https://github.com/nytimes/covid-19-data/blob/master/LICENSEhttps://github.com/nytimes/covid-19-data/blob/master/LICENSE
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 the first reported coronavirus case in Washington State on Jan. 21, 2020, 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.
As of November 11, 2022, almost 96.8 million confirmed cases of COVID-19 had been reported by the World Health Organization (WHO) for the United States. The pandemic has impacted all 50 states, with vast numbers of cases recorded in California, Texas, and Florida.
The coronavirus in the U.S. The coronavirus hit the United States in mid-March 2020, and cases started to soar at an alarming rate. The country has performed a high number of COVID-19 tests, which is a necessary step to manage the outbreak, but new coronavirus cases in the U.S. have spiked several times since the pandemic began, most notably at the end of 2022. However, restrictions in many states have been eased as new cases have declined.
The origin of the coronavirus In December 2019, officials in Wuhan, China, were the first to report cases of pneumonia with an unknown cause. A new human coronavirus – SARS-CoV-2 – has since been discovered, and COVID-19 is the infectious disease it causes. All available evidence to date suggests that COVID-19 is a zoonotic disease, which means it can spread from animals to humans. The WHO says transmission is likely to have happened through an animal that is handled by humans. Researchers do not support the theory that the virus was developed in a laboratory.
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.
April 9, 2020
April 20, 2020
April 29, 2020
September 1st, 2020
February 12, 2021
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/)
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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
In 2020, there were a total of 384,536 deaths in the United States caused by COVID-19. Those aged 85 years and older accounted for 122,707 COVID deaths that year. This statistic shows the total number of deaths due to COVID-19 in the United States in 2020, 2021, and 2022, by age.
Around 282 thousand new cases of COVID-19 were reported in the United States during the week ending November 11, 2022. Between January 20, 2020 and November 11, 2022 there had been around 96.8 million confirmed cases of COVID-19 with over one million deaths in the U.S. as reported by the World Health Organization.
How did the coronavirus outbreak start? Pneumonia cases with an unknown cause were first reported in the Hubei province of China at the end of December 2019. Patients described symptoms including a fever and difficulty breathing, and early reports suggested no evidence of human-to-human transmission. We now know that a novel coronavirus named SARS-CoV-2 is causing the disease COVID-19. The virus has been characterized as a pandemic and continues to spread from person to person – there have been around 642 million cases worldwide as of November 17, 2022.
The importance of isolation and quarantine In an effort to contain the early spread of the virus, China tightened travel restrictions and enforced isolation measures in the hardest-hit areas. The World Health Organization endorsed this strategy, and countries around the world implemented similar quarantine measures. Staying at home can limit the spread of the virus, and this applies to individuals who are only showing mild symptoms or none at all. Asymptomatic carriers of the virus – those that are experiencing no symptoms – may transmit the virus to people who are at a higher risk of getting very sick.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
New Covid tests per month in Brazil, September, 2021 The most recent value is 3787260 new Covid tests as of September 2021, an increase compared to the previous value of 2239698 new Covid tests. Historically, the average for Brazil from April 2020 to September 2021 is 4641320 new Covid tests. The minimum of 436538 new Covid tests was recorded in April 2020, while the maximum of 20400000 new Covid tests was reached in October 2020. | TheGlobalEconomy.com
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.
The following dataset provides state-aggregated data for hospital utilization in a timeseries format dating back to January 1, 2020. These are derived from reports with facility-level granularity across three main sources: (1) HHS TeleTracking, (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities and (3) National Healthcare Safety Network (before July 15).
The file will be updated regularly and provides the latest values reported by each facility within the last four days for all time. This allows for a more comprehensive picture of the hospital utilization within a state by ensuring a hospital is represented, even if they miss a single day of reporting.
No statistical analysis is applied to account for non-response and/or to account for missing data.
The below table displays one value for each field (i.e., column). Sometimes, reports for a given facility will be provided to more than one reporting source: HHS TeleTracking, NHSN, and HHS Protect. When this occurs, to ensure that there are not duplicate reports, prioritization is applied to the numbers for each facility.
On April 27, 2022 the following pediatric fields were added:
On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly and currently shows data through Mar 5, 2023. Notes: as of 5/25/2021, Nebraska stopped sharing COVID-19 testing and on 9/26/21 began, but with a lump sum for the previous four months. Nebraska's reporting became unconsumable by JHU on July 1, 2022. Maryland stopped reporting results for several weeks on 12/4/2021 due to a website hack.It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend.Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility.Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 1, 2020.For more information about COVID-19 trends, see the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The number of COVID-19 vaccination doses administered per 100 people in Morocco rose to 148 as of Oct 27 2023. This dataset includes a chart with historical data for Morocco Coronavirus Vaccination Rate.
Based 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
New Covid tests per thousand people in Aruba, June, 2021 The most recent value is 112 new Covid tests per thousand people as of June 2021, an increase compared to the previous value of new Covid tests per thousand people. Historically, the average for Aruba from June 2021 to June 2021 is 112 new Covid tests per thousand people. The minimum of 112 new Covid tests per thousand people was recorded in June 2021, while the maximum of 112 new Covid tests per thousand people was reached in June 2021. | TheGlobalEconomy.com
The data includes:
More detailed epidemiological charts and graphs are presented for areas in very high and high local COVID alert level areas.
See the https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-hospital-activity/" class="govuk-link">detailed data on hospital activity.
See the https://coronavirus.data.gov.uk/?_ga=2.43448994.685856970.1607933075-1070872729.1597161719" class="govuk-link">detailed data on the progress of the coronavirus pandemic.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The number of COVID-19 vaccination doses administered in Honduras rose to 16963148 as of Jul 15 2023. This dataset includes a chart with historical data for Honduras Coronavirus COVID-19 Vaccination Total.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The number of COVID-19 vaccination doses administered in Brazil rose to 486436436 as of Oct 27 2023. This dataset includes a chart with historical data for Brazil Coronavirus Vaccination Total.
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html).
Cumulative deaths involving COVID-19 reported to NCHS by sex and age in years, in the United States.
NM Health Councils participating in the Vaccine Equity Project can use this map to determine what their baseline data is from Dec 2021.Need help navigating this map? View the Step-by-step guide to identifying your Health Councils Dec Baseline data here: https://nmcdc.maps.arcgis.com/sharing/rest/content/items/208ebb2d96f448858ec7a38dbded3ad6/dataAlso see the data table showing percent vaccinated by age categories as of Dec 31st 2021 to make finding your baseline data easy: https://nmcdc.maps.arcgis.com/sharing/rest/content/items/30848fdb69ea4d2c89324f9830d2cd40/data
Note: Blueprint has been retired as of June 15, 2021. This dataset will be kept up for historical purposes, but will no longer be updated.
California has a new blueprint for reducing COVID-19 in the state with revised criteria for loosening and tightening restrictions on activities. Every county in California is assigned to a tier based on its test positivity and adjusted case rate for tier assignment. Additionally, a new health equity metric took effect on October 6, 2020. In order to advance to the next less restrictive tier, each county will need to meet an equity metric or demonstrate targeted investments to eliminate disparities in levels of COVID-19 transmission, depending on its size. The California Health Equity Metric is designed to help guide counties in their continuing efforts to reduce COVID-19 cases in all communities and requires more intensive efforts to prevent and mitigate the spread of COVID-19 among Californians who have been disproportionately impacted by this pandemic.
Please see https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/COVID19CountyMonitoringOverview.aspx for more information.
Also, in lieu of a Data Dictionary, please refer to the detailed explanation of the data columns in Appendix 1 of the above webpage.
Because this data is in machine-readable format, the merged headers at the top of the source spreadsheet have not been included:
The first 8 columns are under the header "County Status as of Tier Assignment"
The next 3 columns are under the header "Current Data Week Tier and Metric Tiers for Data Week"
The next 4 columns are under the header "Case Rate Adjustment Factors"
The next column is under the header "Small County Considerations"
The last 5 columns are under the header "Health Equity Framework Parameters"
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19"
cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".
These are CSV files of data in the figures and tables published in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".
50-e0diffT.csv
Figure 1: Life expectancy changes 2019/20 and 2020/21 across countries. The countries are ordered by increasing cumulative life expectancy losses since 2019. Grey dots indicate the average annual LE changes over the years 2015 through 2019.
51-arriagaT.csv
Figure 2: Age contributions to life expectancy changes since 2019 separated for 2020 and 2021. The position of the arrowhead indicates the total contribution of mortality changes in a given age group to the change in life expectancy at birth since 2019. The discontinuity in the arrow indicates those contributions separately for the years 2020 and 2021. Annual contributions can compound or reverse. The total life expectancy change from 2019 to 2021 in a given country is the sum of the arrowhead positions across age.
52-sexdiff.csv
Figure 3: Change in the female life expectancy advantage from 2019 through 2021. Blue colors indicate an increase and red colors a decrease in the female life expectancy advantage. Muted colors indicate non-significant changes.
53-e0diffcodT.csv
Figure 4: Life expectancy deficit in 2021 decomposed into contributions by age and cause of death. LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.
55-vaxe0.csv
Figure 5: Years of life expectancy deficit during October through December 2021 contributed by ages <60 and 60+ against % of population twice vaccinated by October 1st in the respective age groups. LE deficit is defined as the counterfactual LE from a Lee-Carter mortality forecast based on death rates for the fourth quarter of the years 2015 to 2019 minus observed LE.
54-tab_arriaga.csv
Table 1: Months of life expectancy (LE) changes and deficits (labelled ES) since the start of the pandemic attributed to age-specific mortality changes (labelled AT). LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.
The dataset consists of self-administered written texts on experiences related to the coronavirus epidemic. The data chart people's everyday lives as the pandemic continued in 2021. The dataset is a continuation of the Finnish Literary Society's previous COVID-19 related data collection, Koronakevät ('COVID-19 Spring”), which was carried out in 2020. The Koronakevät dataset is available from the archive of the Finnish Literature Society. The writing guidelines directed participants to write about their experiences during the continuing COVID-19 pandemic in the spring of 2021. Participants were asked to reflect on how they personally perceived the time period affected by the coronavirus epidemic and how their attitudes towards the coronavirus had changed as the pandemic had continued. The study investigated participants' attitudes towards restrictions and security measures and their efforts to avoid contracting COVID-19. Participants were also prompted to write about their possible personal experiences of contracting COVID-19, the experiences of individuals in their immediate circle who had contracted COVID-19, and their attitudes towards contracting the virus. In relation to the coronavirus, participants were asked about their attitudes towards COVID-19 vaccines and their general attitudes towards COVID-19. Additionally, participants could write about the impact COVID-19 had had on their everyday lives, interpersonal relationships, and life in general. Any possible positive effects of COVID-19 and factors affecting participants' well-being and resilience were also charted. Background information included the participant's gender, year of birth, occupation, and area of residence. The data were organised into an easy to use HTML version at FSD. The dataset is only available in Finnish.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
New Covid tests per month in Madagascar, September, 2021 The most recent value is 20790 new Covid tests as of September 2021, an increase compared to the previous value of 13847 new Covid tests. Historically, the average for Madagascar from April 2020 to September 2021 is 16919 new Covid tests. The minimum of 2445 new Covid tests was recorded in April 2020, while the maximum of 40410 new Covid tests was reached in April 2021. | TheGlobalEconomy.com
https://github.com/nytimes/covid-19-data/blob/master/LICENSEhttps://github.com/nytimes/covid-19-data/blob/master/LICENSE
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 the first reported coronavirus case in Washington State on Jan. 21, 2020, 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.