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TwitterNOTE: This dataset has been retired and marked as historical-only.
This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.
All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.
Only Chicago residents are included based on the home address as provided by the medical provider.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey
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TwitterNOTE: This dataset has been retired and marked as historical-only.
Only Chicago residents are included based on the home ZIP Code, as provided by the medical provider, or the address, as provided by the Cook County Medical Examiner.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted on the date the test specimen was collected. Deaths are those occurring among cases based on the day of death. Hospitalizations are based on the date of first hospitalization. Only one hospitalization is counted for each case. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Because of the nature of data reporting to CDPH, hospitalizations will be blank for recent dates They will fill in on later updates when the data are received, although, as for cases and deaths, may continue to be updated as further data are received.
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases, deaths, and hospitalizations, sources used, how cases, deaths and hospitalizations are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office
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TwitterCOVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.
Where are these numbers coming from?
The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.
A word on the flaws of numbers like this
People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.
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BackgroundMost existing prognostic models of COVID-19 require imaging manifestations and laboratory results as predictors, which are only available in the post-hospitalization period. Therefore, we aimed to develop and validate a prognostic model to assess the in-hospital death risk in COVID-19 patients using routinely available predictors at hospital admission.MethodsWe conducted a retrospective cohort study of patients with COVID-19 using the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Patients hospitalized in Eastern United States (Florida, Michigan, Kentucky, and Maryland) were included in the training set, and those hospitalized in Western United States (Nevada) were included in the validation set. Discrimination, calibration, and clinical utility were evaluated to assess the model's performance.ResultsA total of 17 954 in-hospital deaths occurred in the training set (n = 168 137), and 1,352 in-hospital deaths occurred in the validation set (n = 12 577). The final prediction model included 15 variables readily available at hospital admission, including age, sex, and 13 comorbidities. This prediction model showed moderate discrimination with an area under the curve (AUC) of 0.726 (95% confidence interval [CI]: 0.722—0.729) and good calibration (Brier score = 0.090, slope = 1, intercept = 0) in the training set; a similar predictive ability was observed in the validation set.ConclusionAn easy-to-use prognostic model based on predictors readily available at hospital admission was developed and validated for the early identification of COVID-19 patients with a high risk of in-hospital death. This model can be a clinical decision-support tool to triage patients and optimize resource allocation.
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TwitterAn in depth study on patients admitted to hospital and later deceased with the coronavirus (COVID-19) infection revealed that the majority of cases showed one or more comorbidities. About 67.8 percent of reported deceased COVID-19 patients suffered from three or more pre-existing health conditions, and 17.9 percent from two conditions. Only in 2.9 percent of COVID-19 deaths no prior health conditions were recorded. More statistics and facts about the virus in Italy are available here. For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
NOTE: This dataset has been retired and marked as historical-only.
Weekly rates of COVID-19 cases, hospitalizations, and deaths among people living in Chicago by vaccination status and age.
Rates for fully vaccinated and unvaccinated begin the week ending April 3, 2021 when COVID-19 vaccines became widely available in Chicago. Rates for boosted begin the week ending October 23, 2021 after booster shots were recommended by the Centers for Disease Control and Prevention (CDC) for adults 65+ years old and adults in certain populations and high risk occupational and institutional settings who received Pfizer or Moderna for their primary series or anyone who received the Johnson & Johnson vaccine.
Chicago residency is based on home address, as reported in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE) and Illinois National Electronic Disease Surveillance System (I-NEDSS).
Outcomes: • Cases: People with a positive molecular (PCR) or antigen COVID-19 test result from an FDA-authorized COVID-19 test that was reported into I-NEDSS. A person can become re-infected with SARS-CoV-2 over time and so may be counted more than once in this dataset. Cases are counted by week the test specimen was collected. • Hospitalizations: COVID-19 cases who are hospitalized due to a documented COVID-19 related illness or who are admitted for any reason within 14 days of a positive SARS-CoV-2 test. Hospitalizations are counted by week of hospital admission. • Deaths: COVID-19 cases who died from COVID-19-related health complications as determined by vital records or a public health investigation. Deaths are counted by week of death.
Vaccination status: • Fully vaccinated: Completion of primary series of a U.S. Food and Drug Administration (FDA)-authorized or approved COVID-19 vaccine at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Boosted: Fully vaccinated with an additional or booster dose of any FDA-authorized or approved COVID-19 vaccine received at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Unvaccinated: No evidence of having received a dose of an FDA-authorized or approved vaccine prior to a positive test.
CLARIFYING NOTE: Those who started but did not complete all recommended doses of an FDA-authorized or approved vaccine prior to a positive test (i.e., partially vaccinated) are excluded from this dataset.
Incidence rates for fully vaccinated but not boosted people (Vaccinated columns) are calculated as total fully vaccinated but not boosted with outcome divided by cumulative fully vaccinated but not boosted at the end of each week. Incidence rates for boosted (Boosted columns) are calculated as total boosted with outcome divided by cumulative boosted at the end of each week. Incidence rates for unvaccinated (Unvaccinated columns) are calculated as total unvaccinated with outcome divided by total population minus cumulative boosted, fully, and partially vaccinated at the end of each week. All rates are multiplied by 100,000.
Incidence rate ratios (IRRs) are calculated by dividing the weekly incidence rates among unvaccinated people by those among fully vaccinated but not boosted and boosted people.
Overall age-adjusted incidence rates and IRRs are standardized using the 2000 U.S. Census standard population.
Population totals are from U.S. Census Bureau American Community Survey 1-year estimates for 2019.
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. This dataset reflects data known to CDPH at the time when the dataset is updated each week.
Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.
For all datasets related to COVID-19, see https://data.cityofchic
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Daily official UK Covid data. The data is available per country (England, Scotland, Wales and Northern Ireland) and for different regions in England. The different regions are split into two different files as part of the data is directly gathered by the NHS (National Health Service). The files that contain the word 'nhsregion' in their name, include data related to hospitals only, such as number of admissions or number of people in respirators. The files containing the word 'region' in their name, include the rest of the data, such as number of cases, number of vaccinated people or number of tests performed per day. The next paragraphs describe the columns for the different file types.
Files related to regions (word 'region' included in the file name) have the following columns: - "date": date in YYYY-MM-DD format - "area type": type of area covered in the file (region or nation) - "area name": name of area covered in the file (region or nation name) - "daily cases": new cases on a given date - "cum cases": cumulative cases - "new deaths 28days": new deaths within 28 days of a positive test - "cum deaths 28days": cumulative deaths within 28 days of a positive test - "new deaths_60days": new deaths within 60 days of a positive test - "cum deaths 60days": cumulative deaths within 60 days of a positive test - "new_first_episode": new first episodes by date - "cum_first_episode": cumulative first episodes by date - "new_reinfections": new reinfections by specimen data - "cum_reinfections": cumualtive reinfections by specimen data - "new_virus_test": new virus tests by date - "cum_virus_test": cumulative virus tests by date - "new_pcr_test": new PCR tests by date - "cum_pcr_test": cumulative PCR tests by date - "new_lfd_test": new LFD tests by date - "cum_lfd_test": cumulative LFD tests by date - "test_roll_pos_pct": percentage of unique case positivity by date rolling sum - "test_roll_people": unique people tested by date rolling sum - "new first dose": new people vaccinated with a first dose - "cum first dose": cumulative people vaccinated with a first dose - "new second dose": new people vaccinated with a first dose - "cum second dose": cumulative people vaccinated with a first dose - "new third dose": new people vaccinated with a booster or third dose - "cum third dose": cumulative people vaccinated with a booster or third dose
Files related to countries (England, Northern Ireland, Scotland and Wales) have the above columns and also: - "new admissions": new admissions, - "cum admissions": cumulative admissions, - "hospital cases": patients in hospitals, - "ventilator beds": COVID occupied mechanical ventilator beds - "trans_rate_min": minimum transmission rate (R) - "trans_rate_max": maximum transmission rate (R) - "trans_growth_min": transmission rate growth min - "trans_growth_max": transmission rate growth max
Files related to nhsregion (word 'nhsregion' included in the file name) have the following columns: - "new admissions": new admissions, - "cum admissions": cumulative admissions, - "hospital cases": patients in hospitals, - "ventilator beds": COVID occupied mechanical ventilator beds - "trans_rate_min": minimum transmission rate (R) - "trans_rate_max": maximum transmission rate (R) - "trans_growth_min": transmission rate growth min - "trans_growth_max": transmission rate growth max
It's worth noting that the dataset hasn't been cleaned and it needs cleaning. Also, different files have different null columns. This isn't an error in the dataset but the way different countries and regions report the data.
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TwitterI was paying close attention to the COVID-19 data reported by Orange County's health department in the beginning months of the pandemic. The website initially offered users the opportunity to download the latest data and had visualizations depicting the number of reported deaths and cases. A few months in, the data and visualizations were removed and the website only offered daily numbers. I was lucky enough to download the latest data the day before this happened and began tracking the numbers manually. The data I've been collecting is now automatically updated twice daily and posted to my website (cwjabrams.com) daily.
The data contains dates, COVID-19 case information, COVID-19 mortality information, and COVID-19 hospital information for Orange County, CA. The time period the data covers ranges from near the beginning of February to early January (updated data can be found at my website)
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TwitterBased on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.
The difficulties of death figures
This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.
Where are these numbers coming from?
The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.
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TwitterNote: On April 30, 2024, the Federal mandate for COVID-19 and influenza associated hospitalization data to be reported to CDC’s National Healthcare Safety Network (NHSN) expired. Hospitalization data beyond April 30, 2024, will not be updated on the Open Data Portal. Hospitalization and ICU admission data collected from summer 2020 to May 10, 2023, are sourced from the California Hospital Association (CHA) Survey. Data collected on or after May 11, 2023, are sourced from CDC's National Healthcare Safety Network (NHSN).
Data is from the California Department of Public Health (CDPH) Respiratory Virus State Dashboard at https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx.
Data are updated each Friday around 2 pm.
For COVID-19 death data: As of January 1, 2023, data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2023–Present. Prior to January 1, 2023, death data was sourced from the COVID-19 case registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023. Influenza death data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2020–Present.
COVID-19 testing data represent data received by CDPH through electronic laboratory reporting of test results for COVID-19 among residents of California. Testing date is the date the test was administered, and tests have a 1-day lag (except for the Los Angeles County, which has an additional 7-day lag). Influenza testing data represent data received by CDPH from clinical sentinel laboratories in California. These laboratories report the aggregate number of laboratory-confirmed influenza virus detections and total tests performed on a weekly basis. These data do not represent all influenza testing occurring in California and are available only at the state level.
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TwitterDetroit-specific ZIP code populations, along with their cumulative COVID case counts, deaths, and rates. Data provided by Detroit Health Department. The public-facing COVID Cases Dashboard is hosted at: detroitmi.gov/healthUPDATE* July 29 2021:The underlying calculation for disease date was updated to allow for individuals to appear on the curve in multiple locations if they experienced more than one case of COVID-19 that was at least 90 days apart.Geospatial information analysis was also improved and additional criterial for address clean up were implemented, which leads to more accurate case counts within Zip Codes. Some unverified addresses that may have appeared in previous Zip Code counts are now excluded.This change discourages direct comparison of dashboard visualizations and counts prior to the new calculation, and non-significant shifts in numbers will be noticed.Case numbers represent Detroit residents only. Some ZIP codes with very low case counts are excluded to protect privacy. Case counts are totals per ZIP code and are not adjusted for population. ZIP code totals are preliminary; addresses are updated as new information becomes available and counts are subject to change. Not all cases have an accurate location; only cases with a known ZIP code are represented. Where a ZIP code is split between cities, only the Detroit portion is shown (48203, 48211, 48212, 48236, 48239). The counts exclude cases among prisoners at the Wayne County Jail and known hospital or laboratory locations.ZIP_Code: The USPS ZIP postal code Clipped_ZIP_Population: The 2010 population of the ZIP code, clipped to include Detroit City residents only.ZIP_Case_Count: The current cumulative count of Confirmed COVID cases within the ZIP code, since the beginning of the pandemic. (Have a "Confimed" case status in MDSS)ZIP_Death_Count: The current cumulative count of Confirmed COVID cases within the ZIP code, since the beginning of the pandemic. (Have a "Confimed" case status in MDSS and are deceased)ZIP_Case_Rate: Rate of confirmed cases per 100 thousand residents in the ZIP code. For each zip, the rate was calculated by (C/P)*100000 C = the count of confirmed (MDSS case status = Confirmed) cases with a resident address in the ZIP code P = the population count of the ZIP codeZIP_Death_Rate: Rate of confirmed cases that were marked deceased, per 100 thousand residents in the ZIP code. For each zip, the rate was calculated by (D/P)*100000 D = the count of confirmed (MDSS case status = Confirmed) cases marked as deceased, with a resident address in the ZIP P = the population count of the ZIP code
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TwitterIntroductionCertain living conditions, such as homelessness, increase health risks in epidemic situations. We conducted a prospective observational cohort study to investigate the impact of the COVID-19 pandemic on morbidity and mortality in adult people who were homeless.MethodsThe study population comprised around 40% of the entire population experiencing homelessness in Marseille. They were enrolled at 48 different locations during the first pandemic wave (June to August 2020) and were followed up 3 and 6 months later. Rapid serological screening for SARS-CoV-2 was performed by community outreach teams at each follow-up, who also conducted interviews. Death registers and hospital administrative databases were consulted.ResultsA total of 1,332 participants [mean age 40.1 years [SD 14.2], women 339 (29.9%)] were enrolled in the cohort. Of these, 192 (14.4%) participants were found positive for COVID-19 and were propensity score matched (1:3) and compared with 553 non-COVID-19 cases. Living in emergency shelters was associated with COVID-19 infection. While 56.3% of the COVID-19-infected cohort reported no symptoms, 25.0% were hospitalized due to the severity of the disease. Presence of three or more pre-existing comorbidities was associated with all-cause hospitalization. Among COVID-19 cases, only older age was associated with COVID-19 hospitalization. Three deaths occurred in the cohort, two of which were among the COVID-19 cases.ConclusionThe study provides new evidence that the population experiencing homelessness faces higher risks of infection and hospitalization due to COVID-19 than the general population. Despite the efforts of public authorities, the health inequities experienced by people who are homeless remained major. More intensive and appropriate integrated care and earlier re-housing are needed.
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TwitterAbstract The world changed in just a few months after the emergence of the novel coronavirus disease 2019 (COVID-19), caused by a beta coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. Brazil currently has the world’s second-highest COVID-19 death toll, second only to the USA. The COVID-19 pandemic is spreading fast in the world with more than 181 countries affected. This editorial refers to the article published in Arquivos Brasileiros de Cardiologia: “Increase in home deaths due to cardiorespiratory arrest in times of COVID-19 pandemic.”1 Their main results show a gradual increase in the rate of out-of-hospital cardiac arrest during the Coronavirus disease 2019 (COVID-19) pandemic in the city of Belo Horizonte, Minas Gerais, Brazil. Their data demonstrate a proportional increase of 33% of home deaths in March 2020 compared to previous periods. Their study is the first Brazilian paper to demonstrate the same trend observed in other countries.
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TwitterNotice 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.
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new_deaths column.February 16, 2021
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.
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.
The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.
@(https://datawrapper.dwcdn.net/nRyaf/15/)
<iframe title="USA counties (2018) choropleth map Mapping COVID-19 cases by county" aria-describedby="" id="datawrapper-chart-nRyaf" src="https://datawrapper.dwcdn.net/nRyaf/10/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important;" height="400"></iframe><script type="text/javascript">(function() {'use strict';window.addEventListener('message', function(event) {if (typeof event.data['datawrapper-height'] !== 'undefined') {for (var chartId in event.data['datawrapper-height']) {var iframe = document.getElementById('datawrapper-chart-' + chartId) || document.querySelector("iframe[src*='" + chartId + "']");if (!iframe) {continue;}iframe.style.height = event.data['datawrapper-height'][chartId] + 'px';}}});})();</script>
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
This data should be credited to Johns Hopkins University COVID-19 tracking project
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TwitterFlorida COVID-19 Cases by County exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/ . https://doi.org/10.5038/USF-COVID-19-GISLive FDOH DataSource: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. Up until 3/25 the FDOH Cases by County layer was updated twice a day, archives are taken from the 11AM update.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results. All PUIs fit into one of three residency types: 1. Florida residents tested in Florida2. Non-Florida residents tested in Florida3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outside of Florida, and were not exposed/infectious in Florida.Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state. Total Cases: The total (sum) number of Persons Under Investigation (PUI) who tested positive for COVID-19 while in Florida, as well as Florida residents who tested positive or were exposed/contagious while outside of Florida, and out-of-state residents who were exposed, contagious and/or tested in Florida.Deaths: The Deaths by Day chart shows the total number of Florida residents with confirmed COVID-19 that died on each calendar day (12:00 AM - 11:59 PM). Caution should be used in interpreting recent trends, as deaths are added as they are reported to the Department. Death data often has significant delays in reporting, so data within the past two weeks will be updated frequently.Prefix guide: "PUI" = PUI: Persons under surveillance (any person for which we have data about)"T_ " = Testing: Testing information for all PUIs and cases."C_" = Cases only: Information about cases, which are those persons who have COVID-19 positive test results on file“W_” = Surveillance and syndromic dataKey Data about Testing:T_negative : Testing: Total negative persons tested for all Florida and non-Florida residents, including Florida residents tested outside of the state, and those tested at private facilities.T_positive : Testing: Total positive persons tested for all Florida and non-Florida resident types, including Florida residents tested outside of the state, and those tested at private facilities.PUILab_Yes : All persons tested with lab results on file, including negative, positive and inconclusive. This total does NOT include those who are waiting to be tested or have submitted tests to labs for which results are still pending.Key Data about Confirmed COVID-19 Positive Cases: CasesAll: Cases only: The sum total of all positive cases, including Florida residents in Florida, Florida residents outside Florida, and non-Florida residents in FloridaFLResDeaths: Deaths of Florida ResidentsC_Hosp_Yes : Cases (confirmed positive) with a hospital admission notedC_AgeRange Cases Only: Age range for all cases, regardless of residency typeC_AgeMedian: Cases Only: Median range for all cases, regardless of residency typeC_AllResTypes : Cases Only: Sum of COVID-19 positive Florida Residents; includes in and out of state Florida residents, but does not include out-of-state residents who were treated/tested/isolated in Florida. All questions regarding this dataset should be directed to the Florida Department of Health.
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This indicator is designed to accompany the SHMI publication. The SHMI includes all deaths reported of patients who were admitted to non-specialist acute trusts in England and either died while in hospital or within 30 days of discharge. Deaths related to COVID-19 are excluded from the SHMI. A contextual indicator on the percentage of deaths reported in the SHMI which occurred in hospital and the percentage which occurred outside of hospital is produced to support the interpretation of the SHMI. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells for England from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for this trust are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) has not submitted data to the Secondary Uses Service (SUS) since June 2022 due to an issue with their patient records system. This is causing a large shortfall in records with data only submitted for 4 months out of the 12 months in the current time period. Values for this trust should be viewed in the context of this issue. 5. A number of trusts are currently engaging in a pilot to submit Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS), rather than the Admitted Patient Care (APC) dataset. As the SHMI is calculated using APC data, this does have the potential to impact on the SHMI value for these trusts. Trusts with SDEC activity removed from the APC data have generally seen an increase in the SHMI value. This is because the observed number of deaths remains approximately the same as the mortality rate for this cohort is very low; secondly, the expected number of deaths decreases because a large number of spells are removed, all of which would have had a small, non-zero risk of mortality contributing to the expected number of deaths. We are working to better understand the planned changes to the recording of SDEC activity and the potential impact on the SHMI. The trusts affected in this publication are: Barts Health NHS Trust (trust code R1H), Cambridge University Hospitals NHS Foundation Trust (trust code RGT), Croydon Health Services NHS Trust (trust code RJ6), Epsom and St Helier University Hospitals NHS Trust (trust code RVR), Frimley Health NHS Foundation Trust (trust code RDU), Imperial College Healthcare NHS Trust (trust code RYJ), Manchester University NHS Foundation Trust (trust code R0A), Norfolk and Norwich University Hospitals NHS Foundation Trust (trust code RM1), and University Hospitals of Derby and Burton NHS Foundation Trust (trust code RTG). 6. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of the publication page.
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TwitterFlorida COVID-19 Cases by County exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/ . https://doi.org/10.5038/USF-COVID-19-GISLive FDOH DataSource: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. Up until 3/25 the FDOH Cases by County layer was updated twice a day, archives are taken from the 11AM update.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results. All PUIs fit into one of three residency types: 1. Florida residents tested in Florida2. Non-Florida residents tested in Florida3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outside of Florida, and were not exposed/infectious in Florida.Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state. Total Cases: The total (sum) number of Persons Under Investigation (PUI) who tested positive for COVID-19 while in Florida, as well as Florida residents who tested positive or were exposed/contagious while outside of Florida, and out-of-state residents who were exposed, contagious and/or tested in Florida.Deaths: The Deaths by Day chart shows the total number of Florida residents with confirmed COVID-19 that died on each calendar day (12:00 AM - 11:59 PM). Caution should be used in interpreting recent trends, as deaths are added as they are reported to the Department. Death data often has significant delays in reporting, so data within the past two weeks will be updated frequently.Prefix guide: "PUI" = PUI: Persons under surveillance (any person for which we have data about)"T_ " = Testing: Testing information for all PUIs and cases."C_" = Cases only: Information about cases, which are those persons who have COVID-19 positive test results on file“W_” = Surveillance and syndromic dataKey Data about Testing:T_negative : Testing: Total negative persons tested for all Florida and non-Florida residents, including Florida residents tested outside of the state, and those tested at private facilities.T_positive : Testing: Total positive persons tested for all Florida and non-Florida resident types, including Florida residents tested outside of the state, and those tested at private facilities.PUILab_Yes : All persons tested with lab results on file, including negative, positive and inconclusive. This total does NOT include those who are waiting to be tested or have submitted tests to labs for which results are still pending.Key Data about Confirmed COVID-19 Positive Cases: CasesAll: Cases only: The sum total of all positive cases, including Florida residents in Florida, Florida residents outside Florida, and non-Florida residents in FloridaFLResDeaths: Deaths of Florida ResidentsC_Hosp_Yes : Cases (confirmed positive) with a hospital admission notedC_AgeRange Cases Only: Age range for all cases, regardless of residency typeC_AgeMedian: Cases Only: Median range for all cases, regardless of residency typeC_AllResTypes : Cases Only: Sum of COVID-19 positive Florida Residents; includes in and out of state Florida residents, but does not include out-of-state residents who were treated/tested/isolated in Florida. All questions regarding this dataset should be directed to the Florida Department of Health.
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TwitterFlorida COVID-19 Cases by County exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/ . https://doi.org/10.5038/USF-COVID-19-GISLive FDOH DataSource: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. Up until 3/25 the FDOH Cases by County layer was updated twice a day, archives are taken from the 11AM update.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results. All PUIs fit into one of three residency types: 1. Florida residents tested in Florida2. Non-Florida residents tested in Florida3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outside of Florida, and were not exposed/infectious in Florida.Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state. Total Cases: The total (sum) number of Persons Under Investigation (PUI) who tested positive for COVID-19 while in Florida, as well as Florida residents who tested positive or were exposed/contagious while outside of Florida, and out-of-state residents who were exposed, contagious and/or tested in Florida.Deaths: The Deaths by Day chart shows the total number of Florida residents with confirmed COVID-19 that died on each calendar day (12:00 AM - 11:59 PM). Caution should be used in interpreting recent trends, as deaths are added as they are reported to the Department. Death data often has significant delays in reporting, so data within the past two weeks will be updated frequently.Prefix guide: "PUI" = PUI: Persons under surveillance (any person for which we have data about)"T_ " = Testing: Testing information for all PUIs and cases."C_" = Cases only: Information about cases, which are those persons who have COVID-19 positive test results on file“W_” = Surveillance and syndromic dataKey Data about Testing:T_negative : Testing: Total negative persons tested for all Florida and non-Florida residents, including Florida residents tested outside of the state, and those tested at private facilities.T_positive : Testing: Total positive persons tested for all Florida and non-Florida resident types, including Florida residents tested outside of the state, and those tested at private facilities.PUILab_Yes : All persons tested with lab results on file, including negative, positive and inconclusive. This total does NOT include those who are waiting to be tested or have submitted tests to labs for which results are still pending.Key Data about Confirmed COVID-19 Positive Cases: CasesAll: Cases only: The sum total of all positive cases, including Florida residents in Florida, Florida residents outside Florida, and non-Florida residents in FloridaFLResDeaths: Deaths of Florida ResidentsC_Hosp_Yes : Cases (confirmed positive) with a hospital admission notedC_AgeRange Cases Only: Age range for all cases, regardless of residency typeC_AgeMedian: Cases Only: Median range for all cases, regardless of residency typeC_AllResTypes : Cases Only: Sum of COVID-19 positive Florida Residents; includes in and out of state Florida residents, but does not include out-of-state residents who were treated/tested/isolated in Florida. All questions regarding this dataset should be directed to the Florida Department of Health.
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TwitterFlorida COVID-19 Cases by County exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/ . https://doi.org/10.5038/USF-COVID-19-GISLive FDOH DataSource: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. Up until 3/25 the FDOH Cases by County layer was updated twice a day, archives are taken from the 11AM update.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results. All PUIs fit into one of three residency types: 1. Florida residents tested in Florida2. Non-Florida residents tested in Florida3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outside of Florida, and were not exposed/infectious in Florida.Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state. Total Cases: The total (sum) number of Persons Under Investigation (PUI) who tested positive for COVID-19 while in Florida, as well as Florida residents who tested positive or were exposed/contagious while outside of Florida, and out-of-state residents who were exposed, contagious and/or tested in Florida.Deaths: The Deaths by Day chart shows the total number of Florida residents with confirmed COVID-19 that died on each calendar day (12:00 AM - 11:59 PM). Caution should be used in interpreting recent trends, as deaths are added as they are reported to the Department. Death data often has significant delays in reporting, so data within the past two weeks will be updated frequently.Prefix guide: "PUI" = PUI: Persons under surveillance (any person for which we have data about)"T_ " = Testing: Testing information for all PUIs and cases."C_" = Cases only: Information about cases, which are those persons who have COVID-19 positive test results on file“W_” = Surveillance and syndromic dataKey Data about Testing:T_negative : Testing: Total negative persons tested for all Florida and non-Florida residents, including Florida residents tested outside of the state, and those tested at private facilities.T_positive : Testing: Total positive persons tested for all Florida and non-Florida resident types, including Florida residents tested outside of the state, and those tested at private facilities.PUILab_Yes : All persons tested with lab results on file, including negative, positive and inconclusive. This total does NOT include those who are waiting to be tested or have submitted tests to labs for which results are still pending.Key Data about Confirmed COVID-19 Positive Cases: CasesAll: Cases only: The sum total of all positive cases, including Florida residents in Florida, Florida residents outside Florida, and non-Florida residents in FloridaFLResDeaths: Deaths of Florida ResidentsC_Hosp_Yes : Cases (confirmed positive) with a hospital admission notedC_AgeRange Cases Only: Age range for all cases, regardless of residency typeC_AgeMedian: Cases Only: Median range for all cases, regardless of residency typeC_AllResTypes : Cases Only: Sum of COVID-19 positive Florida Residents; includes in and out of state Florida residents, but does not include out-of-state residents who were treated/tested/isolated in Florida. All questions regarding this dataset should be directed to the Florida Department of Health.
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TwitterFlorida COVID-19 Cases by County exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/ . https://doi.org/10.5038/USF-COVID-19-GISLive FDOH DataSource: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. Up until 3/25 the FDOH Cases by County layer was updated twice a day, archives are taken from the 11AM update.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results. All PUIs fit into one of three residency types: 1. Florida residents tested in Florida2. Non-Florida residents tested in Florida3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outside of Florida, and were not exposed/infectious in Florida.Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state. Total Cases: The total (sum) number of Persons Under Investigation (PUI) who tested positive for COVID-19 while in Florida, as well as Florida residents who tested positive or were exposed/contagious while outside of Florida, and out-of-state residents who were exposed, contagious and/or tested in Florida.Deaths: The Deaths by Day chart shows the total number of Florida residents with confirmed COVID-19 that died on each calendar day (12:00 AM - 11:59 PM). Caution should be used in interpreting recent trends, as deaths are added as they are reported to the Department. Death data often has significant delays in reporting, so data within the past two weeks will be updated frequently.Prefix guide: "PUI" = PUI: Persons under surveillance (any person for which we have data about)"T_ " = Testing: Testing information for all PUIs and cases."C_" = Cases only: Information about cases, which are those persons who have COVID-19 positive test results on file“W_” = Surveillance and syndromic dataKey Data about Testing:T_negative : Testing: Total negative persons tested for all Florida and non-Florida residents, including Florida residents tested outside of the state, and those tested at private facilities.T_positive : Testing: Total positive persons tested for all Florida and non-Florida resident types, including Florida residents tested outside of the state, and those tested at private facilities.PUILab_Yes : All persons tested with lab results on file, including negative, positive and inconclusive. This total does NOT include those who are waiting to be tested or have submitted tests to labs for which results are still pending.Key Data about Confirmed COVID-19 Positive Cases: CasesAll: Cases only: The sum total of all positive cases, including Florida residents in Florida, Florida residents outside Florida, and non-Florida residents in FloridaFLResDeaths: Deaths of Florida ResidentsC_Hosp_Yes : Cases (confirmed positive) with a hospital admission notedC_AgeRange Cases Only: Age range for all cases, regardless of residency typeC_AgeMedian: Cases Only: Median range for all cases, regardless of residency typeC_AllResTypes : Cases Only: Sum of COVID-19 positive Florida Residents; includes in and out of state Florida residents, but does not include out-of-state residents who were treated/tested/isolated in Florida. All questions regarding this dataset should be directed to the Florida Department of Health.
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This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.
All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.
Only Chicago residents are included based on the home address as provided by the medical provider.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey