Homeless Shelter System Monthly Utilization This metric tracks the number of shelter beds used by individuals and families per month. Overnight shelters provide nightly shelter for individuals for up to 12 consecutive hours and do not serve families with children. Interim shelters house families and individuals for up to 120 days. DFSS coordinates activities and funding to increase the availability of permanent and supportive housing services in Chicago. DFSS funds community based agencies that provide services to persons and families who are homeless or at imminent risk of homelessness so they can sustain safe and secure housing in the effort to achieve self-sufficiency.

Updated every Thursday People experiencing homelessness are at risk for infection through community spread of COVID-19. The data below describes impacts of COVID-19 on individuals who are experiencing homelessness, whether they are able to access a congregate shelter or unsheltered (sleeping outside or in places not meant for human habitation).

For COVID-19 investigation purposes, people experiencing homelessness are defined as those who have lived on the streets or stayed in a shelter, vehicle, abandoned building, encampment, tiny house village/tent city, or supportive housing program (transitional or permanent supportive) at any time during the 12 months prior to COVID-19 testing, without evidence that they were otherwise permanently housed. Public Health, the Department of Community and Human Services, homeless service providers, healthcare providers, and the City of Seattle have partnered for increased testing in this community.

Context

The Austin Animal Center is the largest no-kill animal shelter in the United States that provides care and shelter to over 18,000 animals each year. As part of the AAC's efforts to help and care for animals in need, the organization makes available its accumulated data and statistics as part of the city of Austin's Open Data Initiative.

Content

The data contains intakes and outcomes of animals entering the Austin Animal Center from the beginning of October 2013 to the present day. The datasets are also freely available on the Socrata Open Data Access API and are updated daily.

The following are links to the datasets hosted on Socrata's Open Data:

• Austin Animal Center Intakes
• Austin Animal Center Outcomes

The data contained in this dataset is the outcomes and intakes data as noted above, as well as a combined dataset. The merging of the outcomes and intakes data was done on a unique key that is a combination of the given Animal ID and the intake number. Several of the animals in the dataset have been taken into the shelter multiple times, which creates duplicate Animal IDs that causes problems when merging the two datasets.

Copied from the description of the Shelter Outcomes dataset, here are some definitions of the outcome types:

• Adoption
  • the animal was adopted to a home
• Barn Adoption
  • the animal was adopted to live in a barn
• Offsite Missing
  • the animal went missing for unknown reasons at an offsite partner location
• In-Foster Missing
  • the animal is missing after being placed in a foster home
• In-Kennel Missing
  • the animal is missing after being transferred to a kennel facility
• Possible Theft
  • Although not confirmed, the animal went missing as a result of theft from the facility
• Barn Transfer
  • The animal was transferred to a facility for adoption into a barn environment
• SNR
  • SNR refers to the city of Austin's Shelter-Neuter-Release program. I believe the outcome is representative of the animal being released.

Acknowledgements

The data presented here is only possible through the hard work and dedication of the Austin Animal Center in saving and caring for animal lives.

Inspiration

Following from the first dataset I posted to Kaggle, Austin Animal Shelter Outcomes, which was initially filtered for just cats as part of an analysis I was performing, I wanted to post the complete outcome and complementing intake datasets. My hope is the great users of Kaggle will find this data interesting and want to explore shelter animal statistics further and perhaps get more involved in the animal welfare community. The analysis of this data and other shelter animal provided datasets helps uncover useful insights that have the potential to save lives directly.

The National Service Provider List (NSPL) is a comprehensive list of emergency and transitional homeless shelters with permanent beds in Canada. It is updated on an annual basis by the Homelessness Policy Directorate of Housing, Infrastructure and Communities Canada (HICC). It includes information on bed capacity, location, and the clientele served by each service provider. The annual updates are made possible through collaborative efforts, relying on data contributions from service providers, communities, and various partners. This multifaceted information is gathered through a combination of primary and secondary research methods, as well as through collaborative data-sharing initiatives with jurisdictions utilizing the Homeless Individuals and Families Information System (HIFIS) or comparable administrative systems for tracking homelessness data. Related Reports and Statistics: -The Shelter Capacity Report: Housing, Infrastructure and Communities Canada (HICC) - Data analysis, reports and publications (infc.gc.ca) https://secure.infc.gc.ca/homelessness-sans-abri/reports-rapports/publications-eng.html -Statistics Canada. Table 14-10-0353-01 Homeless Shelter Capacity in Canada from 2016 to 2022, Housing, Infrastructure and Communities Canada (HICC) (statcan.gc.ca): https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410035301

The City of Toronto funds and operates services dedicated to people experiencing homelessness in Toronto. The overnight services, including emergency shelters, respites, and other allied services (including hotel/motel programs and warming centres), use the Shelter Management Information System (SMIS) to intake people who are accessing these services into their programs. The Shelter System Flow data shares information about people experiencing homelessness who are entering and leaving the shelter system each month, including the number of unique people who have used the shelter system at least one time in the past three months and are considered to be actively experiencing homelessness (ie; they were not discharged to permanent housing). This information provides insight into who is experiencing homelessness and how the City's system is functioning. It will also help measure progress towards the vision of reducing homelessness in Toronto to rare, brief, and non-recurring instances. Over time, the data will be expanded to capture more people, such as people sleeping outdoors and people using overnight homelessness services that are not funded by the City of Toronto to provide more comprehensive picture of all people experiencing homelessness in Toronto. Based on the most recent Street Needs Assessment, we anticipate that approximately 18 per cent of people experiencing homelessness in Toronto are not currently reflected in this data.

The data set provides a listing of all the active shelters serving the City of Toronto area. Included in the dataset is the name of the shelter, program name, sector served (i.e. men, women, youth, families) addresses, funded program capacity, and the number of people that occupied those spaces at 4:00 AM the next morning. For example, the occupancy count of January 1st would be taken on January 2nd at 4 AM. The reporting in this dataset has now been updated as a new open data set. This updated data set includes all overnight service programs administered by the Shelter, Support and Housing Administration division (e.g. 24-hour respites and COVID-19 hotel shelter programs) rather than just shelter programs. This new data set can be found here. Note : For reasons of confidentiality, information regarding Violence Against Women shelters are removed from the dataset. Please also note : During the COVID-19 pandemic response, shelter programs have undergone significant change. This dataset includes capacity data which are based on pre-existing funding arrangements with shelter providers, rather than the available capacity in the current COVID-19 circumstances. As programs implement physical distancing measures in their facilities, changes to program capacities often took some time to be reflected in this dataset. We advise users not to rely on capacity data to interpret current bed availability.

Data Prepared by Los Angeles Homeless Services AuthorityJune 26, 2019Homeless Count 2019 Dashboard MethodologyTotal number of people experiencing homelessness is the sum of (1) the sheltered population (the total number of people staying in emergency shelter, transitional housing, or safe haven programs on the night of the point-in-time count) and (2) the unsheltered population (the total number of people counted by volunteers and the estimated number of people sleeping in the dwellings counted by volunteers).

(1) The total number of people experiencing homelessness who slept in an emergency shelter, transitional housing, or safe haven program was reported to LAHSA by each provider and assigned to a census tract. For shelter programs with multiple scattered sites in the LA CoC, an administrative address is used for locating the sheltered population in this dashboard. Shelters that serve persons fleeing domestic or intimate partner violence are excluded due to confidentiality concerns. Persons receiving motel vouchers are excluded in this dashboard because the location of the motel is unknown.

(2) The total number of people experiencing homelessness who slept on the street or in a dwelling not meant for human habitation were counted by volunteers on January 22nd, 23rd, or 24th. 3,873 demographic survey interviews were conducted with persons experiencing unsheltered homelessness from December 2018 to March 2019 to describe the population’s demographics and approximate the number of people in each dwelling. The total persons in uninhabitable dwellings was estimated for each type (car, van, camper/RV, tent, or makeshift shelter) and was estimated at the SPA-level for individual and for family households and can be found on our website. Estimates of the people inside these dwellings was rounded to whole numbers for the purposes of this dashboard.Density ScoringThere are 4 columns seen in the data that represent the density of homeless Individuals per square mile. The 4 column labeled RFP-Scoring is based on the data range between the min and max of homeless calculated of LA County's Homeless Individual numbers. For break down the data is given a specific score based on the density. Below are the ranges:0=01= 1-32= 4-73= 8-114= 12-185= 19-276= 28-427= 43-638= 64-999= 100-17910= 180-5341The breakdown of the data used was quantitative statistical range for 11 categories, 0 being one of the ranges.

This dataset provides estimates for the total number of people experiencing homelessness as the sum of the sheltered population (the total number of people staying in emergency shelter, transitional housing, or safe haven programs on the night of the point-in-time count) and the unsheltered population (the total number of people counted by volunteers and the estimated number of people sleeping in the dwellings counted by volunteers) per census tract in 2019. Information like this may be useful for studying homeless populations.(1) The total number of people experiencing homelessness who slept in an emergency shelter, transitional housing, or safe haven program was reported to LAHSA by each provider and assigned to a census tract. For shelter programs with multiple scattered sites in the LA CoC, an administrative address is used for locating the sheltered population in this dashboard. Shelters that serve persons fleeing domestic or intimate partner violence are excluded due to confidentiality concerns. Persons receiving motel vouchers are excluded in this dashboard because the location of the motel is unknown. (2) The total number of people experiencing homelessness who slept on the street or in a dwelling not meant for human habitation were counted by volunteers on January 22nd, 23rd, or 24th. 3,873 demographic survey interviews were conducted with persons experiencing unsheltered homelessness from December 2018 to March 2019 to describe the population’s demographics and approximate the number of people in each dwelling. The total persons in uninhabitable dwellings was estimated for each type (car, van, camper/RV, tent, or makeshift shelter) and was estimated at the SPA-level for individual and for family households and can be found on our website. Estimates of the people inside these dwellings was rounded to whole numbers for the purposes of this dashboard.Spatial Extent: Los Angeles CountySpatial Unit: Census TractCreated: 2019Updated: n/aSource: Los Angeles Homeless Services AuthorityContact Telephone: 213-683-3333Contact Email: datasupport@lahsa.orgSource Link:https://www.lahsa.orgAPI Source Link: https://geohub.lacity.org/datasets/homeless-count-los-angeles-county-2019?geometry=-120.792%2C33.011%2C-115.783%2C34.609

The Street Needs Assessment (SNA) is a survey and point-in-time count of people experiencing homelessness in Toronto on April 26, 2018. The results provide a snapshot of the scope and profile of the City's homeless population. The results also give people experiencing homelessness a voice in the services they need to find and keep housing. The 2018 SNA is the City's fourth homeless count and survey and was part of a coordinated point-in-time count conducted by communities across Canada and Ontario. The results of the 2018 Street Needs Assessment were summarized in a report and key highlights slide deck. During the course of the night, a 23 core question survey was completed with 2,019 individuals experiencing homelessness staying in shelters (including provincially-administered Violence Against Women shelters), 24-hour respite sites (including 24-hour women's drop-ins and the Out of the Cold overnight program open on April 26, 2018), and outdoors. The SNA includes individuals experiencing absolute homelessness but does not capture hidden homelessness (i.e., people couch surfing or staying temporarily with others who do not have the means to secure permanent housing). This dataset includes the SNA survey results; it does not include the count of people experiencing homelessness in Toronto. The SNA employs a point-in-time methodology for enumerating homelessness that is now the standard for most major US and Canadian urban centres. While a consistent methodology and approach has been used each year in Toronto, changes were made in 2018, in part, as a result of participation in the national and provincial coordinated point-in-time count. As a result, caution should be made in comparing these results to previous SNA survey results. Key changes included: administering the survey in a representative sample (rather than census) of shelters; administering the survey in all 24-hour respite sites and a sample of refugee motel programs added to the homelessness service system since the 2013 SNA; and a standard set of core survey questions that communities were required to follow to ensure comparability. In addition, in 2018, surveys were not conducted in provincially-administered health and treatment facilities and correctional facilities as was done in 2013. The 2018 survey results provide a valuable source of information about the service needs of people experiencing homelessness in Toronto. This information is used to improve the housing and homelessness programs provided by the City of Toronto and its partners to better serve our clients and more effectively address homelessness. Visit https://www.toronto.calcity-government/data-research-maps/research-reports/housing-and-homelessness-research-and-reports/

The number individuals experiencing homelessness in Hamilton and their length of homelessness. Individuals depicted are shown as being homeless for six months or less, or for more than months. Includes those who have had a shelter stay in the past 90 days. This gives a more fulsome picture of individuals experiencing homelessness who may access shelters in one month and not the next.Data is collected by homeless-serving shelters through the Homeless Individuals and Families Information System (HIFIS).

Homeless Shelter Capacity in Canada, bed and shelter counts by target population and geographical location for emergency shelters, transitional housing, and domestic violence shelters.

The City of Toronto funds and operates services dedicated to people experiencing homelessness in Toronto. The overnight services, including emergency shelters, respites, and other allied services (including hotel/motel programs and warming centres), use the Shelter Management Information System (SMIS) to intake people who are accessing these services into their programs. The Shelter System Flow data shares information about people experiencing homelessness who are entering and leaving the shelter system each month, including the number of unique people who have used the shelter system at least one time in the past three months and are considered to be actively experiencing homelessness (ie; they were not discharged to permanent housing). This information provides insight into who is experiencing homelessness and how the City's system is functioning. It will also help measure progress towards the vision of reducing homelessness in Toronto to rare, brief, and non-recurring instances. Over time, the data will be expanded to capture more people, such as people sleeping outdoors and people using overnight homelessness services that are not funded by the City of Toronto to provide more comprehensive picture of all people experiencing homelessness in Toronto. Based on the most recent Street Needs Assessment, we anticipate that approximately 18 per cent of people experiencing homelessness in Toronto are not currently reflected in this data.

This dataset provides information on individuals experiencing sheltered or unsheltered homelessness in the Austin/Travis County Continuum of Care (CoC) on a single night in January when the Point in Time (PIT) Count occurs. "Sheltered" homelessness refers to individuals residing in emergency shelter, safe haven, or transitional housing project types. Unsheltered homelessness refers to individuals with a primary nighttime residence that is a public or private place not designed for or ordinarily used as a regular sleeping accommodation for human beings, including a car, park, abandoned building, bus or train station, airport, or camping ground on the night designated for the count. This measure overlaps, but is different from, the annual count of sheltered homelessness in HMIS (SD23 Measure EOA.E.1b). Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/hjiv-t2tm Last Updated December 2020 with data for 2020 PIT Count.

If you are in need of emergency shelter space, please call the City of Toronto’s Central Intake line at 416-338-4766 or 1-877-338-3398. This catalogue entry provides two data sets related to calls to Central Intake. Central Intake is a City-operated, 24/7 telephone-based service that offers referrals to emergency shelter and other overnight accommodation, as well as information about other homelessness services. These two data sets provide information about calls received by Central Intake, the outcomes of those calls, and the number of individuals who could not be matched to a shelter space each day. The first, Central Intake Service Queue Data, provides counts of the number of unique individuals who contacted Central Intake to access emergency shelter but were not matched to a shelter space. Generated through Central Intake caseworkers' use of the City's Shelter Management Information System (SMIS), the data are reported as a count for every operational day. The SMIS service queue for Central Intake records when a bed is requested for a caller seeking a shelter space. Those callers who could not be matched to an available space that suits their needs at the time of their call remain in the queue until they can be provided a referral or until the closeout process at the end of the night (i.e. 4:00 a.m.). Service Queue data combines data exported from the Central Intake service queue at 4:00 a.m., with manually coded outcome data based on the review of each individual's SMIS records for the day. SSHA began collecting data on how many people remain unmatched in the service queue over a 24 hour period at the beginning of November 2020. Given the manual nature of the preparation of the data in this data set, this file will be updated on a monthly basis. Data will be reported separately for every operational day in that month. The second data set, Central Intake Call Wrap-Up Codes Data, provides counts of calls answered by Central Intake, classified by the nature of the call. When a call is handled by a caseworker at Central Intake, the caseworker assigns a wrap-up code to the call. This tracking allows for analysis of call trends. Central Intake uses 13 distinct wrap-up codes to code the calls they receive. This data set provides a daily summary of the number of calls received by each call wrap-up code. The data are manually retrieved from the City's call centre database reports. Given the manual nature of the preparation of the data in this data set, this file will be updated on a monthly basis. Data will be reported separately for every operational day in that month. Please note that while the wrap-up codes provide information related to the volume and type of calls answered by Central Intake, the data do not track requests made by unique individuals nor the ultimate outcomes of referrals. Please also note that the previews and Data Features below only show information pertaining to the Central Intake Call Wrap-Up Codes Data dataset.

BC Stats (with partners at the Ministry of Housing, Ministry of Social Development and Poverty Reduction (SDPR), and BC Housing) has developed aggregated summary statistics estimating the homeless population in B.C. These estimates were derived from three administrative service use datasets from the Data Innovation Program (DIP): shelter use from BC Housing, social assistance payments from SDPR, demographic information from the Health medical service plan (MSP) central demographics file. The analytic definition of homelessness includes individuals who received income assistance with no fixed address for at least three consecutive months or those who visited a shelter at any time throughout the year. Estimates have been aggregated into four tables: * Annual estimates of the homeless population by age and gender * Annual estimates of the homeless population by chronicity category (chronic vs non-chronic homelessness) * Annual estimates of the homeless population by census division * Monthly estimates of the homeless population by service use (income assistance with no fixed address, shelter use, or both) \ Estimates are available for 2019-2022. Full methodology details are available in the Homeless Cohort Development - Technical Documentation resource.

What is the Point-In-Time Count?

The U.S. Department of Housing and Urban Development (HUD) and Washington State Department of Commerce require communities to conduct a one-day Point-In-Time (PIT) Count to survey individuals experiencing homelessness. PIT Counts are one source of data among many that help us understand the magnitude and characteristics of people who are homeless in our community.

The Point-In-Time (PIT) Count is a one-day snapshot that captures the characteristics and situations of people living here without a home. The PIT Count includes both sheltered individuals (temporarily living in emergency shelters or transitional housing) and unsheltered individuals (those sleeping outside or living in places that are not meant for human habitation).

The annual PIT Count happens the last Friday in January, and is carried out by volunteers who interview people and asks where they slept the night before, where their last residence was located, what may have contributed to their loss of housing, and disabilities the individual may have. It also asks how long the individual has been homeless, age and demographics, and whether the person is a veteran and/or a survivor of domestic violence.

Like all surveys, the PIT Count has limitations. Results from the Count are influenced by the weather, by availability of overflow shelter beds, by the number of volunteers, and by the level of engagement of the people we are interviewing. Comparisons from year to year should be done with those limitations in mind.

This dataset provides information on individuals experiencing sheltered homelessness in the Austin/Travis County Continuum of Care (CoC) in a given fiscal year. "Sheltered" homelessness refers to individuals residing in emergency shelter, safe haven, or transitional housing project types. This measure overlaps, but is different from, the Point in Time (PIT) Count (SD23 Measure EOA.E.1a), which is a snapshot of both sheltered and unsheltered homelessness on one night in January. Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/2ejn-hrh2

This data set provides a daily list of active overnight shelter and allied services in the Toronto Shelter and Support Services division's Shelter Management Information System (SMIS) database. The data provides daily updated information about shelter and overnight service programs administered by TSSS including the program's operator, location, classification, occupancy and capacity. This reporting revises and updates the approach taken in the Daily Shelter Occupancy data set, starting with the current year data for 2021. This new data set includes the following revisions: Overnight service type: The previous data set only reported on shelter programs, now all overnight service types where occupancy is tracked in SMIS are included. Capacity type: Programs are categorized in this data set as having either bed based or room based capacity. Bed based capacity is typically applicable for programs with common sleeping areas, while room based capacity is typically applicable for family programs and hotel programs where sleeping rooms are not shared by people from different households. This change prevents over reporting of capacity in room based programs. Two measures of capacity: This data set provides information about two measures of capacity. Funding capacity reports the number of beds or rooms that a program is intended to provide. This is also the capacity measure provided in the previous Daily Shelter Occupancy data set. There are a number of reasons why beds or rooms may be temporarily out of service, including maintenance, repairs, renovations, outbreaks or pest control, so a second capacity measure is also included in the reporting. Actual capacity reports the number of beds or rooms in service and showing as available for occupancy in the Shelter Management Information System at time of reporting. The previous data set reported only funding capacity, but actual capacity is a more effective capacity measure to assess program occupancy rates. Definitions

Here are a few use cases for this project:

1. Pet Adoption Agencies: To streamline the process of pairing dogs with potential adopters based on captured images. For instance, a person's image could help the system suggest dogs that are comfortable around people with certain attributes like age or gender.

2. Training Assistance: Dog trainers or pet shops could use this model to create or augment training modules. By understanding the dog-human interaction through images, they could get insights into the behavior of different breeds and develop better training techniques.

3. Security Applications: This model could be integrated into security systems to differentiate between human and dog movement. The system can then alert homeowners only to human intruders, reducing false alarms triggered by pet movement.

4. Smart Home Automation: In smart homes, based on the identification of the individual (dog or human), the system could adjust the settings accordingly. For instance, if a dog is identified in a specific room, it could adjust the temperature or play certain calming sounds.

5. Animal Shelter Management: The model could help in managing shelters better by identifying dogs and humans, and monitoring their interaction frequency. It could provide data on which dogs are being ignored, ensuring all animals get equal attention.

Individuals who have had a shelter stay since October 2019 (the date which our homeless-serving system started using the newly released HIFIS 4.0). Data is collected by homeless-serving shelters through the Homeless Individuals and Families Information System (HIFIS). It is based on a snapshot of the system at 12 am.