One of the most persistent falsehoods of the COVID pandemic has been the claim that Florida has been “hiding” data. This idea has been advanced primarily by Rebekah Jones, a former Florida Department of Health employee, who, having at first expressed only some modest political disagreements with the way in which Florida responded to COVID, has over time become a fountain of misinformation.
To understand what is happening here, one needs to go back to the beginning. Over the past 15 months, Florida has published a truly remarkable amount of COVID-related data. At the heart of this trove has been a well-maintained list of literally every documented case of COVID — listed by county, age, and gender, and replete with information about whether the patient had recently traveled, had visited the ER, had been hospitalized, and had had any known contact with other Floridians. To my knowledge, Florida has been the only state in the union that has published this kind of data.
To this day, you can download Florida’s case-line data and see 21 cases of COVID that, despite having been identified between March 2020 and December 2020, feature a December 2019 “Event Date.” To anyone who understands data, these results are clearly the product of the system having assigned a non-null default value when no data has been entered. To the Miami Herald, however, these results hinted at scandal. Even now, when its reporters know beyond any doubt that their initial instincts were wrong, the Herald continues to tell its readers that these entries serve as “evidence of community spread potentially months earlier than previously reported.” This is not true.
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. For a list of Frequently Asked Questions, please click here. For a full list of variables included in this Public Use File (PUF) and their descriptions, please see the data dictionary. The file contains an individual record for each certified Medicare skilled nursing facility/Medicaid nursing facility and the ending date for each collection week, and is updated weekly. More information on CMS requirements for reporting COVID-19 information can be found here. We note that the presence of cases of COVID-19 in a nursing home does not automatically indicate noncompliance with federal requirements. This information is used to assist with national surveillance of COVID-19 in nursing homes, and support actions to protect the health and safety of nursing home residents.
In a major victory for America’s counties, the State and Local Coronavirus Fiscal Recovery Funds legislation, part of the American Rescue Plan Act was passed by the U.S. Senate on March 6. The bill, which now heads back to the U.S. House of Representatives for final consideration, includes $65.1 billion in direct, flexible aid to every county in America, as well as other crucial investments in local communities.
The Senate version amends the House-adopted bill in several important ways:
The U.S. Department of Treasury would still oversee and administer these payments to state and local governments, and every county would be eligible to receive a direct allocation from Treasury. States, municipalities, and counties would now receive funds in two tranches – both tranches would provide 50 percent of the entity’s total allocation. In cases where a state has a very high level of unemployed individuals, these states may receive both tranches at the same time.
In order to receive a payment either under the first or second tranche, local governments must provide the U.S. Treasury with a certification signed by an authorized officer. The U.S. Treasury is required to pay first tranche to counties not later than 60-days after enactment, and second payment no earlier than 12 months after the first payment.
Our tracker uses data from a number of statistical bureaus, government departments and academic projects. For many of the countries, we have imported total_deaths from the Human Mortality Database, which collates detailed weekly breakdowns from official sources around the world. For other countries, you can find a full list of sources and links in a file called list_of_sources.csv, as well as spreadsheets in the /source-data/ folder.
The Supplement is a major resource for data on programs administered by the Social Security Administration—the Old-Age, Survivors, and Disability Insurance program, known collectively as Social Security, and the Supplemental Security Income program. The Supplement also includes program summaries and legislative histories that help users of the data understand these programs. Please note that additional disability tables and statistics can be found in the SSI Annual Statistical Report and the Annual Statistical Report on the Social Security Disability Insurance Program.
The Supplement has been published annually since 1940. Decisions affecting the future of Social Security are facilitated by the availability of relevant data over a long period. The data provide a base for research, policy analysis, and proposals for changing the programs. In addition to meeting the Social Security Administration’s information needs, the Supplement strengthens the agency’s ability to respond to requests for program data from congressional committees, government agencies at all levels, and the research community.
The Supplement is prepared by Social Security Administration staff from various components throughout the agency. I would like to express my thanks to them for their contributions.
Katherine N. Bent Acting Associate Commissioner for Research, Evaluation, and Statistics February 2021
We’re keeping this page up to date with systemwide ridership and traffic estimates for subways, buses, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, and Bridges and Tunnels. You can see changes over the past seven days, as well as get a sense of how ridership and traffic differs this year versus last year. We will generally update the page on weekdays, excluding holidays, with the prior day’s figures. At times, data issues may delay the updates.
The release came six months after the FOIL request was submitted, five months after we and the Government Justice Center filed suit, and one week after a court found that the department had violated FOIL and ordered it to release what were clearly public records.
The Yu Group at UC Berkeley Statistics / EECS / CCB is working to help forecast the severity of the epidemic for individual counties and hospitals in the US. We develop interpretable models (updated daily) and curate data to predict the trajectory of COVID-19-related deaths. This website provides access to those predictions, in the form of interactive visualizations. We are collaborating with Response4Life to blunt the effect of COVID-19 through the production and appropriate distribution of PPE, medical equipment, and medical personnel to healthcare facilities across the United States.
For hospital level prediction, please go to our hospitalization prediction page where one can upload data for a specific hospital and download prediction results for the given hospital. The uploaded data will only be temporarily used for prediction and will not be collected.GITHUB