The Community Resilience Estimates (CRE) program provides an easily understood metric for how socially vulnerable every neighborhood in the United States is to the impacts of disasters.This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census, CRE, and ACS when using this data.Overview:Community resilience is the capacity of individuals and households within a community to prepare, absorb, respond, and recover from a disaster. Local planners, policy makers, public health officials, emergency managers, and community stakeholders need a variety of estimates to help assess the potential resiliency and vulnerabilities of communities and their constituent populations to help prepare and plan mitigation, recovery, and response strategies. Community Resilience Estimates (CRE) focuses on developing a tool to identify socio-economic vulnerabilities within populations. The 2022 Community Resilience Estimates (CRE) are produced using information on individuals and households from the 2022 American Community Survey (ACS) and the Census Bureau’s Population Estimates Program (PEP). The CRE uses small area modeling techniques that can be used for a broad range of disaster related events (hurricanes, tornadoes, floods, economic shocks, etc.) to identify population concentrations likely to be relatively more impacted by and have greater difficulties overcoming disasters. The end result is a data product which measures vulnerability more accurately and timely. Data:The ACS is a nationally representative survey with data on the characteristics of the U.S. population. The sample is selected from all counties and county-equivalents and has a sample size of about 3.5 million housing units each year. It is the premier source for timely and detailed population and housing information about our nation and its communities. We also use auxiliary data from the PEP, the Census Bureau’s program that produces and publishes estimates of the population living at a given time within a geographic entity in the U.S. and Puerto Rico. We use population data from the PEP by age group, race and ethnicity, and sex. Since the PEP does not go down to the census tract level, the CRE uses the Public Law 94-171 summary files (PL94) and Demographic Housing Characteristics File (DHC) tables from the 2020 Decennial Census to help produce the population base estimates. Once the weighted estimates are tabulated, small area modeling techniques are used to create the estimates for the CRE. Components of Social Vulnerability (SV): Resilience to a disaster is partly determined by the components of social vulnerability exhibited within a community’s population. To measure these components and construct the community resilience estimates, we designed population estimates based on individual- and household-level components of social vulnerability. These components are binary indicators or variables that add up to a maximum of 10 possible components using data from the ACS. The specific ACS-defined measures we use are as follows: Components of Social Vulnerability (SV) for Households (HH) and Individuals (I):SV 1: Income-to-Poverty Ratio (IPR) < 130 percent (HH). SV 2: Single or zero caregiver household - only one or no individuals living in the household who are 18-64 (HH). SV 3: Unit-level crowding with >= 0.75 persons per room (HH). SV 4: Communication barrier defined as either: Limited English-speaking households1 (HH) orNo one in the household over the age of 16 with a high school diploma (HH). SV 5: No one in the household is employed full-time, year-round. The flag is not applied if all residents of the household are aged 65 years or older (HH). SV 6: Disability posing constraint to significant life activity. Persons who report having any one of the six disability types (I): hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. SV 7: No health insurance coverage (I). SV 8: Being aged 65 years or older (I). SV 9: No vehicle access (HH). SV 10: Households without broadband internet access (HH). Each individual is assigned a 0 or 1 for each of the components based upon their individual or household attributes listed above. It is important to note that SV 4 is not double flagged. An individual will be assigned a 1, if either of the characteristics is true for their household. For example, if a household is linguistically isolated and no one over the age of 16 has attained a high school diploma or more education, the household members are only flagged once. The result is an index that produces aggregate-level (tract, county, and state) small area estimates: the CRE. The CRE provide an estimate for the number of people with a specific number of social vulnerabilities. In its current data file layout form, the estimates are categorized into three groups: zero , one-two, or three plus social vulnerability components. Differences with CRE 2021:The number of census tracts have increased from 84,414 in CRE 2021 to 84,415 in CRE 2022. This is due to the boundary changes in Connecticut implemented in 2022 census data products. To accommodate the boundary change, Connecticut also now has nine planning regions instead of eight counties in CRE 2022.To avoid confusion, the modeled rates are now set to equal zero in CRE 2022 for geographic areas with zero population in universe. To improve the population base estimates, CRE 2022 uses more detailed decennial estimates from the 2020 DHC in addition to PL94, whereas CRE 2021 just used PL94 due to availability at the time. See “2022 Community Resilience Estimates: Detailed Technical Documentation” for more information. Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). This dataset does not contain values for Puerto Rico or Island Areas at any level of geography.Further Information:Community Resilience Estimates Program Website https://www.census.gov/programs-surveys/community-resilience-estimates.htmlCommunity Resilience Estimates Technical Documentation https://census.gov/programs-surveys/community-resilience-estimates/technical-documentation.htmlFor Data Questionssehsd.cre@census.gov

Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025.

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 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template.

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 18th 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.

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 on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000.

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 greater than 10 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. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero.

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:

Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7)
1. Total - Private households by tenure including presence of mortgage payments and subsidized housing
2. Owner
3. With mortgage
4. Without mortgage
5. Renter
6. Subsidized housing
7. Not subsidized housing

Housing indicators in Core Housing Universe (12)
1. Total - Private Households by core housing need status
2. Households examined for core housing need
3. Households in core housing need
4. Below one standard only
5. Below affordability standard only
6. Below adequacy standard only
7. Below suitability standard only
8. Below 2 or more standards
9. Below affordability and suitability
10. Below affordability and adequacy
11. Below suitability and adequacy
12. Below affordability, suitability, and adequacy

Period of construction (10)
1. Total – Period of Construction
2. Before 2016
3. 1960 or before
4. 1961 to 1980
5. 1981 to 1990
6. 1991 to 2000
7. 2001 to 2005
8. 2006 to 2010
9. 2011 to 2015
10. 2016 to 2021 (Note 1)
Note 1). Includes data up to May 11, 2021.

Structural type of dwelling and Household income as proportion to AMHI (16)
1. Total - Structural type of dwelling
2. Single-detached house
3. Apartment in a building that has five or more storeys
4. Other attached dwelling
5. Apartment or flat in a duplex
6. Apartment in a building that has fewer than five storeys
7. Other single-attached house
8. Row house
9. Semi-detached house
10. Movable dwelling
11. Total – Private households by household income proportion to AMHI
12. Households with income 20% or under of area median household income (AMHI)
13. Households with income 21% to 50% of AMHI
14. Households with income 51% to 80% of AMHI
15. Households with income 81% to 120% of AMHI
16. Households with income 121% or more of AMHI

Selected characteristics (12)
1. Total – Private households by presence of activity limitation (Q18e only)
2. HH has at least one person who had an activity limitations reported for Question 18 e) only 1
3. Total – Age of primary household maintainer
4. 18 to 29 years
5. Total – Private households by military service status of the HH members
6. HH includes a person who is currently serving member and/or veteran
11. Total – Private households by shelter cost proportion to AMHI_1
12. Households with shelter cost 0.5% and under of AMHI
13. Households with shelter cost 0.6% to 1.25% of AMHI
14. Households with shelter cost 1.26% to 2% of AMHI
15. Households with shelter cost 2.1% to 3% of AMHI
16. Households with shelter cost 3.1% or more of AMHI*

Median income (2)
1. Number of households
2. Median income of household ($)
The household median income in the custom tabulation were estimates from a 25% sample-based data that have undergone weighting. These weights were applied to the sample data to produce estimates from the census long-form sample. The incomes used were drawn from the previous tax year, and therefore represent 2020 dollars.

[Only in "Census 2021 - Gender Diverse HHs" file] Genderdiversity (2)
1. Total - Gender diversity status of households
2. HH is gender diverse

File list (19 total):

Original data files (18):
1. Census 2021 - Table 1 - Median Incomes.ivt
2. Census 2021 - Table 2 - Canada.ivt
3. Census 2021 - Table 3 - Census Divisions.ivt
4. Census 2021 - Table 4 - Ontario CSDs.ivt
5. Census 2021 - Table 5 - BC CSDs.ivt
6. Census 2021 - Table 6 - Alberta CSDs.ivt
7. Census 2021 - Table 7 - Manitoba CSDs.ivt
8. Census 2021 - Table 8 - Saskatchewan CSDs.ivt
9. Census 2021 - Table 9-1 - Quebec CSDs (Part 1 of 3).ivt
10. Census 2021 - Table 9-2 - Quebec CSDs (Part 2 of 3).ivt
11. Census 2021 - Table 9-3 - Quebec CSDs (Part 3 of 3).ivt
12. Census 2021 - Table 10 - Newfoundland&Labrador CSDs.ivt
13. Census 2021 - Table 11 - PEI CSDs.ivt
14. Census 2021 - Table 12 - Nova Scotia CSDs.ivt
15. Census 2021 - Table 13 - New Brunswick CSDs.ivt
16. Census 2021 - Table 14 - Yukon CSDs.ivt
17. Census 2021 - Table 15 - NWT CSDs.ivt
18. Census 2021 - Table 16 - Nunavut CSDs.ivt
19. Census 2021 - Gender Diverse HHs.ivt

Pour de plus amples renseignements, veuillez visiter HART.ubc.ca.

Outils d'évaluation du logement ("HART")

Cet ensemble de données contient 18 tableaux qui s’appuient sur les données

Note: April 22, 2025: Updates to "CHN by income and HH size_v3".

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Note: April 16, 2025: Updates to the following files have been made on April 9th and 16th: "CHN by income and HH size_v2", "cd_hh_projections_v2", "csd_hh_projections_v2", and "CMAs_all data_v3".

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Note: March 31, 2025 files "Data_Element_1a" & "...1b" updated to v3 to include additional geographies (CDs and PTs) in the calculation of households close to rail transit.

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Note: This dataset as of March 31st, 2025 now contains data on all 12 data elements, including core housing need among "gender diverse" households (formerly called "2SLGBTQ+" households) in table "Data_Element_ 3".

That table (i.e. Data_Element_3) now also includes core housing need data on those priority populations reported in HART's HNA Tool. Two other outputs were migrated from that HNA Tool into this Federal HNA Template dataset:

• Income Categories and Affordable Shelter Costs, Percentage of Households in Core Housing Need by Income Category and Household Size, and 2021 Affordable Housing Deficit. (HICC Section 3.6), and
• Projected Households by Household Size and Income Category (HICC Section 6.1.1)

This Borealis dataset has been updated accordingly to include that data:

• "AMHI.csv" (2021 AMHI and dollar ranges of income and shelter cost categories)
• "cd_hh_projections.csv" (Projected households in 2031 for CDs)
• "csd_hh_projections.csv" (Projected households in 2031 for CSDs)
• "CHN by income and HH size.csv" (2021 core housing need by income and household size)

The geographical scope of the dataset has also been expanded. Before March 31st, only CSDs were included. As of March 31st, data on CDs, provinces/territories, the country of Canada, and CMA/CAs has been added. Not all data is available for all geographies:

• Data from CMHC's Rental Market Survey and Starts and Completions Survey are reported at the CSD level within CMAs/CAs. Results for provinces/territories/Canada are reported, but data for CDs is not. Since these surveys may not include all CSDs within a given CD, we have not attempted to aggregate this CSD data into CDs.
• Data from any custom census order by HART does not include CMA/CAs. We are able to aggregate the data by CSD into CMA/CAs, but all income and shelter cost data had been categorized based on the AMHI of the CSD as part of the original order (i.e. whether a household is "Very Low" income or "Low" income depends on the median household income of the CSD that the household lives in). This will lead to some inaccuracy and ambiguity of interpretation for the income or shelter cost data reported for CMAs.
• Data on "gender diverse" households is only available from Statistics Canada for geographies with a population count greater than 50,000 as of the 2021 census. This represents a total of 239 geographies (incl. Canada and the provinces/territories). Due to the low number of CSDs with this data, we have not attempted to aggregated this to the CMA/CA level.

Data for CMAs/CAs will be added to the tool by mid-April 2025, but the source data has been summarized and included in this dataset:

• "CMAs_all data.csv" (All available data for CMAs and CAs)

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Update (March 14, 2025): Tables "Data_Element_1a" and "...1b" have been updated to exclude some non-rail rapid transit stops that were erroneous included, notably in Winnipeg.

For more information, please visit HART.ubc.ca.

Housing Assessment Resource Tools (HART)

This database was created to accompany the dashboard on HART's website called the "Federal Housing Needs Assessment Template." URL: https://hart.ubc.ca/federal-hna-template/.

This dashboard presents housing-related data to help communities complete the Housing Needs Assessment template requested by the Government of Canada as a requirement for certain funding applications. For more information on that template, please visit the Government of Canada's website (https://housing-infrastructure.canada.ca/housing-logement/hna-ebml/template-modele-eng.html).

This dataset represents the underlying data used to populate HART's dashboard. The data contains some public and custom data from Canada's Census of Population (author: Statistics Canada), public data from the Canada Mortgage and Housing Corporation (CMHC) regarding it's Rental Market Survey as well as it's Starts and Completions Survey, private data from the Co-operative Housing Federation of Canada, and data created by Licker Geospatial Consulting Co. specifically for this dashboard. Due to the variety of sources, the dataset is not complete for every CSD.

The full list of data elements, their sources, and any methodological considerations can be found in the attached file "Federal-HNA-Template-Methodology.pdf".

The other attached files have been named to correspond with the Data Elements listed in the methodology document on page 2. Each file contains data on all available geographies. Some files will have a letter after he number (i.e. "1a" and "1b") if there was more than one data table associated with a given data element. Some data will not be available until March 14, 2025, namely elements 3, 5, and 11.

Data Elements:

1. Counts and percentages of households within 800m and 200m of rail/light-rail transit station (applies only to municipalities with 2021 population of 30,000+, excluding BC and Quebec) (HICC Section 3.1.1)
2. Changes to headship rates 2016-2021 & Household Suppression by age of Primary household maintainer following the Province of British Columbia’s HNR methodology (HICC Section 3.3)
3. (Part 2, March 14) Provide priority groups by core housing need status (Youth age 18-29, 2SLGBTQ+, People dealing with mental health and addictions issues, Veterans) (HICC Section 4.1)
4. Number of secondary rental units (HICC Section 5.2.1)
5. (Part 2, March 14) The number of affordable units for low and very low-income households built, and the number lost (HICC Section 5.3)
6. Change in Average rents (HICC Section 5.4)
7. Change in Vacancy rates (HICC Section 5.5)
8. Changes in core housing need over time in both tenant and owner-occupied households (HICC Section 5.6)
9. Number of housing units that are subsidized (HICC Section 5.7.1)
10. Number of housing units that are below market rent in the private market (HICC Section 5.7.1)
11. (Part 2, March 14th) Number of co-operative housing units (HICC Section 5.7.1)
12. Housing starts by structural type and tenure (HICC Section 5.9.2)

Each "Data_Element_#" file has the geography indicated as a geocode of a certain length. Provinces and territories have 2 digits (e.g. 10), census divisions have 4 digits (e.g. 1011), census subdivisions have 7 digits (e.g. 1011001), and census metropolitan areas and census agglomerations have a 3 digit geocode (e.g. 001). This geocode is drawn from the latest edition of Statistics Canada's Standard Geographical Classification (SCG) which provides standard names and codes for the geographical regions of Canada.

Each geocode may have multiple rows of data associated with it. For example, in the file Data_Element_6 each geography has three rows:

1. % Change in Avg Rent,
2. Avg Monthly Rent, and
3. Change in Avg Rent.

(2025)