This dashboard displays a daily report on COVID-19 cases for inmates tested within the Massachusetts Department of Correction custody population.
DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2
As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.
With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).
This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity).
A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.
These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.
These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020.
Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
This dataset is no longer being updated as of 6/30/2022. It is being retained on the Open Data Portal for its potential historical interest.
In November 2020, the City of Cambridge began collecting and analyzing COVID-19 data from municipal wastewater, which can serve as an early indicator of increased COVID-19 infections in the city. The Cambridge Public Health Department and Cambridge Department of Public Works are using technology developed by Biobot, a Cambridge based company, and partnering with the Massachusetts Water Resources Authority (MWRA). This Cambridge wastewater surveillance initiative is funded through a $175,000 appropriation from the Cambridge City Council.
This dataset indicates the presence of the COVID-19 virus (measured as viral RNA particles from the novel coronavirus per ml) in municipal wastewater. The Cambridge site data here were collected as a 24-hour composite sample, which is taken weekly. The MWRA site data ere were collected as a 24-hour composite sample, which is taken daily. MWRA and Cambridge data are listed here in a single table.
An interactive graph of this data is available here: https://cityofcambridge.shinyapps.io/COVID19/?tab=wastewater
All areas within the City of Cambridge are captured across four separate catchment areas (or sewersheds) as indicated on the map viewable here: https://cityofcambridge.shinyapps.io/COVID19/_w_484790f7/BioBot_Sites.png. The North and West Cambridge sample also includes nearly all of Belmont and very small areas of Arlington and Somerville (light yellow). The remaining collection sites are entirely -- or almost entirely -- drawn from Cambridge households and workplaces.
Data are corrected for wastewater flow rate, which adjusts for population in general. Data listed are expected to reflect the burden of COVID-19 infections within each of the four sewersheds. A lag of approximately 4-7 days will occur before new transmissions captured in wastewater data would result in a positive PCR test for COVID-19, the most common testing method used. While this wastewater surveillance tool can provide an early indication of major changes in transmission within the community, it remains an emerging technology. In assessing community transmission, wastewater surveillance data should only be considered in conjunction with other clinical measures, such as current infection rates and test positivity.
Each location is selected because it reflects input from a distinct catchment area (or sewershed) as identified on the color-coded map. Viral data collected from small catchment areas like these four Cambridge sites are more variable than data collected from central collection points (e.g., the MWRA facility on Deer Island) where wastewater from dozens of communities are joined and mixed. Data from each catchment area will be impacted by daily activity among individuals living in that area (e.g., working from home vs. traveling to work) and by daytime activities that are not from residences (businesses, schools, etc.) As such, the Regional MWRA data provides a more stable measure of regional viral counts. COVID wastewater data for Boston North and Boston South regions is available at https://www.mwra.com/biobot/biobotdata.htm
View dashboards that show data on COVID-19 incidences among staff and patients in state facilities and congregate care sites, and mobile testing results. Published by the Executive Office of Health and Human Services (EOHHS).
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.
This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.
The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.
Using these data, the COVID-19 community level was classified as low, medium, or high.
COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.
For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.
Archived Data Notes:
This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.
March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.
March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.
March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.
March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.
March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).
March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.
April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.
April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.
May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.
May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.
May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.
June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.
June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.
June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.
July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.
July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.
July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.
July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.
July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.
August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.
August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.
August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.
August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.
August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.
August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.
August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.
September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.
September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States SB: MA: NF: Availability of COVID-19 Tests for Employees data was reported at 2.700 % in 21 Feb 2022. This records a decrease from the previous number of 2.900 % for 14 Feb 2022. United States SB: MA: NF: Availability of COVID-19 Tests for Employees data is updated weekly, averaging 2.800 % from Feb 2022 (Median) to 21 Feb 2022, with 2 observations. The data reached an all-time high of 2.900 % in 14 Feb 2022 and a record low of 2.700 % in 21 Feb 2022. United States SB: MA: NF: Availability of COVID-19 Tests for Employees data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S039: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).
The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.
Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.
We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.
The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.
The following dashboards provide data on contagious respiratory viruses, including acute respiratory diseases, COVID-19, influenza (flu), and respiratory syncytial virus (RSV) in Massachusetts. The data presented here can help track trends in respiratory disease and vaccination activity across Massachusetts.
The participating towns in this effort included Grafton, Holden, Leicester, Millbury, Shrewsbury, West Boylston, and the City of Worcester. This file is no longer updated and is categorized as a legacy dataset. Serology vs Antibody testing: Serology testing looks for the presence of COVID-19 antibodies in the bloodstream which means the person has been exposed to the virus about 2 weeks or more before the test.Date fields: Date fields are displayed in the table with data type string. The string data type is typically used to represent text. All date information is accurate but will sort as text in the online table. Use the download feature if you would like to sort by date.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Logistic regression analysis testing the association of inflammatory makers and outcomes among patients with COVID-19.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Geostatistics analyzes and predicts the values associated with spatial or spatial-temporal phenomena. It incorporates the spatial (and in some cases temporal) coordinates of the data within the analyses. It is a practical means of describing spatial patterns and interpolating values for locations where samples were not taken (and measures the uncertainty of those values, which is critical to informed decision making). This archive contains results of geostatistical analysis of COVID-19 case counts for all available US counties. Test results were obtained with ArcGIS Pro (ESRI). Sources are state health departments, which are scraped and aggregated by the Johns Hopkins Coronavirus Resource Center and then pre-processed by MappingSupport.com.
This update of the Zenodo dataset (version 6) consists of three compressed archives containing geostatistical analyses of SARS-CoV-2 testing data. This dataset utilizes many of the geostatistical techniques used in previous versions of this Zenodo archive, but has been significantly expanded to include analyses of up-to-date U.S. COVID-19 case data (from March 24th to September 8th, 2020):
Archive #1: “1.Geostat. Space-Time analysis of SARS-CoV-2 in the US (Mar24-Sept6).zip” – results of a geostatistical analysis of COVID-19 cases incorporating spatially-weighted hotspots that are conserved over one-week timespans. Results are reported starting from when U.S. COVID-19 case data first became available (March 24th, 2020) for 25 consecutive 1-week intervals (March 24th through to September 6th, 2020). Hotspots, where found, are reported in each individual state, rather than the entire continental United States.
Archive #2: "2.Geostat. Spatial analysis of SARS-CoV-2 in the US (Mar24-Sept8).zip" – the results from geostatistical spatial analyses only of corrected COVID-19 case data for the continental United States, spanning the period from March 24th through September 8th, 2020. The geostatistical techniques utilized in this archive includes ‘Hot Spot’ analysis and ‘Cluster and Outlier’ analysis.
Archive #3: "3.Kriging and Densification of SARS-CoV-2 in LA and MA.zip" – this dataset provides preliminary kriging and densification analysis of COVID-19 case data for certain dates within the U.S. states of Louisiana and Massachusetts.
These archives consist of map files (as both static images and as animations) and data files (including text files which contain the underlying data of said map files [where applicable]) which were generated when performing the following Geostatistical analyses: Hot Spot analysis (Getis-Ord Gi*) [‘Archive #1’: consecutive weeklong Space-Time Hot Spot analysis; ‘Archive #2’: daily Hot Spot Analysis], Cluster and Outlier analysis (Anselin Local Moran's I) [‘Archive #2’], Spatial Autocorrelation (Global Moran's I) [‘Archive #2’], and point-to-point comparisons with Kriging and Densification analysis [‘Archive #3’].
The Word document provided ("Description-of-Archive.Updated-Geostatistical-Analysis-of-SARS-CoV-2 (version 6).docx") details the contents of each file and folder within these three archives and gives general interpretations of these results.
The Executive Order is relative to requiring all city employees be fully vaccination against the COVID-19 virus or submit to weekly COVID-19 testing. More information: Visit the City Manager's webpage to learn more about the current City Manager and their goals, programs, and initiatives.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Objectives: Patients with comorbidities are at increased risk for poor outcomes in COVID-19, yet data on patients with prior neurological disease remains limited. Our objective was to determine the odds of critical illness and duration of mechanical ventilation in patients with prior cerebrovascular disease and COVID-19.Methods: A observational study of 1,128 consecutive adult patients admitted to an academic center in Boston, Massachusetts, and diagnosed with laboratory-confirmed COVID-19. We tested the association between prior cerebrovascular disease and critical illness, defined as mechanical ventilation (MV) or death by day 28, using logistic regression with inverse probability weighting of the propensity score. Among intubated patients, we estimated the cumulative incidence of successful extubation without death over 45 days using competing risk analysis.Results: Of the 1,128 adults with COVID-19, 350 (36%) were critically ill by day 28. The median age of patients was 59 years (SD: 18 years) and 640 (57%) were men. As of June 2nd, 2020, 127 (11%) patients had died. A total of 177 patients (16%) had a prior cerebrovascular disease. Prior cerebrovascular disease was significantly associated with critical illness (OR = 1.54, 95% CI = 1.14–2.07), lower rate of successful extubation (cause-specific HR = 0.57, 95% CI = 0.33–0.98), and increased duration of intubation (restricted mean time difference = 4.02 days, 95% CI = 0.34–10.92) compared to patients without cerebrovascular disease.Interpretation: Prior cerebrovascular disease adversely affects COVID-19 outcomes in hospitalized patients. Further study is required to determine if this subpopulation requires closer monitoring for disease progression during COVID-19.
The participating towns in this effort included Grafton, Holden, Leicester, Millbury, Shrewsbury, West Boylston, and the City of Worcester. This file is no longer updated and is categorized as a legacy dataset.Serology vs Antibody testing: Serology testing looks for the presence of COVID-19 antibodies in the bloodstream which means the person has been exposed to the virus about 2 weeks or more before the test.Date fields:Date fields are displayed in the table with data type string. The string data type is typically used to represent text. All date information is accurate but will sort as text in the online table. Use the download feature if you would like to sort by date.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.
The participating towns in this effort included Grafton, Holden, Leicester, Millbury, Shrewsbury, West Boylston, and the City of Worcester. This file is no longer updated and is categorized as a legacy dataset.Serology vs Antibody testing: Serology testing looks for the presence of COVID-19 antibodies in the bloodstream which means the person has been exposed to the virus about 2 weeks or more before the test.Date fields: Date fields are displayed in the table with data type string. The string data type is typically used to represent text. All date information is accurate but will sort as text in the online table. Use the download feature if you would like to sort by date.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Resource utilization and outcomes of 858 patients hospitalized primarily for COVID-19 using clinician decision, identified by the CDC algorithm or Massachusetts method.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
This dashboard displays a daily report on COVID-19 cases for inmates tested within the Massachusetts Department of Correction custody population.