About this dataset

Context

The dataset tabulates the Ontario population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Ontario across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Ontario was 182,457, a 1.08% increase year-by-year from 2022. Previously, in 2022, Ontario population was 180,500, an increase of 1.25% compared to a population of 178,272 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Ontario increased by 23,788. In this period, the peak population was 182,457 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Ontario is shown in this column.
• Year on Year Change: This column displays the change in Ontario population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Ontario Population by Year. You can refer the same here

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

About this dataset

Context

The dataset tabulates the data for the Ontario, OR population pyramid, which represents the Ontario population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Ontario, OR, is 39.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Ontario, OR, is 32.7.
• Total dependency ratio for Ontario, OR is 71.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Ontario, OR is 3.1.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Ontario population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Ontario for the selected age group is shown in the following column.
• Population (Female): The female population in the Ontario for the selected age group is shown in the following column.
• Total Population: The total population of the Ontario for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Ontario Population by Age. You can refer the same here

Annual population projections, from 2024 to 2051. These datasets include population projections by age and gender organized by geography: * Projections for Ontario * Projections for each of the 6 regions * Projections for each of the 49 census divisions * Projections for each of the 34 public health units * Projections for each of the 9 Ministry of Children, Community and Social Services’ Service Delivery Division (SDD) regions For Ontario only, the projected annual components of demographic change are provided for the reference, low- and high-growth scenarios. For all other geographies, only the reference scenario is produced.

Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.

How Are We Protecting Privacy?

Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.

This information is also available on the Ministry of Education's School Information Finder website by individual school.

Descriptions for some of the data types can be found in our glossary.

School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

Annual population projections, from 2024 to 2051. These datasets include population projections by age and gender organized by geography: * Projections for Ontario * Projections for each of the 6 regions * Projections for each of the 49 census divisions * Projections for each of the 34 public health units * Projections for each of the 9 Ministry of Children, Community and Social Services’ Service Delivery Division (SDD) regions For Ontario only, the projected annual components of demographic change are provided for the reference, low- and high-growth scenarios. For all other geographies, only the reference scenario is produced.

About this dataset

Context

The dataset tabulates the Ontario population by age. The dataset can be utilized to understand the age distribution and demographics of Ontario.

Content

The dataset constitues the following three datasets

• Ontario, OR Age Group Population Dataset: A complete breakdown of Ontario age demographics from 0 to 85 years, distributed across 18 age groups
• Ontario, OR Age Cohorts Dataset: Children, Working Adults, and Seniors in Ontario - Population and Percentage Analysis
• Ontario, OR Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

Components of population growth, annual: births, deaths, immigrants, emigrants, returning emigrants, net temporary emigrants, net interprovincial migration, net non-permanent residents, residual deviation.

**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.

About this dataset

Context

The dataset tabulates the population of Ontario by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Ontario across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.61% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Ontario is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Ontario total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Ontario Population by Race & Ethnicity. You can refer the same here

This dataset details the total number of electric vehicles (EVs) in Ontario. This includes both battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Data includes: * Total EVs by Forward Sortation Area (FSA) (the first three characters of the postal code) of the vehicle plate owner’s registered address * Number of BEVs by FSA of the vehicle plate owner’s registered address * Number of PHEVs by FSA of the vehicle plate owner’s registered address Note: Datasets from July 1, 2024 onward include all electric vehicles with licence plates that have been automatically renewed.

People who have been granted permanent resident status in Canada. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.

Data includes public and Catholic schools and school authorities. Private schools and publicly funded hospital and provincial schools and care, treatment and correctional facilities are not included.

Includes:

• board number
• board name
• school name
• school number
• school level
• school type
• school language
• enrolment

Source: As reported by schools in Ontario School Information System (OnSIS), October Submissions.

Boards update and maintain "/dataset/ontario-public-school-contact-information">contact information related to schools and boards of education.

Small cells have been suppressed:

• where fewer than 10 students are in a given category, the data is depicted with (10)
• the report may not be used in any way that could lead to the identification of an individual.

Note:

• Starting 2018-2019, enrolment numbers have been rounded to the nearest five.
• Where sum/totals are required, actual totals are calculated and then rounded to the nearest 5. As such, rounded numbers may not add up to the reported rounded totals.
• Includes Temporary Remote Learning Schools (TRLS)

This data includes the characteristics of Ontario Works and Ontario Disability Support Program cases, by census metropolitan area, and by the province including: * family type * family size * primary applicant's age and sex * consecutive months on social assistance A census metropolitan area (CMA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core. *[CMA]: census metropolitan area

This dataset reports the daily reported number of deaths involving COVID-19 by fatality type.

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
• Total number of deaths involving COVID-19
• Number of deaths with “COVID-19 as the underlying cause of death”
• Number of deaths with “COVID-19 contributed but not underlying cause”
• Number of deaths where the “Cause of death unknown” or “Cause of death missing”

Additional Notes

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.

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.

As of December 1, 2022, data are based on the date on which the death occurred. This reporting method differs from the prior method which is based on net change in COVID-19 deaths reported day over day.

Data are based on net change in COVID-19 deaths for which COVID-19 caused the death reported day over day. Deaths are not reported by the date on which death happened as reporting may include deaths that happened on previous dates.

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 number of deaths involving COVID-19 reported.

"_Cause of death unknown_" is the category of death for COVID-19 positive individuals with cause of death still under investigation, or for which the public health unit was unable to determine cause of death. The category may change later when the cause of death is confirmed either as “COVID-19 as the underlying cause of death”, “COVID-19 contributed but not underlying cause,” or “COVID-19 unrelated”.

"_Cause of death missing_" is the category of death for COVID-19 positive individuals with the cause of death missing in CCM.

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.

Data on resident owners who are persons occupying one of their residential properties: sex, age, total income, the type and the assessment value of the owner-occupied property, as well as the number and the total assessment value of residential properties owned.

This dataset provides total number of death registrations by the primary residence of the deceased (municipality). For privacy purposes, only regulation counts greater than 5 are available. Data released for 2024 is preliminary and may not match counts from other sources. The data represents counts in the reference calendar quarters, which are collated approximately 90 days after the end of the quarter. Previously released counts for 2024 are updated to reflect vital event registrations completed after the release of the initial report. Each subsequent quarterly report is the cumulative total of the preceding quarterly reports. ServiceOntario’s ability to provide timely information depends on receiving vital event registration information from a variety of sources. The preliminary data presented may not represent all the events that occurred in the reporting period. This is particularly true for events that occurred near the end of the reporting period as they may not have been received by ServiceOntario by the time the data is collated. Final counts for the reporting year will be released with the publication of the Office of the Registrar General Annual Report. The Vital Statistics Act requires that after the end of each calendar year, the Registrar General publish a report that includes the number of births, marriages, deaths, still-births, adoptions and changes of name registered during the calendar year preceding the one that has ended.