Ottawa residents with laboratory-confirmed COVID-19 by episode date.Weekly Total of Cases by Reported Date – number of Ottawa residents with laboratory-confirmed COVID-19 by reported date.Weekly Rate of COVID-19 (per 100,000 pop) by Reported Date – number of Ottawa residents with laboratory-confirmed COVID-19 by reported date divided by the total Ottawa population and multiplied by 100,000. Contact: OPH Epidemiology Team | Epidemiology & Evidence, Ottawa Public Health
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.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This dataset compiles daily snapshots of reported data on 2019 Novel Coronavirus (COVID-19) testing of inmates in Ontario's Provincial Correctional Institutions. ## Data includes: * reporting date * region * tests completed * test outcomes Staff data is not included. This dataset is subject to change. Please review the technical notes for information on variables, methodology, caveats, and other considerations. *Effective January 17 2022, the ministry is no longer reporting testing data (including number of tests completed and test outcomes). For the latest COVID-19 data, please visit the Public Health Ontario Data Tool. ### Related dataset(s) * Status of COVID-19 cases in Ontario’s Provincial Correctional Institutions * Ontario’s Provincial Correctional Institution locations
This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Data includes: * date * OH region * current hospitalizations with COVID-19 * current patients in Intensive Care Units (ICUs) due to COVID-related critical Illness * current patients in Intensive Care Units (ICUs) testing positive for COVID * current patients in Intensive Care Units (ICUs) no longer testing positive for COVID * current patients in Intensive Care Units (ICUs) on ventilators due to COVID-related critical illness * current patients in Intensive Care Units (ICUs) on ventilators testing positive for COVID * current patients in Intensive Care Units (ICUs) on ventilators no longer testing positive for COVID **Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool ** ##Additional notes Data for the period of October 24, 2023 to March 24, 2024 excludes hospitals in the West region who were experiencing data availability issues. Daily adult, pediatric, and neonatal patient ICU census data were impacted by technical issues between September 9 and October 20, 2023. As a result, when public reporting resumes on November 16, 2023, historical ICU data for this time period will be excluded. As of August 3, 2023, the data in this file has been updated to reflect that there are now six Ontario Health (OH) regions. This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This is the Zenodo archive for the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada" (Mucaki EJ, Shirley BC and Rogan PK. F1000Research 2021, 10:1312, DOI: 10.12688/f1000research.75891.1). This study aimed to produce community-level geo-spatial mapping of patterns and clusters of symptoms, and of confirmed COVID-19 cases, in near real-time in order to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. This archive will contain data and image files from this study, which were too numerous to be included in the manuscript for this study. It also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript and other software developed (cluster, outlier, streak identification and pairing)..
We also provide a guide which provides a general description of the contents of the four sections in this archive (Documentation_for_Sections_of_Zenodo_Archive.docx). If you have any intent to utilize the data provided in Section 3, we greatly advise you to review this document as it describes the output of all geostatistical analyses performed in this study in detail.
Data Files:
Section 1. "Section_1.Tables_S1_S7.Figures_S1_S11.zip"
This section contains all additional tables and figures described in the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada". Additional tables S1 to S7 are presented in an Excel document. These 7 tables provide summary statistics of various geostatistical tests described in the study (“Section 1 – Tables S1-S4”) and lists all identified single and paired high-case cluster streaks (“Section 1 – Tables S5-S7”). This section also contains 11 additional figures referred to in the manuscript (“Section 1 – Figures S1-S11”) both individually and within a Word document which describes them.
Section 2. "Section_2.Localized_Hotspot_Lists.zip"
All localized hotspots (identified through kriging analysis) were catalogued for each municipality evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex). These files indicate the FSA in which the hotspot was identified, the date in which it was identified (utilizing 3-day case data at the postal code level), the amount of cases which occurred within the FSA within these 3 dates, the range of cases interpolated by kriging analysis (between 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-50, >50), and whether or not the FSA was deemed a hotspot by Gi* relative to the rest of Ontario on any of the three dates evaluated. Please see Section 4 for map images of these localized hotspots.
Section 3. "Section_3.All-Data_Files.Kriging_GiStar_Local_and_GlobalMorans.2020_2021"
Section 3 – All output files from the geostatistical tests performed in this study are provided in this section. This includes the output from Ontario-wide FSA-level Gi* and Cluster and Outlier analyses, and PC-level Cluster and Outlier, Spatial Autocorrelation, and kriging analysis of 6 municipal regions. It also includes kriging analysis of 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan). This section also provides data files from our analyses of stratified case data (by age, gender, and at-risk condition). All coordinates presented in these data files are given in “PCS_Lambert_Conformal_Conic” format. Case values between 1-5 were masked (appear as “NA”).
Section 4. "Section_4.All_Map_Images_of_Geostat_Analyses.zip"
Sets of image files which map the results of our geostatistical analyses onto a map of Ontario or within the municipalities evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex) are provided. This includes: Kriging analysis (PC-level), Local Moran's I cluster and outlier analysis (FSA and PC-level), normal and space-time Gi* analysis, and all images for all analyses performed on stratified data (by age, gender and at-risk condition). Kriging contour maps are also included for 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan).
Software:
This Zenodo archive also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript. This geostatistical toolbox was developed by CytoGnomix Inc., London ON, Canada and is distributed freely under the terms of the GNU General Public License v3.0. It can be easily modified to accommodate other Canadian provinces and, with some additional effort, other countries.
This distribution of the Geostatistical Epidemiology Toolbox does not include postal code (PC) boundary files (which are required for some of the tools included in the toolbox). The PC boundary shapefiles used to test the toolbox were obtained from DMTI (https://www.dmtispatial.com/canmap/) through the Scholar's Geoportal at the University of Western Ontario (http://geo2.scholarsportal.info/). The distribution of these files (through sharing, sale, donation, transfer, or exchange) is strictly prohibited. However, any equivalent PC boundary shape file should suffice, provided it contains polygon boundaries representing postal code regions (see guide for more details).
Software File 1. "Software.GeostatisticalEpidemiologyToolbox.zip"
The Geostatistical Epidemiology Toolbox is a set of custom Python-based geoprocessing tools which function as any built-in tool in the ArcGIS system. This toolbox implements data preprocessing, geostatistical analysis and post-processing software developed to evaluate the distribution and progression of COVID-19 cases in Canada. The purpose of developing this toolbox is to allow external users without programming knowledge to utilize the software scripts which generated our analyses and was intended to be used to evaluate Canadian datasets. While the toolbox was developed for evaluating the distribution of COVID-19, it could be utilized for other purposes.
The toolbox was developed to evaluate statistically significant distributions of COVID-19 case data at Canadian Forward Sortation Area (FSA) and Postal Code-level in the province of Ontario utilizing geostatistical tools available through the ArcGIS system. These tools include: 1) Standard Gi* analysis (finds areas where cases are significantly spatially clustered), 2) spacetime based Gi* analysis (finds areas where cases are both spatially and temporally clustered), 3) cluster and outlier analysis (determines if high case regions are an regional outlier or part of a case cluster), 4) spatial autocorrelation (determines the cases in a region are clustered overall) and, 5) Empirical Bayesian Kriging analysis (creates contour maps which define the interpolation of COVID-19 cases in measured and unmeasured areas). Post-processing tools are included that import these all of the preceding results into the ArcGIS system and automatically generate PNG images.
This archive also includes a guide ("UserManual_GeostatisticalEpidemiologyToolbox_CytoGnomix.pdf") which describes in detail how to set up the toolbox, how to format input case data, and how to use each tool (describing both the relevant input parameters and the structure of the resultant output files).
Software File 2: “Software.Additional_Programs_for_Cluster_Outlier_Streak_Idendification_and_Pairing.zip"
In the manuscript associated with this archive, Perl scripts were utilized to evaluate postal code-level Cluster and Outlier analysis to identify significantly, highly clustered postal codes over consecutive periods (i.e., high-case cluster “streaks”). The identified streaks are then paired to those in close proximity, based on the neighbors of each postal code from PC centroid data ("paired streaks"). Multinomial logistic regression models were then derived in the R programming language to measure the correlation between the number of cases reported in each paired streak, the interval of time separating each streak, and the physical distance between the two postal codes. Here, we provide the 3 Perl scripts and the R markdown file which perform these tasks:
“Ontario_City_Closest_Postal_Code_Identification.pl”
Using an input file with postal code coordinates (by centroid), this program identifies the nearest neighbors to all postal codes for a given municipal region (the name of this region is entered on the command line). Postal code centroids were calculated in ArcGIS using the “Calculate Geometry” function against DMTI postal code boundary files (not provided). Input from other sources could be used, however, as long as the input includes a list of coordinates with a unique label associated with a particular municipality.
The output of this program (for the same municipal region being evaluated) is required for the following two Perl
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool ** As of January 26, 2023, the population counts are based on Statistics Canada’s 2021 estimates. The coverage methodology has been revised to calculate age based on the current date and deceased individuals are no longer included. The method used to count daily dose administrations has changed is now based on the date delivered versus the day entered into the data system. Historical data has been updated. Please note that Cases by Vaccination Status data will no longer be published as of June 30, 2022. Please note that case rates by vaccination status and age group data will no longer be published as of July 13, 2022. Please note that Hospitalization by Vaccination Status data will no longer be published as of June 30, 2022. Learn more about COVID-19 vaccines. ##Data includes: * daily and total doses administered * individuals with at least one dose * individuals fully vaccinated * total doses given to fully vaccinated individuals * vaccinations by age * percentage of age group * individuals with at least one dose, by PHU, by age group * individuals fully vaccinated, by PHU, by age group * COVID-19 cases by status: not fully vaccinated, fully vaccinated, vaccinated with booster * individuals in hospital due to COVID-19 (excluding ICU) by status: unvaccinated, partially vaccinated, fully vaccinated * individuals in ICU due to COVID-19 by status: unvaccinated, partially vaccinated, fully vaccinated, unknown * rate of COVID-19 cases per 100,000 by status and age group * rate per 100,000 (7-day average) by status and age group All data reflects totals from 8 p.m. the previous day. This dataset is subject to change. Additional notes * Data entry of vaccination records is still in progress, therefore the dosage data may not be a full representation of all vaccination doses administered in Ontario. * The data does not include dosage data where consent was not provided for vaccination records to be entered into the provincial CoVax system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information into CoVax. ##Hospitalizations and cases by vaccination status Hospitalizations * This is a new data collection and the data quality will continue to improve as hospitals continue to submit data. * In order to understand the vaccination status of patients currently hospitalized, a new data collection process was developed and this may cause discrepancies between other hospitalization numbers being collected using a different data collection process. * Data on patients in ICU are being collected from two different data sources with different extraction times and public reporting cycles. The existing data source (Critical Care Information System, CCIS) does not have vaccination status. * Historical data for hospitalizations by region may change over time as hospitals update previously entered data. * Due to incomplete weekend and holiday reporting, vaccination status data for hospital and ICU admissions is not updated on Sundays, Mondays and the day after holidays * Unvaccinated is defined as not having any dose, or between 0-13 days after administration of the first dose of a COVID-19 vaccine. * Partially vaccinated is defined as 14 days or more after the first dose of a 2-dose series COVID-19 vaccine, or between 0-13 days after administration of the second dose * Fully vaccinated is defined as 14 days or more after receipt of the second dose of a 2-dose series COVID-19 vaccine Cases * The cases by vaccination status may not match the daily COVID-19 case count because records with a missing or invalid health card number cannot be linked.
https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0
Effective June 7th, 2024, this dataset will no longer be updated.This file contains data on:
Cumulative count of Ottawa residents with laboratory-confirmed COVID-19 by episode date (i.e. the earliest of symptom onset, testing or reported date), including active cases and resolved cases.
Cumulative count of Ottawa residents with laboratory-confirmed COVID-19 who died by date of death.
Daily count of Ottawa residents with laboratory-confirmed COVID-19 by reported date and episode date.
Daily count of Ottawa residents with laboratory-confirmed COVID-19 by outbreak association and episode date.
Daily count of Ottawa residents with laboratory-confirmed COVID-19 newly admitted to the hospital, currently in hospital, and currently in the intensive care unit (ICU).
Cumulative rate of confirmed COVID-19 for Ottawa residents by age group and episode date.
Cumulative rate of confirmed COVID-19 for Ottawa residents by gender and episode date.
Daily count of Ottawa residents with laboratory-confirmed COVID-19 by source of infection and episode date.
Data are from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM).
Accuracy: Points of consideration for interpretation of the data:
The percent of cases with no known epidemiological (epi) link, during the current day and previous 13 days, is calculated as the number of cases with no known epi link among all cases. The percent of cases with no known epi link is unstable during time periods with few cases.
Source of infection is based on a case's epidemiologic linkage. If no epidemiologic linkage is identified, source of infection is allocated using a hierarchy of risk factors: related to travel prior to April 1, 2020 > part of an outbreak > close or household contact of a known case > related to travel since April 1, 2020 > unspecified epidemiological link > no known source of infection > no information available.
Data are entered into and extracted by Ottawa Public Health from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM). The CCM is a dynamic disease reporting system that allows for ongoing updates; data represent a snapshot at the time of extraction and may differ from previous or subsequent reports.
As the cases are investigated and more information is available, the dates are updated.
A person’s exposure may have occurred up to 14 days prior to onset of symptoms. Symptomatic cases occurring in approximately the last 14 days are likely under-reported due to the time for individuals to seek medical assessment, availability of testing, and receipt of test results.
Confirmed cases are those with a confirmed COVID-19 laboratory result as per the Ministry of Health Public health management of cases and contacts of COVID-19 in Ontario. March 25, 2020 version 6.0.
Counts will be subject to varying degrees of underreporting due to a variety of factors, such as disease awareness and medical care seeking behaviours, which may depend on severity of illness, clinical practice, changes in laboratory testing, and reporting behaviours.
Data on hospital admissions, ICU admissions and deaths are likely under-reported as these events may occur after the completion of public health follow up of cases. Cases that were admitted to hospital or died after follow-up was completed may not be captured in iPHIS or local health unit reporting tools.
Cases are associated with a specific, isolated community outbreak; an institutional outbreak (e.g. healthcare, childcare, education); or no known outbreak (i.e., sporadic).
The distribution of the source of infection among confirmed cases is impacted by the provincial guidance on testing.
Surveillance testing for COVID-19 began in long term care facilities on April 25, 2020.
Source of infection is allocated using a hierarchy: Related to travel prior to April 1, 2020 > Close contact of a known case or part of a community outbreak or source of infection is an institutional outbreak > Related to travel since April 1, 2020 > No known source of infection > Missing.
The percent of cases with unknown source, during the current day and previous 13 days, is calculated as the number of cases with no known source among cases who source of infection is not an institutional outbreak. Calculated over a 14 day period (i.e. the day of interest and the preceding 13 days). The percent of cases with no known source is unstable during time periods with few cases.
Update Frequency: Wednesdays
Attributes: Data fields:
Data fields:
Date – Date in format YYYY-MM-DD H:MM. The date type varies based on the column of interest and could be:
- Episode date – Earliest of
symptom onset, test or reported date for cases;
- Date of death – The date
the person was reported to have died
- Reported date – Date the
confirmed laboratory results were reported to Ottawa Public Health
- Hospitalization date
Cumulative Cases by Episode Date – cumulative number of Ottawa residents with laboratory-confirmed COVID-19 by episode date. Cumulative Resolved Cases by Episode Date – cumulative number of Ottawa residents with laboratory-confirmed COVID-19 that have not died and are either (1) assessed as ‘recovered’ in The CCM or (2) 14 days past their episode date and not currently hospitalized. Cumulative Active Cases by Episode Date– cumulative number of Ottawa residents with an active COVID-19 infection. Calculated as the total number of Ottawa residents with COVID-19 excluding resolved and deceased cases. Cumulative Deaths by Date of Death - cumulative number of Ottawa residents with laboratory-confirmed COVID-19 who died by date of death. Deaths are included whether or not COVID-19 was determined to be a contributing or underlying cause of death. Daily Cases by Reported Date – number of Ottawa residents with laboratory-confirmed COVID-19 by reported date 7-Day Average of Newly Reported Cases by Reported Date – number of Ottawa residents with laboratory-confirmed COVID-19 by reported date. Calculated over a 7 day period (i.e. the day of interest and the preceding 6 days). Daily Cases by Episode Date - number of Ottawa residents with laboratory-confirmed COVID-19 by episode date. Daily Cases Linked to a Community Outbreak by Episode Date – number of Ottawa residents with laboratory-confirmed COVID-19 associated with a specific isolated community outbreak by episode date. Daily Cases Linked to an Institutional Outbreak – number of Ottawa residents with laboratory-confirmed COVID-19 associated with a COVID-19 outbreak in a healthcare, childcare or educational establishment by case episode date. Healthcare institutions include places such as long-term care homes, retirement homes, hospitals, other healthcare institutions (e.g. group homes, shelters). Daily Cases Not Linked to an Institutional Outbreak (i.e. Sporadic Cases) – number of Ottawa residents with laboratory-confirmed COVID-19 not associated to an outbreak of COVID-19. Cases Newly Admitted to Hospital – Daily number of Ottawa residents with confirmed COVID-19 admitted to hospital. Emergency room visits are not included in the number of hospital admissions. Cases Currently in Hospital – Number of Ottawa residents with confirmed COVID-19 currently in hospital, includes patients in intensive care. Emergency room visits are not included in the number of hospitalizations. Cases Currently in ICU - Number of Ottawa residents with confirmed COVID-19 currently being treated in the intensive care unit (ICU). It is a subset of the count of hospitalized cases. Cumulative Rate of COVID-19 by 10-year Age Groupings (per 100,000 pop) and Episode Date – The number of Ottawa residents with confirmed COVID-19 within an age group (e.g. 0-9 years) divided by the total Ottawa population for that age group. This fraction is then multiplied by 100,000 to get a rate of COVID-19 per 100,000 population for that age group. Cumulative Rate of COVID-19 by Gender (per 100,000 pop) and Episode Date – The number of Ottawa residents with confirmed COVID-19 of a given gender (e.g. female) divided by the total Ottawa population for that gender. This fraction is then multiplied by 100,000 to get a rate of COVID-19 per 100,000 population for that gender. Source of infection is travel by episode date: individuals who are most likely to have acquired their infection during out-of-province travel. Number of cases with missing information on source of infection by episode date: assessment for source of infection was not completed. Number of cases with no known epidemiological link by episode date: individuals who did not travel outside Ontario, are not part of an outbreak, and are not able to identify someone with COVID-19 from whom they might have acquired infection. The assessment for source of infection was completed, but no sources were identified. Source of infection is a close contact by episode date: individuals presumed to have acquired their infection following close contact (e.g. household member, friend, relative) with an individual with confirmed COVID-19. Source of infection is an outbreak by episode date: individuals who are most likely to have acquired their infection as part of a confirmed COVID-19 outbreak. Source of Infection is Unknown by Episode Date: Ottawa residents with confirmed COVID-19 who did not travel outside
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset include two .csv files containing the integrated dataset used by the COVID-19 School Dashboard website to report and maps confirmed school-related cases of COVID-19 in publicly funded elementary and secondary schools in Ontario, Canada, and connects this to data on school social background characteristics. One csv file reports cases from 2020-09-10 to 2021-04-14 (2020 school year) while the other csv file reports cases from 2021-09-13 to 2021-12-22 (2021 school year). Two accompanying .doc files are included to describe the variables in the .csv files.
As of May 2, 2023, of 34,206 COVID-19 cases deceased in Canada, around 4,058 were aged 60 to 69 years. This statistic shows the number of COVID-19 deaths in Canada as of May 2, 2023, by age.
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Data and Stata code for recreation of "Impact of Adjustment for Differential Testing by Age and Sex on Apparent Epidemiology of SARS-CoV-2 Infection in Ontario, Canada". For questions about analysis please contact me directly at david.fisman@gmail.com or david.fisman@utoronto.ca.Paper abstract: Surveillance of communicable diseases typically relies on case counts for estimates of risk, and counts can be strongly influenced by testing rates. In the Canadian province of Ontario, testing rates varied markedly by age, sex, geography and time over the course of the SARS-CoV-2 pandemic. We applied a standardization-based approach to test-adjustment to better understand pandemic dynamics from 2020 to 2022, and to better understand when test-adjustment is necessary for accurate estimation of risk. SARS-CoV-2 case counts by age, sex, public health unit and week were obtained from Ontario’s Case and Contact Management system (CCM), which includes all SARS-CoV-2 cases from March 2020 to August 2022. Complete data on testing volumes was obtained from the Ontario Laboratory Information System (OLIS). Case counts were adjusted for under-testing using a previously published standardization-based approach that estimates case numbers that would have been expected if the entire population was tested at the same rate as most-tested age and sex groups. Logistic regression was used to identify threshold testing rates beyond which test-adjustment was unnecessary. Testing rates varied markedly by age, sex, public health unit and pandemic wave. After adjustment for under-testing, overall case counts increased threefold. Adjusted epidemic curves suggested, in contrast to reported case counts, that the first two pandemic waves were equivalent in size, and that there were three distinct pandemic waves in 2022, due to the emergence of Omicron variants. Under-reporting was greatest in children and young males, and varied significantly across public health units, with variation explained partly by testing rates and prevalence of multigenerational households. Test adjustment resulted in little change in the epidemic curve during pandemic waves when testing rates were highest; we found that test-adjustment did not increase case counts once weekly per capita testing rates exceeded 6.3%. We conclude that standardization-based adjustment for differential testing by age and sex, and for dynamic changes in testing over time, results in a different picture of infection risk during the SARS-CoV-2 pandemic in Ontario; test-adjusted epidemic curves are concordant with observed patterns of mortality during the pandemic and have face validity. This methodology offers an alternative to sero-epidemiology for identification of true burden of infection when reinfection, sero-reversion, and non-specificity of serological assays make sero-epidemiology challenging.Update, December 15, 2023This data source is being updated in relation to work in progress showing the importance of test-adjusting for accurate estimation of the impacts of community masking mandates, as were introduced in Ontario in summer 2020 (see https://www.medrxiv.org/content/10.1101/2023.07.26.23293155v1). New files include a dataset that can be used to run updated analyses, Stata macros that create test-adjusted case counts by public health unit, age group, gender and week, and a spreadsheet that shows the estimated impact of mask mandates as compared to a counterfactual where they were not introduced.
https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0
Daily number of Ottawa residents tested for COVID-19 and the percentage of residents tested with laboratory-confirmed COVID-19. Data are based on information extracted from the Ontario Laboratories Information System (OLIS) on Monday, Wednesday, and Friday.
Accuracy: Points of consideration for interpretation of the data: Not all labs report to OLIS and only patients with health card numbers are included in the OLIS dataset.Once an individual is confirmed positive, subsequent tests for that individual are excluded from the daily totals.Duplicate tests are excluded from the total number of positive tests, including those that arose from multiple tests of cure. Results for patients who placed an OLIS consent block (~50 records province-wide) are excluded.Staff working in long-term care homes are not captured in OLIS.City assignment in OLIS is based on the patient's health card address. Patients living in long-term care homes may not have the correct address associated with their health cards; therefore, not all tests in long-term care homes may be captured.Confirmed cases are those with a confirmed COVID-19 laboratory result as per the Ministry of Health Public health management of cases and contacts of COVID-19 in Ontario. March 25, 2020 version 6.0.The province has had to limit testing to priority groups in the early stages of the pandemic. Since only a small fraction of all the persons who were infected with the COVID-19 virus were tested, the number of reported confirmed community cases underestimates the actual number of infections. Information on overall infection rates in Canada will not be available until large studies on COVID-19 antibody presence in blood serum are conducted. Based on available information, the actual number of infections may lie from 5 to 30 times or more than the reported number of cases (1).Surveillance testing for COVID-19 began in long term care facilities on April 25, 2020. Reference: Richterich P. Severe underestimation of COVID-19 case numbers: Effect of epidemic growth rate and test restrictions. medRxiv. April 2020: 2020.04.13. doi.org/10.1101/2020.04.13.20064220 Update Frequency: Tuesdays and Fridays Attributes: Data fields: Date – date of the test (YYYY-MM-DD).Number of tests – number of Ottawa residents tested for COVID-19Daily % Positivity – number of Ottawa residents tested on that day that received a positive test result for COVID-19 divided by the total number of Ottawa residents tested on that dayNumber of tests in LTCH– number of Ottawa residents in long-term care homes who were tested for COVID-19LTCH Daily % Positivity – number of Ottawa residents in long-term care homes tested on that day that received a positive test result for COVID-19 divided by the total number of Ottawa residents in long-term care homes tested on that day Contact: OPH Epidemiology Team | Epidemiology & Evidence, Ottawa Public Health
https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0
Summary of COVID-19 community outbreaks in Ottawa based on the most up to date information available in the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM).
Accuracy: Points of consideration for interpretation of the data:
• The data was extracted by Ottawa Public Health from the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM). The CCM is a dynamic disease reporting system that allows for ongoing updates to data previously entered. The data extracted from The CCM represent a snapshot at the time of extraction and may differ in previous or subsequent reports.
• Data are for confirmed outbreaks and the number Ottawa residents with laboratory confirmed COVID-19 associated to each outbreak is provided. Please note, individuals may be linked to multiple outbreaks.
• All the outbreaks reflect the outbreak definitions at the time they were declared open:
o Community: From April 1st 2020, 2 or more laboratory-confirmed COVID-19 cases with an epidemiological link in the setting within a 14-day period where at least 2 cases could have reasonably acquired their infection in the setting. Examples of epidemiological links in community settings include community organization (e.g. attended same social or volunteer club meeting), religious/spiritual organization (e.g. attended same service), residential (e.g. multi-unit dwelling - from different households in the same apartment building but rode the elevator together, used a common room at the same time), social event (e.g. attended same one-time party, wedding or funeral together), sports and recreation (e.g. attended same sports team practice or fitness class), or workplace (e.g. same work area, same shift).
• Public health is only required to formally declare outbreaks for workplace community settings but has chosen to declare outbreaks in other community settings when there is more risk to the public, there are challenges in contact tracing and/or capacity allows. Since October 2020, OPH has systematically reported outbreaks in other community settings. Please see the definitions for community outbreaks posted on the OPH COVID-19 Dashboard web page for more information.
Attributes: Data fields:
• Outbreak ID
• Setting - text
• Sub-category - text
• Start Date - outbreak start date
• End Date – outbreak end date
• Cases – total number of people with confirmed COVID-19 linked to the outbreak
• Deaths – total number of people with confirmed COVID-19 linked to the outbreak who died
Update Frequency: Daily
Contact: OPH Epidemiology Team
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Through 2020, the Government of Ontario has been posting near-daily COVID19 status reports at https://www.ontario.ca/page/2019-novel-coronavirus. These reports are usually updated at 10:30am and 5:30am ET. Unfortunately, the reports as presented are of-the-moment snapshots and provide no historic context for time-based analysis. Using the Internet Archive's Wayback Machine (https://web.archive.org/), this data has been indexed for improved time-based analysis by researchers, journalists, and the public. Reporting begins February 15 and continues to March 19; gaps exist due to the intermittent nature of WBM scraping, especially in February and Early March. Summary versioning changes are included in the Notes field below and in the Version tab of the record. A complete change log is included in the spreadsheet.
This dataset provides Canadians and researchers with preliminary data on the confirmed cases of coronavirus (COVID-19) in Canada. Given the rapidly-evolving nature of this situation, these data are considered preliminary. The dataset was downloaded from Statistics Canada as a CSV file. Due to the size of the data file, it was imported into SPSS from which 5 CSV files were exported based on the region variable. The regions are Atlantic, Quebec, Ontario and Nunavut, Prairies and Northwest Territories, and British Columbia and Yukon. This dataset is a custom extraction of Preliminary dataset on confirmed cases of COVID-19, Public Health Agency of Canada
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Cet ensemble de données compile les données sur les cas confirmés de nouveau coronavirus 2019 (COVID-19) en Ontario communiquées par les bureaux de santé publique.
Les données comprennent :
Cet ensemble de données pourrait changer. Veuillez consulter rapport quotidien sur l’état des cas en Ontario pour vous renseigner sur les variables, la méthodologie et les considérations techniques.
Ces données ne sont plus disponibles sur cette page. Des informations sur la COVID-19 et d’autres virus respiratoires sont disponibles via l’outil « Ontario Respiratory Virus Tool » de Santé publique Ontario.
Le 30 novembre 2023, le nombre de décès dus à la COVID-19 a été mis à jour afin d’inclure les décès manquants du 15 janvier 2020 au 31 mars 2023. Cela a un impact sur les données saisies dans la colonne « Résultat 1 ».
En raison de changements relatifs à la disponibilité des données, les variables qui suivent seront retirées de ce dossier à compter du jeudi 13 avril 2023 : “Case_AcquisitionInfo”, “Outbreak_Related”. Également en raison de changements relatifs à la disponibilité des données, la variable “Outcome1” équivaudra à “Fatal” (décès causés par la COVID-19) ou à une valeur vide (tous les autres cas).
La méthodologie utilisée pour compter les décès liés à la COVID-19 a changé afin d’exclure les décès non causés par la COVID. Cela a un impact sur les données saisies dans la colonne « Résultat 1 » pour les données affichées dans le catalogue à partir du 11 mars 2022.
Le Système GCC est un système de déclaration des maladies dynamique, qui permet des mises à jour continues des données saisies précédemment. Par conséquent, les renseignements tirés du système représentent un instantané au moment de leur extraction et peuvent être différents de rapports précédents ou ultérieurs. Les bureaux de santé publique nettoient continuellement les données sur la COVID-19, en corrigeant les cas et les décès manquants ou en trop. Ces corrections peuvent entraîner des pics de données, des chiffres négatifs et des totaux actuels différents des nombres de cas et de décès signalés précédemment. Les tendances observées au fil du temps doivent être interprétées avec prudence pour la période la plus récente en raison des délais de déclaration ou de saisie des données. Sauf indication contraire, les données précédemment déclarées peuvent changer à mesure que les bureaux de santé publique mettent les données à jour.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario.
Effective April 13, 2023, this dataset will be discontinued. The public can continue to access the data within this dataset in the following locations updated weekly on the Ontario Data Catalogue:
For information on Long-Term Care Home COVID-19 Data, please visit: Long-Term Care Home COVID-19 Data.
Data includes:
This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.
**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool **
The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the columns “Deaths”, “Deaths_Data_Cleaning” and “newly_reported_deaths” starting with data for March 11, 2022. A new column has been added to the file “Deaths_New_Methodology” which represents the methodological change.
The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1, 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred.
On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. A small number of COVID deaths (less than 20) do not have recorded death date and will be excluded from this file.
CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.