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TwitterResidential real estate transactions saw both a decline as well as an increase during the coronavirus pandemic in 2020, depending on the country. In Denmark, for example, property sales increased by over ***** percent year-on-year in the second quarter of 2020. This was in stark contrast to the United Kingdom, where provisional and non-seasonal data suggested the country saw one of its largest drops in housing transactions since 2009. Some countries, on the other hand, already witnessed a decrease in their transactions before COVID-19 hit Europe. The housing trade inFrance, for example, suffered a large decrease in the first quarter of 2020, right before quarantine measures were enforced. Data for Germany, on the other hand, suggested that its housing market was still growing before the lockdown. Whether this was still the case in 2020 remains to be seen.
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TwitterThe Nursing Home COVID-19 Public File from the Centers for Medicare & Medicaid Services, filtered for Connecticut. View the full dataset and detailed metadata here. The Nursing Home COVID-19 Public File includes data reported by nursing homes to the CDC’s National Healthcare Safety Network (NHSN) system COVID-19 Long Term Care Facility Module, including Resident Impact, Facility Capacity, Staff & Personnel, and Supplies & Personal Protective Equipment, and Ventilator Capacity and Supplies Data Elements.
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TwitterNursing homes with residents positive for COVID-19 from 4/22/2020 to 6/19/2020. Starting in July 2020, this dataset will no longer be updated and will be replaced by the CMS COVID-19 Nursing Home Dataset, available at the following link: https://data.ct.gov/Health-and-Human-Services/CMS-COVID-19-Nursing-Home-Dataset/w8wc-65i5. Methods: 1) Laboratory-confirmed case counts are based upon data reported via the FLIS web portal. Nursing homes were asked to provide cumulative totals of residents with laboratory confirmed covid. This includes residents currently in-house, in the hospital, or who are deceased. Residents were excluded if they tested positive prior to initial admission to the nursing home. 2) The cumulative number of deaths among nursing home residents is based upon data reported by the Office of the Chief Medical Examiner. For public health surveillance, COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death (laboratory-confirmed) and persons whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death (probable). Limitations: 1) As of the week of 5/10/20, Point Prevalence Survey testing is being offered to all asymptomatic nursing home residents to inform infection prevention efforts. Point prevalence surveys will be conducted over a period of several weeks. Some nursing homes had adequate testing resources available to conduct surveys prior to this date. Differences in survey timing will impact the number of positive results that a nursing home reports. 2) Cumulative totals of residents testing positive are being collected rather than individual resident data. Thus we cannot verify the counts, de-duplicate, and/or verify whether there is a record of a positive lab test. This may result in either under- or over-counting. 3) The number of COVID-19 positive residents and the number of confirmed deaths among residents are tabulated from different data sources. Due to the timing of availability of test results for deceased residents, it is not appropriate to calculate the percent of cases who died due to COVID-19 at any particular facility based upon this data. 4) The count of deaths reported for 4/14 are not included in this dataset, as they were not broken out by laboratory-confirmed or probable. They can be viewed in the DPH Report here: https://portal.ct.gov/-/media/Coronavirus/CTDPHCOVID19summary4162020.pdf?la=en
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Twitterhttps://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
This dataset contains records of publicly reported data on COVID-19 testing in Ontario long-term care homes. It was collected between April 24, 2020 and March 30, 2023.
Summary data is aggregated to the provincial level. Reports fewer than 5 are indicated with <5 to maintain the privacy of individuals.
An outbreak is defined as two or more lab-confirmed COVID-19 cases in residents, staff or other visitors in a home, with an epidemiological link, within a 14-day period, where at least one case could have reasonably acquired their infection in the long-term care home. Prior to April 7, 2021, the definition required one or more lab-confirmed COVID-19 cases in a resident or staff in the long-term care home.
Notes
February 21 to March 29, 2023: Data is only available for regular business days (for example, Monday through Friday, except statutory holidays)
March 12 – 13, 2022: Due to technical difficulties, data is not available.
September 8, 2022: The data dated September 6, 2022 represents data collected during the period of September 3, 4 and 5, 2022.
October 6, 2022: The data dated October 5, 2022 represents data collected during the period of October 1, 2, 3 and 4, 2022.
October 13, 2022: Due to technical difficulties, data for the date of October 9 is not available.
October 20, 2022: Due to technical difficulties, data for the dates of October 15, 16 is not available.
November 24, 2022: Due to technical difficulties, data is not available.
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TwitterMany U.S. states have introduced strategies to ensure safe, decent, and stable housing during the COVID-19 pandemic. To better understand the steps states have taken to prevent homelessness, a special policy scorecard for each state was developed. Washington D.C. had the highest score among the states, which amounted to 4.63. On the contrary, Maryland, Georgia, Arkansas, Alaska, Wisconsin, and Ohio received zero points, which indicated that they had introduced no housing policy measures in response to the pandemic, or the protections they brought in have expired.
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TwitterIn a September 2020 survey among adults in the United States, many respondents said that the COVID-19 pandemic did not change their interest in buying a home. Millennials were most likely to have changed their homeownership plans: ** percent of Millennials were more interested in buying a home due to the COVID-19 pandemic compared with **** percent of Baby Boomers.In the United States, the 2020 homeownership rate reached **** percent.
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TwitterIn April 2020, the Sakha (Yakutiya) Republic recorded the most significant price drop in real estate prices in Russia with a roughly five percent price fall per square meter. In the Moscow and Leningrad Regions, the price of residential properties dropped by 3.2 and 3 percentage points per square meter over the given period, respectively.
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TwitterAs of 6/1/2023, this data set is no longer being updated. Connecticut nursing homes are required by the Centers for Medicare and Medicaid Services (CMS) to report on the impact of COVID-19 on their residents and staff through CDC’s National Healthcare Safety Network (NHSN). This reporting is intended to reflect recent COVID-19 activity in nursing homes. Data presented here from NHSN reflect resident and staff COVID-19 cases and COVID-related deaths reported for Connecticut nursing homes for the previous week, Thursday–Wednesday. All nursing homes follow NHSN definitions and instructions when reporting to the NHSN COVID-19 module, ensuring data are reported in a systematic way. These data do not show where the resident or staff got infected. Detailed information about COVID-19 reporting for nursing homes and NHSN can be found here: https://www.cdc.gov/nhsn/ltc/covid19/index.html
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TwitterA. SUMMARY This dataset includes aggregate data on the type, status, population served, and individuals placed at each alternative housing site under contract with HSA. B. HOW THE DATASET IS CREATED Site Type, Status, and Population The HSA DOC leadership inform the data tracker owner when the legal status, site type, or intended population to serve changes. Daily Census and Units Available The site monitors at each site inform the data tracker owner at the HSA DOC at least once daily with the updates to the daily census. C. UPDATE PROCESS Updated several times daily, whenever new information is shared with the data tracker owner. The data tracker owner inputs the data directly into the underlying SharePoint spreadsheet. D. HOW TO USE THIS DATASET Use the data for aggregate data on the site type, status, and daily census of individuals placed in the sites. Do not use this spreadsheet for individual-level information. There is no personally identifying or medical information in this dataset.
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Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.
The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.
It is a weekly snapshot in time that:
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TwitterThis letter notes that agencies should also be prepared to offer youth assistance with food, health care, and emotional support.
Browse All COVID-19 Resources
Metadata-only record linking to the original dataset. Open original dataset below.
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TwitterThe coronavirus (COVID-19) pandemic and the lockdowns during this period had an impact on the attitudes of prospective home buyers in the United Kingdom (UK) in different ways. On one hand, there was a large percentage of prospective home buyers of ** percent that said COVID-19 motivated them to buy homes between ********** and **********.
However, concerns of financial security and the home buying process being harder were also registered at high rates. ** percent of prospective home buyers were worried about their financial security, ** percent reported that lockdowns made it harder to buy homes. This shows that while the motivation and interest in buying homes was large, but the conditions of lockdown and the financial impact of the coronavirus (COVID-19) pandemic were a big barrier towards making purchases.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The data in this paper are divided into two main sections, which are data on the housing market and data on epidemic case information. The time span of the data sample is from December 1, 2019 to April 26, 2020.The original data of the housing market aspect such as the second-hand house price index in Wuhan and the surrounding provincial capital cities were obtained from Chain Home and Baidu Maps. Among them, there are 53,541 valid records of residential transactions in second-hand neighborhoods, with a final total of 347,720 after data cleaning (5582 in Wuhan; 5710 in Hefei; 7988 in Xi'an; 2066 in Changsha; 5910 in Zhengzhou; and 7464 in Chongqing).
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TwitterAlmost two years after the start of the coronavirus (COVID-19) pandemic, the occupancy rate of rental properties around college campuses in the United States has not fully recovered. In the period between 2014 and 2019, the average occupancy rate for properties within *** mile reach of the campus was close to ** percent, while in 2020 and 2021, it was about ** percent. For properties further away from the campus, the occupancy rate was even lower.
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License information was derived automatically
Additional file 1.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Relative risk of county Covid-19 mortality as of April 21, 2020 related to percent households with poor housing conditions.
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Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.
The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.
It is a weekly snapshot in time that:
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TwitterIn this Economic Commentary , we compare characteristics of the 2000–2006 house-price boom that preceded the Great Recession to the house-price boom that began in 2020 during the COVID-19 pandemic. These two episodes of high house-price growth have important differences, including the behavior of rental rates, the dynamics of housing supply and demand, and the state of the mortgage market. The absence of changes in fundamentals during the 2000s is consistent with the literature emphasizing house-price beliefs during this prior episode. In contrast to during the 2000s boom, changes in fundamentals (including rent and demand growth) played a more dominant role in the 2020s house-price boom.
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Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.
The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.
It is a weekly snapshot in time that:
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TwitterIn May 2020, ** percent of U.S. realtors said that home sellers have made changes due to the COVID-19 pandemic. For instance, ** percent of realtors reported that home sellers actually stopped opening their houses. Only ***** percent of home sellers obtained home inspection before listing home for sale.
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TwitterResidential real estate transactions saw both a decline as well as an increase during the coronavirus pandemic in 2020, depending on the country. In Denmark, for example, property sales increased by over ***** percent year-on-year in the second quarter of 2020. This was in stark contrast to the United Kingdom, where provisional and non-seasonal data suggested the country saw one of its largest drops in housing transactions since 2009. Some countries, on the other hand, already witnessed a decrease in their transactions before COVID-19 hit Europe. The housing trade inFrance, for example, suffered a large decrease in the first quarter of 2020, right before quarantine measures were enforced. Data for Germany, on the other hand, suggested that its housing market was still growing before the lockdown. Whether this was still the case in 2020 remains to be seen.