This layer serves as an inventory of hospitals and other healthcare facilities within Stark County, Ohio. It is part of the Stark County Community Features umbrella of layers, which includes CommunityFeatures, LiveWorkLocate, and EmergencyResponseFacilities. These layers depict places of interest throughout the county, including Airfields and Helipads, Colleges and Universities, Corporate Headquarters, EMS Facilities, Event Venues, Fire Stations, Golf Courses, Hospitals and Health Clinics, Museums and Historic Landmarks, Parks and Recreation Areas, Places of Worship, Police Stations, Public Libraries, Retail Centers, Schools and Daycares, and Senior Citizen Centers. These "community features" were first inventoried and digitized by the Stark County Regional Planning Commission (RPC) in 2008. The initial inventory was a collaborative effort between RPC and each community within the county, who provided lists of their respective features. Since then, each layer is periodically updated by RPC and Stark County GIS.

This layer serves as an inventory of emergency medical services (EMS) facilities within Stark County, Ohio. It is part of the Stark County Community Features umbrella of layers, which includes CommunityFeatures, LiveWorkLocate, and EmergencyResponseFacilities. These layers depict places of interest throughout the county, including Airfields and Helipads, Colleges and Universities, Corporate Headquarters, EMS Facilities, Event Venues, Fire Stations, Golf Courses, Hospitals and Health Clinics, Museums and Historic Landmarks, Parks and Recreation Areas, Places of Worship, Police Stations, Post Offices, Public Libraries, Retail Centers, Schools and Daycares, and Senior Citizen Centers. These "community features" were first inventoried and digitized by the Stark County Regional Planning Commission (RPC) in 2008. The initial inventory was a collaborative effort between RPC and each community within the county, who provided lists of their respective features. Since then, each layer is periodically updated by RPC and Stark County GIS.

Updates

• Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• April 9, 2020

  • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.

• April 20, 2020

  • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.

• April 29, 2020

  • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.

• September 1st, 2020

  • Johns Hopkins is now providing counts for the five New York City counties individually.

• February 12, 2021

  • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
  • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.

• February 16, 2021

  - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

  Overview

The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

The AP is updating this dataset hourly at 45 minutes past the hour.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Queries

Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

Interactive

The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

@(https://datawrapper.dwcdn.net/nRyaf/15/)

Interactive Embed Code

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Caveats

• This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
• In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
• In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
• This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
• Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
• Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
• The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

Attribution

This data should be credited to Johns Hopkins University COVID-19 tracking project

This layer serves as an inventory of senior citizen centers within Stark County, Ohio. It is part of the Stark County Community Features umbrella of layers, which includes CommunityFeatures, LiveWorkLocate, and EmergencyResponseFacilities. These layers depict places of interest throughout the county, including Airfields and Helipads, Colleges and Universities, Corporate Headquarters, EMS Facilities, Event Venues, Fire Stations, Golf Courses, Hospitals and Health Clinics, Museums and Historic Landmarks, Parks and Recreation Areas, Places of Worship, Police Stations, Post Offices, Public Libraries, Retail Centers, Schools and Daycares, and Senior Citizen Centers. These "community features" were first inventoried and digitized by the Stark County Regional Planning Commission (RPC) in 2008. The initial inventory was a collaborative effort between RPC and each community within the county, who provided lists of their respective features. Since then, each layer is periodically updated by RPC and Stark County GIS.

This layer serves as an inventory of parks and other recreation areas within Stark County, Ohio. It is part of the Stark County Community Features umbrella of layers, which includes CommunityFeatures, LiveWorkLocate, and EmergencyResponseFacilities. These layers depict places of interest throughout the county, including Airfields and Helipads, Colleges and Universities, Corporate Headquarters, EMS Facilities, Event Venues, Fire Stations, Golf Courses, Hospitals and Health Clinics, Museums and Historic Landmarks, Parks and Recreation Areas, Places of Worship, Police Stations, Post Offices, Public Libraries, Retail Centers, Schools and Daycares, and Senior Citizen Centers. These "community features" were first inventoried and digitized by the Stark County Regional Planning Commission (RPC) in 2008. The initial inventory was a collaborative effort between RPC and each community within the county, who provided lists of their respective features. Since then, each layer is periodically updated by RPC and Stark County GIS.

Introduction: Multiple risk factors of mortality have been identified in patients with COVID-19. Here, we sought to determine the effect of a history of neurological disorder and development of neurological manifestations on mortality in hospitalized patients with COVID-19.Methods: From March 20 to May 20, 2020, hospitalized patients with laboratory confirmed or highly suspected COVID-19 were identified at four hospitals in Ohio. Previous history of neurological disease was classified by severity (major or minor). Neurological manifestations during disease course were also grouped into major and minor manifestations. Encephalopathy, ischemic or hemorrhagic stroke, and seizures were defined as major manifestations, whereas minor neurological manifestations included headache, anosmia, dysgeusia, dizziness or vertigo, and myalgias. Multivariate logistic regression models were used to determine significant predictors of mortality in patients with COVID-19 infection.Results: 574/626 hospitalized patients were eligible for inclusion. Mean age of the 574 patients included in the analysis was 62.8 (SD 17.6), with 298 (51.9%) women. Of the cohort, 240(41.8%) patients had a prior history of neurological disease (HND), of which 204 (35.5%) had a major history of neurological disease (HND). Mortality rates were higher in patients with a major HND (30.9 vs. 15.4%; p = 0.00002), although this was not a significant predictor of death. Major neurological manifestations were recorded in 203/574 (35.4%) patients during disease course. The mortality rate in patients who had major neurological manifestations was 37.4% compared to 11.9% (p = 2 × 10−12) in those who did not. In multivariate analysis, major neurological manifestation (OR 2.1, CI 1.3-3.4; p = 0.002) was a predictor of death.Conclusions: In this retrospective study, history of pre-existing neurological disease in hospitalized COVID-19 patients did not impact mortality; however, development of major neurological manifestations during disease course was found to be an independent predictor of death. Larger studies are needed to validate our findings.