This statistic shows the estimated population of Manitoba, Canada from 2000 to 2022. In 2022, the estimated population of Manitoba was about 1.41 million people. This is an increase from 2000, when there were about 1.15 million people living in Manitoba.

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

In 2048, the population in Manitoba is projected to reach about 1.84 million people. This is compared to a population of 1.46 million people in 2024.

This table contains 13 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia ...).

This statistic shows the population of Manitoba, Canada in 2022, by age and sex. In 2022, there were 126,054 females 65 years of age and over in Manitoba.

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate that shows two maps. The first map shows the density of population per square mile for every township in British Columbia and Alberta, circa 1911. The second map shows the density of population per square mile for every township in Manitoba and Saskatchewan, circa 1911. Communities with a population greater than 5000 people are shown as proportional dots on the map. In addition, major railway systems displayed. The map displays the rectangular survey system which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

This statistic shows the population distribution of Manitoba, Canada, in 2016, by urban/rural type. In 2016, 55.7 percent of Manitoba's population lived in large urban population centers.

An interactive web map illustrating the future state of Emergency Medical Service (EMS) Facilities in Manitoba outside the Winnipeg Regional Health Authority. An interactive web map illustrating the future state of Emergency Medical Service (EMS) Facilities in Manitoba outside the Winnipeg Regional Health Authority. The map includes points representing the future locations of EMS facilities. Polygons representing drive time catchment areas (9, 15, and 30 minutes) for each EMS facility are also shown, including the approximate population served (Statistics Canada 2011 census data) and incident responses (2015/16 data) within each catchment area . Note that this information is only available for rural Manitoba and areas south of 53°N. Pop-ups for the future EMS Facilities display the following information: Community Name Facility Name Pop-ups for the future catchment areas display the following information: Community Name Facility Name Total Population in 9, 15, and 30 minute night time catchment areas (south of 53°N only) Total Incidents ((2015/16) in 9, 15, and 30 minute night time catchment areas (south of 53°N only)

This statistic shows the number of households in Manitoba, Canada, in 2016, by household size. In this year, there were 164,880 private households in Manitoba with 2 persons.

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate map that shows 2 maps. The first map shows the origin of the population in Manitoba and Saskatchewan, circa 1911. The second map shows the origin of the population in British Columbia and Alberta, circa 1911A varying number of ethnic groups are shown, but always included are: English, Scotch [Scottish], Irish, French and German. People of British origin predominate in all provinces, except Quebec, where the French predominate. There is a cosmopolitan population due to immigration from Great Britain and Europe, but British are the predominating people in British Columbia and Alberta. Major railway systems are displayed, which extend into the U.S. The map presents the rectangular survey system, which records the land that is available to the public. This grid like system is divided into sections, townships, range, and meridian from mid-Manitoba to Alberta.

In order to anticipate the impact of local public policies, a synthetic population reflecting the characteristics of the local population provides a valuable test bed. While synthetic population datasets are now available for several countries, there is no open-source synthetic population for Canada. We propose an open-source synthetic population of individuals and households at a fine geographical level for Canada for the years 2021, 2023 and 2030. Based on 2016 census data and population projections, the synthetic individuals have detailed socio-demographic attributes, including age, sex, income, education level, employment status and geographic locations, and are related into households. A comparison of the 2021 synthetic population with 2021 census data over various geographical areas validates the reliability of the synthetic dataset. Users can extract populations from the dataset for specific zones, to explore ‘what if’ scenarios on present and future populations. They can extend the dataset using local survey data to add new characteristics to individuals. Users can also run the code to generate populations for years up to 2042.

To capture the full social and economic benefits of AI, new technologies must be sensitive to the diverse needs of the whole population. This means understanding and reflecting the complexity of individual needs, the variety of perceptions, and the constraints that might guide interaction with AI. This challenge is no more relevant than in building AI systems for older populations, where the role, potential, and outstanding challenges are all highly significant.

The RAIM (Responsible Automation for Inclusive Mobility) project will address how on-demand, electric autonomous vehicles (EAVs) might be integrated within public transport systems in the UK and Canada to meet the complex needs of older populations, resulting in improved social, economic, and health outcomes. The research integrates a multidisciplinary methodology - integrating qualitative perspectives and quantitative data analysis into AI-generated population simulations and supply optimisation. Throughout the project, there is a firm commitment to interdisciplinary interaction and learning, with researchers being drawn from urban geography, ageing population health, transport planning and engineering, and artificial intelligence.

The RAIM project will produce a diverse set of outputs that are intended to promote change and discussion in transport policymaking and planning. As a primary goal, the project will simulate and evaluate the feasibility of an on-demand EAV system for older populations. This requires advances around the understanding and prediction of the complex interaction of physical and cognitive constraints, preferences, locations, lifestyles and mobility needs within older populations, which differs significantly from other portions of society. With these patterns of demand captured and modelled, new methods for meeting this demand through optimisation of on-demand EAVs will be required. The project will adopt a forward-looking, interdisciplinary approach to the application of AI within these research domains, including using Deep Learning to model human behaviour, Deep Reinforcement Learning to optimise the supply of EAVs, and generative modelling to estimate population distributions.

A second component of the research involves exploring the potential adoption of on-demand EAVs for ageing populations within two regions of interest. The two areas of interest - Manitoba, Canada, and the West Midlands, UK - are facing the combined challenge of increasing older populations with service issues and reducing patronage on existing services for older travellers. The RAIM project has established partnerships with key local partners, including local transport authorities - Winnipeg Transit in Canada, and Transport for West Midlands in the UK - in addition to local support groups and industry bodies. These partnerships will provide insights and guidance into the feasibility of new AV-based mobility interventions, and a direct route to influencing future transport policy. As part of this work, the project will propose new approaches for assessing the economic case for transport infrastructure investment, by addressing the wider benefits of improved mobility in older populations.

At the heart of the project is a commitment to enhancing collaboration between academic communities in the UK and Canada. RAIM puts in place opportunities for cross-national learning and collaboration between partner organisations, ensuring that the challenges faced in relation to ageing mobility and AI are shared. RAIM furthermore will support the development of a next generation of researchers, through interdisciplinary mentoring, training, and networking opportunities.

The provide detailed statistical tables for 18 scenarios by single year of the projection period (2001 to 2017). For each of the scenarios, data are available for persons who identify with each of the following three groups: the North American Indian population, the Métis or the Inuit. All three groups were projected separately for each of the ten provinces and three territories. However, the subprovincial and subterritorial level shown for the three groups varies as it depends on the groups' size. For the North American Indians, future numbers were calculated for the urban parts of all census metropolitan areas (CMAs), urban areas outside CMAs, rural areas and reserves. For the Métis, places of residence were grouped into urban parts of CMAs, urban areas outside CMAs and rural areas, which also include reserves. Because of their relatively small size, the Inuit population was projected separately for urban and rural locations only. This information is further broken down by age and sex. The 18 scenarios, as well as scenario-specific assumptions on the future trend in fertility and internal migration, are presented in the table below. In addition to these two components of population growth, all scenarios assumed declining mortality and negligible importance of international migration to the change of the size of three Aboriginal groups. The statistical tables of this CD-ROM are organized into three sections: Aboriginal groups - The projected population by Aboriginal group, type of residence, province/territory and sex for the 18 scenarios by single year from 2001 to 2017; Age and sex - The projected population by Aboriginal group, type of residence, age group and sex for the 18 scenarios by single year from 2001 to 2017; and Province/territory - The projected total Aboriginal population by province/territory, age group, sex and type of residence for the 18 scenarios for 2001 and 2017. The statistical tables are supplementary to the publication Projections of the Aboriginal populations, Canada, provinces and territories: 2001 to 2017 (catalogue no. 91-547).

Note: The data release is complete as of August 14th, 2023. 1. (Added April 4th) Canada and Census Divisions = Early April 2023 2. (Added May 1st) Ontario, British Columbia, and Alberta Census Subdivisions (CSDs) = Late April 2023 3a. (Added June 8th) Manitoba and Saskatchewan CSDs 3b. (Added June 12th) Quebec CSDs = June 12th 2023 4. (Added June 30th) Newfoundland and Labrador, Prince Edward Island, New Brunswick, and Nova Scotia CSDs = Early July 2023 5. (Added August 14th) Yukon, Northwest Territories, and Nunavut CSDs = Early August 2023. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Census of Canada. The tables are a custom order and contains data pertaining to core housing need and characteristics of households. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The last table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. Included alongside the data tables is a guide to HART's housing need assessment methodology. This guide is intended to support independent use of HART's custom data both to allow for transparent verification of our analysis, as well as supporting efforts to utilize the data for analysis beyond what HART did. There are many data fields in the data order that we did not use that may be of value for others. 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, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole 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: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. 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: Note 1: Certain data fields from the original .ivt...

La deuxième édition de l’Atlas du Canada (1915) comprend une planche contenant deux cartes. La première représente la densité de la population, par mil carré, de tous les cantons de la Colombie-Britannique et de l’Alberta vers 1911. La seconde carte représente la densité de la population, par mil carré, de tous les cantons du Manitoba et de la Saskatchewan vers 1911. Les communautés de plus de 5000 habitants sont représentées à l’aide de points noirs proportionnels. De plus, la carte indique les systèmes de chemins de fer principaux et le système rectangulaire d’arpentage des terres disponible pour le public. Le quadrillage est divisé en sections, en villages, en rangs et en méridiens du milieu du Manitoba à l’Alberta.

This statistic shows the number of deaths in Manitoba, Canada from 2000 to 2022. Between July 1, 2021 and June 30, 2022, a total of 12,477 people died in Manitoba.

The Manitoba Longitudinal Study of Young Adults (MLSYA) was a five-year longitudinal study conducted by Liquor and Gaming Authority of Manitoba (LGA), formerly the Manitoba Gaming Control Commission (MGCC); the Addictions Foundation of Manitoba; and the former Manitoba Lotteries Corporation. The study followed a sample of Manitobans between the ages of 18 and 20 from 2007 and 2011. The aim of the study was to develop a better understanding of protective facts that promote responsible gambling and risk factors for gambling-related harms. In addition to gambling-specific data, the MLSYA study includes: Psychosocial indicators Demographic characteristics Measures of alcohol and drug use among participants The final sample for all waves of data included 516 participants. Participants were on average 18.9 years of age at recruitment and 22.2 years of age at study completion. LGA commissioned Prairie Research Associates Inc. to recruit participants and collect data for the MLSYA. While the sample is not truly random, it is reasonably representative of the Manitoba population, other than an overrepresentation of participants living in Winnipeg. Participants were recruited through various methods. This included random-digit dialing, onsite casino recruitment, and advertisements at post-secondary institutions and VLT lounges. At each subsequent wave, past participants were contacted and asked to take part in the next wave of the study. Wave 1 data was collected between November 2007 and October 2002. Wave 2 data was collected between December 2008 and December 2009. Wave 3 data was collected between May and December 2010. Wave 4 data was collected between May and December 2011. Additional information on sampling, retention, study variables, and survey questionnaires can be found in the accompanying summary report and codebook.

RHA Districts are geographic areas that are used to define populations and catchment areas for the administration and delivery of health services. This file provides RHA district boundaries for cartographic and analytical purposes. Within Manitoba there are five Regional Health Authorities (or "RHAs") responsible for the delivery of health service in five specific areas of the province described as "health regions". (In practice, the terms "health region" and "RHA" are used interchangeably to describe these geographic areas.) In consultation with Manitoba Health, Healthy Living and Seniors, and with the Manitoba Centre for Health Policy, each of the RHAs has defined further subdivisions within each RHA . These sub-areas of each RHA generally correspond to areas of clustered population and/or service delivery. They are used to plan service delivery, and are also used to describe and analyze population health and health service use with more specificity than analysis at the RHA level could provide. Due to the size and the total population of Manitoba's RHAs, there are two levels of subdivided RHA geography which are used for analytical and planning purposes. The smallest subdivisions used for this purpose are RHA Districts. RHA Districts within an RHA are also grouped into larger sub-areas with the RHA called RHA Zones, within each RHA District within an RHA included in precisely one of these zone. This shapefile contains the boundaries of Manitoba's RHA districts.

Incident-based crime statistics (actual incidents, rate per 100,000 population, percentage change in rate, unfounded incidents, percent unfounded, total cleared, cleared by charge, cleared otherwise, persons charged, adults charged, youth charged / not charged), by detailed violations (violent, property, traffic, drugs, other Federal Statutes), police services in Manitoba, 1998 to 2023.

The household incomes chart shows how many household fall in each of the income brackets specified by Statistics Canada.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.