These datasets explore disparities in COVID-19 mortality observed in the US and Canada between January 2020 and early March 2021. Table 1 provides counts of deaths, hospitalizations, ICU admissions, and cases, by age, for Ontario, Canada (Canada's most populous province).

Table 2 estimates deaths averted by Canada's response to the COVID-19 pandemic, relative to that in the United States, by "Canada-standardizing" the US epidemic (i.e., by applying US age-specific mortality to Canadian populations, in order to estimate the deaths that would have occurred in a Canadian pandemic with the same rates of death as have been observed in the US). Observed Canadian deaths are compared to "expected" deaths with a US-like response in order to estimate both deaths averted and SMR (Table 2).

As Canadian age groups for purposes of death reporting are slightly different from those used in the US (e.g., 0-17 in the US vs. 0-19 in Canada), we reallocate Canadian deaths based on proportions of deaths occurring in 2-year age categories in Ontario (Table 1).

Ontario age-specific case-fatality is used to inflate the deaths averted, in order to estimate cases averted. Ontario age-specific hospitalization and ICU risk (again derived from Table 1) are used to estimate hospitalizations and ICU admissions averted (Table 2).

As of August 9, 2022, a new dataset has been added which applies the methodology described above to compare deaths in Canada to those in the United Kingdom, France, and Australia. Estimates of QALY loss, and healthcare costs averted, have also been added. Uncertainty bounds are estimated either as parametric confidence intervals, or as upper and lower bound 95% credible intervals through simulation (implemented using the random draw funding in Microsoft Excel).

Errors in confidence intervals for QALY losses in France and Australia corrected February 28, 2023.

The whole files will be uploaded soon for public research usage.

The related publication: Alzamzami, Fatimah, and Abdulmotaleb El Saddik. "Monitoring cyber SentiHate social behavior during COVID-19 pandemic in North America." IEEE Access 9 (2021): 91184-91208. - V2

Context

Each workbook contains daily COVID-19 stats by each country affected. Additional sheets have also been added for more specific breakdown by different locations within Australia, Canada, China, and USA. Worked with BNO News to put this together. Additional credits include: Michael Van Poppel and Carlos Robles. Github updated every 24 hrs can be found here: https://github.com/jamesvalles/CORONAVIUS-COVID-19-DAILYSTATS

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This dashboard created by Operations Dashboard contains the most up-to-date coronavirus COVID-19 cases and latest trend plot. It covers China, the US, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals). Data sources are WHO, US CDC, China NHC, ECDC, and DXY. The China data is automatically updating at least once per hour, and non China data is updating manually. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This service is supported by Esri Living Atlas team and JHU Data Services.

[!NOTE] Dataset origin: https://live.european-language-grid.eu/catalogue/corpus/21332

  Description

Multilingual (EN, FR, DE, ES, EL, IT, PL, PT, RO, KO, RU, ZH, UK, VI, TA, TL) COVID-19-related corpus acquired from the website (https://www.canada.ca/) of the Government of Canada (17th July 2020). It contains 77606 TUs in total.

  Citation

COVID-19 Government of Canada dataset v2. Multilingual (EN, FR, DE, ES, EL, IT, PL, PT, RO, KO, RU, ZH, UK, VI, TA, TL) (2020, August… See the full description on the dataset page: https://huggingface.co/datasets/FrancophonIA/COVID-19_Canada_Government.

Additional File 3. Provides data to support the results pertaining to the percentage change analyses reported in the main text of the manuscript

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. 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 Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. 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. 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. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

The dataset comprises of 10 JSON files, each containing geographic metadata and a sentiment score collected from tweets between March 20, 2020 and December 1, 2020 pertaining to the COVID-19 global pandemic for ten of the most populous cities in the United States and Canada.

Four datasets are presented here. The original dataset is a collection of the COVID-19 data maintained by Our World in Data. It includes data on confirmed cases, and deaths, as well as other variables of potential interest for ten countries such as Australia, Brazil, Canada, China, Denmark, France, Israel, Italy, the United Kingdom, and the United States. The original dataset includes the data from the date of 31st December in 2019 to 31st May in 2020 with a total of 1.530 instances and 19 features. This dataset is collected from a variety of sources (the European Centre for Disease Prevention and Control, United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). After the original dataset is pre-processed by cleaning and removing some data including unnecessary and blank. Then, all strings are converted numeric values, and some new features such as continent, hemisphere, year, month, and day are added by extracting the original features. After that, the processed original dataset is organized for prediction of the number of new cases of COVID-19 for 1 day, 3 days, and 10 days ago and three datasets (Dataset-1, 2, 3) are created for that.

This Project Tycho dataset includes a CSV file with COVID-19 data reported in CANADA: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

**Description **

COVID-19 is something we all are aware of by now, it has affected almost each and everything humans have had connection with . With the rise in COVID cases worldwide in early 2020, a lot of movement was seen throughout the world, people were sent back to their native countries or places , as a result places such as AIrports, Ports, Stations became highly populated during that period . As a result , the density of traffic in such places (Airports etc.) increased a lot , this dataset gives us the density of traffic in four international airports during the march-2020 period .

People infected with COVID-19 can shed the virus through their stool, even if they don't have any symptoms. Testing a community's sewage (wastewater) can tell us if COVID-19 is increasing or decreasing in that community. Our scientists have developed a pan-Canadian wastewater network to monitor the spread of COVID-19 in Canada. This is in collaboration with provincial, territorial and municipal governments and academia across Canada. Some communities and local health authorities are collecting wastewater samples for analysis by Canada's National Microbiology Laboratory. Analysis helps detect the virus that causes COVID-19 and variants.

Context

These datasets are from Our World in Data. Their complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. It is updated daily and includes data on confirmed cases, deaths, hospitalizations, testing, and vaccinations as well as other variables of potential interest.

Content

Confirmed cases and deaths:

our data comes from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). We discuss how and when JHU collects and publishes this data. The cases & deaths dataset is updated daily. Note: the number of cases or deaths reported by any institution—including JHU, the WHO, the ECDC, and others—on a given day does not necessarily represent the actual number on that date. This is because of the long reporting chain that exists between a new case/death and its inclusion in statistics. This also means that negative values in cases and deaths can sometimes appear when a country corrects historical data because it had previously overestimated the number of cases/deaths. Alternatively, large changes can sometimes (although rarely) be made to a country's entire time series if JHU decides (and has access to the necessary data) to correct values retrospectively.

Hospitalizations and intensive care unit (ICU) admissions:

our data comes from the European Centre for Disease Prevention and Control (ECDC) for a select number of European countries; the government of the United Kingdom; the Department of Health & Human Services for the United States; the COVID-19 Tracker for Canada. Unfortunately, we are unable to provide data on hospitalizations for other countries: there is currently no global, aggregated database on COVID-19 hospitalization, and our team at Our World in Data does not have the capacity to build such a dataset.

Testing for COVID-19:

this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. The testing dataset is updated around twice a week.

Acknowledgements

Our World in Data GitHub repository for covid-19.

Inspiration

All we love data, cause we love to go inside it and discover the truth that's the main inspiration I have.

Canada's response to the novel coronavirus (COVID-19) pandemic has been steadfast—keeping up with new scientific evidence and discoveries which allows us to adapt public health measures to prevent the spread of COVID-19, and providing guidance to health care workers so they have the appropriate tools they need to treat patients. Yet, there is still more to learn about COVID-19.

Fully vaccinated travellers entering Canada during COVID-19.The border changes for August 9. - American citizens and permanent residents of the United States, who currently reside in the U.S. and who qualify as fully vaccinated travellers, will be able to enter Canada for discretionary travel starting August 9.

This is the data for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).Data SourcesWorld Health Organization (WHO): https://www.who.int/ DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia. BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html Macau Government: https://www.ssm.gov.mo/portal/ Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-casesMinistry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

Canada's response to the novel coronavirus (COVID-19) pandemic has been steadfast—keeping up with new scientific evidence and discoveries which allows us to adapt public health measures to prevent the spread of COVID-19, and providing guidance to health care workers so they have the appropriate tools they need to treat patients. Yet, there is still more to learn about COVID-19.

During the peak of the coronavirus (COVID-19) crisis (March-April 2020) when many countries worldwide introduced lockdown measures, e-commerce share in total retail sales saw proportions that were not seen before. In the United Kingdom, where an already mature e-commerce market exists, e-commerce share saw as high as **** percent, before stabilizing in the subsequent periods. In the most current period (as of January 31, 2021), United Kingdom, United States and Canada were the leading countries where e-commerce had a higher share as a proportion of total retail, at **, **, and ** percent, respectively.

Data split and prediction.

Since the start of the COVID-19 pandemic the Centre for Social Data Integration and Development (CSDID) team, in conjunction with various partners, has conducted 8 crowdsource surveys targeting the general population, parents, students and persons living with disabilities. We have also conducted 6 iterations of the Canadian Perspectives Series, a web panel experiment and have been diligently producing PUMFs for all these projects. Kathleen Fowler and Melanie Kowalski from CSDID will walk us through the highlights of the COVID-19 data projects focusing on the methodology of collection tools used, results and dissemination products produced from this initiative.