On December 19, 2022, there were 3,553 new cases of COVID-19 in New York City. The state of New York has been one of the hardest hit U.S. states by the COVID-19 pandemic. This statistic shows the number of new COVID-19 cases in New York City from March 8, 2020 to December 19, 2022, by diagnosis date.

On April 7, 2020, there were 598 new deaths due to COVID-19 in New York City, higher than any other day since the pandemic hit the city. The state of New York has been one of the hardest hit U.S. states by the COVID-19 pandemic. This statistic shows the number of new COVID-19 deaths in New York City from March 3, 2020 to December 19, 2022, by date.

Note: Data elements were retired from HERDS on 10/6/23 and this dataset was archived.

This dataset includes the cumulative number and percent of healthcare facility-reported fatalities for patients with lab-confirmed COVID-19 disease by reporting date and age group. This dataset does not include fatalities related to COVID-19 disease that did not occur at a hospital, nursing home, or adult care facility. The primary goal of publishing this dataset is to provide users with information about healthcare facility fatalities among patients with lab-confirmed COVID-19 disease.

The information in this dataset is also updated daily on the NYS COVID-19 Tracker at https://www.ny.gov/covid-19tracker.

The data source for this dataset is the daily COVID-19 survey through the New York State Department of Health (NYSDOH) Health Electronic Response Data System (HERDS). Hospitals, nursing homes, and adult care facilities are required to complete this survey daily. The information from the survey is used for statewide surveillance, planning, resource allocation, and emergency response activities. Hospitals began reporting for the HERDS COVID-19 survey in March 2020, while Nursing Homes and Adult Care Facilities began reporting in April 2020. It is important to note that fatalities related to COVID-19 disease that occurred prior to the first publication dates are also included.

The fatality numbers in this dataset are calculated by assigning age groups to each patient based on the patient age, then summing the patient fatalities within each age group, as of each reporting date. The statewide total fatality numbers are calculated by summing the number of fatalities across all age groups, by reporting date. The fatality percentages are calculated by dividing the number of fatalities in each age group by the statewide total number of fatalities, by reporting date. The fatality numbers represent the cumulative number of fatalities that have been reported as of each reporting date.

IntroductionOur study explores how New York City (NYC) communities of various socioeconomic strata were uniquely impacted by the COVID-19 pandemic.MethodsNew York City ZIP codes were stratified into three bins by median income: high-income, middle-income, and low-income. Case, hospitalization, and death rates obtained from NYCHealth were compared for the period between March 2020 and April 2022.ResultsCOVID-19 transmission rates among high-income populations during off-peak waves were higher than transmission rates among low-income populations. Hospitalization rates among low-income populations were higher during off-peak waves despite a lower transmission rate. Death rates during both off-peak and peak waves were higher for low-income ZIP codes.DiscussionThis study presents evidence that while high-income areas had higher transmission rates during off-peak periods, low-income areas suffered greater adverse outcomes in terms of hospitalization and death rates. The importance of this study is that it focuses on the social inequalities that were amplified by the pandemic.

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 December 22, 2022, those aged 18 to 24 years had the highest rates of COVID-19 in New York City. The state of New York has been one of the hardest hit U.S. states by the COVID-19 pandemic. This statistic shows rates of COVID-19 cases in New York City by age group, as of December 22, 2022.

As of December 16, 2022, there had been almost 6.37 million COVID-19 cases in New York State, with 2.97 million cases found in New York City. New York has been one of the U.S. states most impacted by the pandemic, recording the highest number of deaths in the country.

A closer look at the outbreak in New York Towards the middle of December 2022, the number of deaths due to the coronavirus in New York State had reached almost 60 thousand, and almost half of those deaths were in New York City. However, the number of new daily deaths in New York City peaked early in the pandemic and although there have been times when the number of new daily deaths surged, they have not gotten close to reaching the levels seen at the beginning of the pandemic. New York City is made up of five counties, which are more commonly known by their borough names – Staten Island is the borough with the highest rate of COVID-19 cases.

This dataset shows daily confirmed and probable cases of COVID-19 in New York City by date of specimen collection. Total cases has been calculated as the sum of daily confirmed and probable cases. Seven-day averages of confirmed, probable, and total cases are also included in the dataset. A person is classified as a confirmed COVID-19 case if they test positive with a nucleic acid amplification test (NAAT, also known as a molecular test; e.g. a PCR test). A probable case is a person who meets the following criteria with no positive molecular test on record: a) test positive with an antigen test, b) have symptoms and an exposure to a confirmed COVID-19 case, or c) died and their cause of death is listed as COVID-19 or similar. As of June 9, 2021, people who meet the definition of a confirmed or probable COVID-19 case >90 days after a previous positive test (date of first positive test) or probable COVID-19 onset date will be counted as a new case. Prior to June 9, 2021, new cases were counted ≥365 days after the first date of specimen collection or clinical diagnosis. Any person with a residence outside of NYC is not included in counts. Data is sourced from electronic laboratory reporting from the New York State Electronic Clinical Laboratory Reporting System to the NYC Health Department. All identifying health information is excluded from the dataset. These data are used to evaluate the overall number of confirmed and probable cases by day (seven day average) to track the trajectory of the pandemic. Cases are classified by the date that the case occurred. NYC COVID-19 data include people who live in NYC. Any person with a residence outside of NYC is not included.

To conduct a longitudinal cross-sectional study of anti-S and anti-NP to study the geographical distribution of the seroprevalence and antibody titers in residents of NYC throughout the pandemic.

Here, the authors describe results of a cross-sectional hospital-based study of anti-spike seroprevalence in New York City (NYC) from February 2020 to July 2022, and a follow-up period from August 2023 to October 2023.

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently.Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19.Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method.Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0–17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0–17 and 18–44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC.Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

Historical Coronavirus (Covid-19) Data for the United States

NEW: We are publishing the data behind our excess deaths tracker in order to provide researchers and the public with a better record of the true toll of the pandemic. This data is compiled from official national and municipal data for 24 countries. See the data and documentation in the excess-deaths/ directory.

[ U.S. Data (Raw CSV) | U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Live and Historical Data

We are providing two sets of data with cumulative counts of coronavirus cases and deaths: one with our most current numbers for each geography and another with historical data showing the tally for each day for each geography.

The historical data files are at the top level of the directory and contain data up to, but not including the current day. The live data files are in the live/ directory.

A key difference between the historical and live files is that the numbers in the historical files are the final counts at the end of each day, while the live files have figures that may be a partial count released during the day but cannot necessarily be considered the final, end-of-day tally..

The historical and live data are released in three files, one for each of these geographic levels: U.S., states and counties.

Each row of data reports the cumulative number of coronavirus cases and deaths based on our best reporting up to the moment we publish an update. Our counts include both laboratory confirmed and probable cases using criteria that were developed by states and the federal government. Not all geographies are reporting probable cases and yet others are providing confirmed and probable as a single total. Please read here for a full discussion of this issue.

We do our best to revise earlier entries in the data when we receive new information. If a county is not listed for a date, then there were zero reported confirmed cases and deaths.

State and county files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

Download all the data or clone this repository by clicking the green "Clone or download" button above.

Historical Data

U.S. National-Level Data

The daily number of cases and deaths nationwide, including states, U.S. territories and the District of Columbia, can be found in the us.csv file. (Raw CSV file here.)

date,cases,deaths
2020-01-21,1,0
...

State-Level Data

State-level data can be found in the states.csv file. (Raw CSV file here.)

date,state,fips,cases,deaths
2020-01-21,Washington,53,1,0
...

County-Level Data

County-level data can be found in the counties.csv file. (Raw CSV file here.)

date,county,state,fips,c...

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

<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>

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

Acknowledgements

This dataset is from the New York Times GITHUB source. https://github.com/nychealth/coronavirus-data/tree/master/trends

This dataset contains data on Coronavirus Disease 2019 (COVID-19) in New York City (NYC). The Health Department classifies the start of the COVID-19 outbreak in NYC as the date of the first laboratory-confirmed case, February 29, 2020.

This dataset has been adjusted and only contains a week of data in Florida.

=

All Pandora data used in this studycan be downloaded freely from the Pandonia Global Network website https://www.pandonia-global-network.org/ (last access: 4 June 2021). Our gridded satellite NO2 products and output from our model simulations can be obtained by contacting the corresponding author, Maria Tzortziou (mtzortziou@ccny.cuny.edu). This dataset is associated with the following publication: Tzortziou, M., C. Kwong, D. Goldberg, L. Schiferl, R. Commane, N. Abuhassan, J. Szykman, and L. Valin. Declines and peaks in NO2 pollution during the multiple waves of the COVID-19 pandemic in the New York metropolitan area. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 22(4): 2399-2417, (2022).

After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.

It is a weekly snapshot in time that:

• Focuses on recent outcomes in the last seven days and changes relative to the month prior
• Provides additional contextual information at the county level for each state, and includes national level information
• Supports rapid visual interpretation of results with color thresholds

In response to the COVID-19 pandemic, NYC Parks temporarily closed several amenities, including Adult Exercise Equipment. This data collection contains the status of each Adult Exercise Equipment, and is subject to change. Although the data feed is refreshed daily, it may not reflect current conditions.

Data Dictionary:

https://docs.google.com/spreadsheets/d/1aaYE82BS-SYh-xjI-t_oyJcNEPFWJNPfdI7T220-rv4/edit#gid=1499621902

Source

This data comes from the New York Times Coronavirus (Covid-19) Data in the United States GitHub repository. They use it to power their interactive page(s) on Covid-19, such as Coronavirus in the U.S.: Latest Map and Case Count.

What's Included?

The primary data published here are the daily cumulative number of cases and deaths reported in each county and state across the U.S. since the beginning of the pandemic. We have also published these additional data sets:

• Prisons: Cases in prisons
• Colleges: Cases on college and university campuses.
• Excess deaths: The elevated overall number of deaths during the pandemic.
• Mask use: A July 2020 survey of how regularly people in each county wore masks.
• Averages and anomalies: A set of pre-computed rolling averages of cases and deaths for ease of analysis or use in making graphics, along with a set of days with anomalous data that have been excluded from the averages.

The cumulative & rolling averages for cases and deaths are continually updated, but the more specific data mentioned above for prisons, etc. is no longer being updated.

This includes data at the national, state, and county levels.

License and Attribution

If you use this data, you must attribute it to “The New York Times” in any publication. If you would like a more expanded description of the data, you could say “Data from The New York Times, based on reports from state and local health agencies.”

Acknowledgements

Header Image: https://www.pexels.com/photo/n95-face-mask-3993241/

More Information

See the original New York Times source README which is also included in this dataset.

Socio-demographics, medical history, and admission laboratory markers for patients with COVID-19 Illness requiring supplemental oxygen (n = 270).

The dataset we provide is composed of a CSV file containing the answers of responders to our questionnaire conducted to explore perceptions and feelings on the COVID-19 pandemic. The survey was conducted from June 27 to July 2 2022 among university students and adult residents of Milan, Italy, and New York City, NY, U.S.A. The two target demographics for this study were adult residents of the two cities who were employed at the beginning of 2020 and students who attended university during 2020 or joined during the pandemic. The survey was accompanied by a promotional video and an introductory paragraph describing the objective of the study. It was shared through social media platforms, on specialized social media groups, and on university students’ mailing lists. The total number of questions asked is a maximum of 20, variable depending on answers given by a user since we employed branching based on previous answers. This feature was particularly useful in creating questions that were specific to a subset of the sample population The topics of questions cover the following broad areas: Relationships: Multiple Choice and sorting/ranking questions designed to understand who the respondents spent lockdown with, if they managed to keep in touch with those they could not meet, and to family, friends, and intimate relationships during the pandemic Policies: Likert scale questions measuring agreement with measures put in place in both Milan and New York Personal Life: questions about one’s priorities before and during the pandemic Occupation: Multiple Choice questions about one’s occupation during the pandemic and feelings towards work or university Post-pandemic: Likert scale questions about one's perception of contagion threats and feelings of normalcy at the time they responded to the survey Demographics: Multiple choice questions to describe the pool of respondents and control sample bias The types of questions are one of the following: Multiple choice (one or more selections or single selection); Ranking; and Numeric scale (1-5 or 1-10). The “ranking” question type allowed users to sort a list of items in descending order of importance. In the dataset the column name represents the ranking given to the item, e.g. 1. highest priority. (2023-02-03)