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

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

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

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

The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

The first two cases of the new coronavirus (COVID-19) in Italy were recorded between the end of January and the beginning of February 2020. Since then, the number of cases in Italy increased steadily, reaching over 26.9 million as of January 8, 2025. The region mostly hit by the virus in the country was Lombardy, counting almost 4.4 million cases. On January 11, 2022, 220,532 new cases were registered, which represented the biggest daily increase in cases in Italy since the start of the pandemic. The virus originated in Wuhan, a Chinese city populated by millions and located in the province of Hubei. 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.

Reporting of new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

• A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
• If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
• CDC compiles these data and posts the finalized information on COVID Data Tracker.
• County level data is aggregated to obtain state and territory specific totals.

This process is collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provide the most up-to-date numbers on cases and deaths by report date. CDC may retrospectively update counts to correct data quality issues.

Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

• Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
• Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
• Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
• Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.

Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

Council of State and Territorial Epidemiologists (ymaws.com).

Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (total case counts) as the present dataset; however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed.

Number of Jurisdictions Reporting There are currently 60 public health jurisdictions reporting cases of COVID-19. This includes the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. New York State’s reported case and death counts do not include New York City’s counts as they separately report nationally notifiable conditions to CDC.

CDC COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths, available by state and by county. These and other data on COVID-19 are available from multiple public locations, such as:

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

https://www.cdc.gov/covid-data-tracker/index.html

https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

https://www.cdc.gov/coronavirus/2019-ncov/php/open-america/surveillance-data-analytics.html

Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

Archived Data Notes:

November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 3, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 10, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Per the request of the jurisdiction, cases and deaths among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case and death counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases and deaths. 

November 17, 2022: Two new columns, weekly historic cases and weekly historic deaths, were added to this dataset on November 17, 2022. These columns reflect case and death counts that were reported that week but were historical in nature and not reflective of the current burden within the jurisdiction. These historical cases and deaths are not included in the new weekly case and new weekly death columns; however, they are reflected in the cumulative totals provided for each jurisdiction. These data are used to account for artificial increases in case and death totals due to batched reporting of historical data.

December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the data released on December 1, 2022.

January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case and death data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case and death metrics will appear higher than expected in the January 5, 2023, weekly release.

January 12, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0. As a result, case and death metrics will appear lower than expected in the January 12, 2023, weekly release.

January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case and death data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release.

January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties (Livingston and Washtenaw) were higher than expected in the January 19, 2023 weekly release.

January 26, 2023: Due to a backlog of historic COVID-19 cases being reported this week, aggregate case and death counts in Charlotte County and Sarasota County, Florida, will appear higher than expected in the January 26, 2023 weekly release.

January 26, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0 in the weekly release posted on January 26, 2023.

February 2, 2023: As of the data collection deadline, CDC observed an abnormally large increase in aggregate COVID-19 cases and deaths reported for Washington State. In response, totals for new cases and new deaths released on February 2, 2023, have been displayed as zero at the state level until the issue is addressed with state officials. CDC is working with state officials to address the issue.

February 2, 2023: Due to a decrease reported in cumulative case counts by Wyoming, case rates will be reported as 0 in the February 2, 2023, weekly release. CDC is working with state officials to verify the data submitted.

February 16, 2023: Due to data processing delays, Utah’s aggregate case and death data will be reported as 0 in the weekly release posted on February 16, 2023. As a result, case and death metrics will appear lower than expected and should be interpreted with caution.

February 16, 2023: Due to a reporting cadence change, Maine’s

Updates

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

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

• April 9, 2020

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

• April 20, 2020

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

• April 29, 2020

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

• September 1st, 2020

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

• February 12, 2021

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

• February 16, 2021

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

  Overview

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

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

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

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

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

Queries

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

• Filter cases by state here

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

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

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

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

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

Interactive

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

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

Interactive Embed Code

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Caveats

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

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

Attribution

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

After entering Italy, the coronavirus (COVID-19) spread fast. The strict lockdown implemented by the government during the Spring 2020 helped to slow down the outbreak. However, the country had to face four new harsh waves of contagion. As of January 1, 2025, the total number of cases reported by the authorities reached over 26.9 million. The north of the country was mostly hit, and the region with the highest number of cases was Lombardy, which registered almost 4.4 million of them. The north-eastern region of Veneto and the southern region of Campania followed in the list. When adjusting these figures for the population size of each region, however, the picture changed, with the region of Veneto being the area where the virus had the highest relative incidence. Coronavirus in Italy Italy has been among the countries most impacted by the coronavirus outbreak. Moreover, the number of deaths due to coronavirus recorded in Italy is significantly high, making it one of the countries with the highest fatality rates worldwide, especially in the first stages of the pandemic. In particular, a very high mortality rate was recorded among patients aged 80 years or older. Impact on the economy The lockdown imposed during the Spring 2020, and other measures taken in the following months to contain the pandemic, forced many businesses to shut their doors and caused industrial production to slow down significantly. As a result, consumption fell, with the sectors most severely hit being hospitality and tourism, air transport, and automotive. Several predictions about the evolution of the global economy were published at the beginning of the pandemic, based on different scenarios about the development of the pandemic. According to the official results, it appeared that the coronavirus outbreak had caused Italy’s GDP to shrink by approximately nine percent in 2020.

The COVID Tracking Project collects information from 50 US states, the District of Columbia, and 5 other US territories to provide the most comprehensive testing data we can collect for the novel coronavirus, SARS-CoV-2. We attempt to include positive and negative results, pending tests, and total people tested for each state or district currently reporting that data.

Testing is a crucial part of any public health response, and sharing test data is essential to understanding this outbreak. The CDC is currently not publishing complete testing data, so we’re doing our best to collect it from each state and provide it to the public. The information is patchy and inconsistent, so we’re being transparent about what we find and how we handle it—the spreadsheet includes our live comments about changing data and how we’re working with incomplete information.

From here, you can also learn about our methodology, see who makes this, and find out what information states provide and how we handle it.

As of March 10, 2023, the state with the highest number of COVID-19 cases was California. Almost 104 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers.

From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time. When the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide has now reached over 669 million.

The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. People aged 85 years and older have accounted for around 27 percent of all COVID-19 deaths in the United States, although this age group makes up just two percent of the U.S. population

This dataset contains the input data for the panel regression and SEIR analyses for the paper "Weather drives variation in COVID-19 transmission and detection", as well as the results of the SEIR calibrations.

Under the `inputs` directory, the `panel_all.csv` data provides the compiled data for the core analyses. For information on COVID cases, we use daily reports from the John Hopkins University's COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) (Dong et al. 2020). We complement these data with a variety of online sources on confirmed cases at the subnational level.

For information on weather, we use ERA 5 reanalysis (Hersbach et al. 2018). The data were downloaded from the Copernicus Climate Change Service (C3S) Climate Data Store in January 2021.

The governance data (in `inputs/governance`) is drawn from https://info.worldbank.org/governance/wgi/ for the year 2019.

The mapping is done using GADM 3.6, simplified to reduce its size, and stored in `inputs/gadm36_levels_simple`.

The result data in the `results` directory represents calibrations of the Bayesian SEIR model:

- Files of the form `epimodel-meta-0314...-nodel.csv` include parameter estimates both as initially calibrated (group = "Raw") and after the meta-analysis (group = "Combined"). Paramater estimates are represented by their mean, standard deviation, and five quantiles. Different files of this form reflect different assumptions: (1) `-noweather` exclude weather effects; `-noprior` exclude panel regression priors, and `-full3` include weather and priors; (2) `-all` were estimated using all observations; `-mobile` were estimated using only region/observations with mobility data; (3) `-nobs` include meta-analyzed data weighted by the number of observations; `-pop` are weighted by population; and `-region` are weighted by region.

- The `global-0314.RData` file contains calibrations treating the whole world as one region.

- The `pairwise.csv` and `pairwise-all.csv` compare data from regions that have valid no-prior (suffix 1) and no-weather (suffix 2) projections. `pairwise.csv` has summary statistics while `pairwise-all.csv` includes every region.

Acknowledgements:

The results contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

Bibliography:

Dong E, Du H, Gardner L (2020): An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2018): ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed in January 2021), 10.24381/cds.adbb2d47

*** The County of Santa Clara Public Health Department discontinued updates to the COVID-19 data tables effective June 30, 2025. The COVID-19 data tables will be removed from the Open Data Portal on December 30, 2025. For current information on COVID-19 in Santa Clara County, please visit the Respiratory Virus Dashboard [sccphd.org/respiratoryvirusdata]. For any questions, please contact phinternet@phd.sccgov.org ***

The dataset summarizes counts and rates of cumulative COVID-19 cases by cities in Santa Clara County. Source: California Reportable Disease Information Exchange

This dataset is updated every Thursday.

Supplementary materials for Gonzalez, A. R., & Lin, T. (2022). Translated Emission Pathways (TEPs): Long-Term Simulations of COVID-19 CO2 Emissions and Thermosteric Sea Level Rise Projections. Earth's Future. In Press.

Summary: This study introduces climate science to a broader audience by presenting an accessible research framework and environmental data related to the ongoing COVID-19 pandemic. A series of translated emission pathways (TEPs) were constructed based on the CO2 emission patterns from the various phases of COVID-19 response. In addition to resembling the forcing scenarios used within climate research, a thermosteric sea level rise analysis was incorporated to further emphasize the environmental benefits that can be obtained from long-term sustainability. As a promising start for including the general public in climate change discussion, this research promotes collective environmental action that mirrors the recommendations of the scientific community.

The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

The global COVID-19 diagnosis market is projected to reach USD XXX million by 2033, with a CAGR of XX% during the forecast period 2025-2033. The market is driven by the increasing incidence of COVID-19, the rising demand for early and accurate diagnosis, and the growing adoption of molecular diagnostic tests. The market is segmented into two main types of tests: RT-PCR (Reverse Transcription Polymerase Chain Reaction) and isothermal nucleic acid amplification (INAAT). RT-PCR is the most commonly used test, as it is highly accurate and sensitive. However, it is also more expensive and time-consuming than INAAT. INAAT is a newer technology that is becoming increasingly popular, as it is faster and less expensive than RT-PCR. The market is also segmented by application, with hospitals and laboratories being the two main end-users. Hospitals are expected to account for the larger share of the market, as they are more likely to have the necessary equipment and expertise to perform COVID-19 tests. Laboratories are expected to play an increasingly important role in the market, as they are able to offer a wider range of testing services. With the global COVID-19 pandemic continuing to impact healthcare systems worldwide, the demand for accurate and reliable diagnostic tests has skyrocketed. The market for COVID-19 diagnosis has experienced significant growth, with advancements in technology and innovation driving the development of novel and efficient testing methods.

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

Several additional data limitations should be kept in mind:

• Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

• Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

• However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

• Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

• The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

The COVID-19 Health Code market has witnessed substantial growth in recent years, driven by the increasing demand for digital health solutions to mitigate the spread of infectious diseases. The market was valued at USD 3.5 billion in 2023 and is projected to reach USD 14.1 billion by 2030, exhibiting a CAGR of 20.6% during the forecast period. The rising prevalence of chronic diseases and the growing need for remote patient monitoring have further fueled the adoption of COVID-19 Health Codes. Key drivers of the market include the increasing number of COVID-19 cases, rising healthcare costs, government initiatives to promote digital health solutions, and the growing adoption of mobile health devices. However, factors such as data privacy and security concerns and a lack of standardization across different health code systems may restrain market growth. The market's major segments include application (domestic and international) and type (cloud-based and on-premise). Cloud-based systems are gaining popularity due to their scalability and cost-effectiveness, while on-premise systems offer more control and security. Geographically, North America and Europe dominate the COVID-19 Health Code market, followed by Asia Pacific and the Middle East & Africa.

The global COVID-19 Diagnosis market was valued at USD 25.6 billion in 2025 and is expected to expand at a CAGR of 5.4% from 2025 to 2033, reaching USD 39.8 billion by 2033. The market growth is primarily driven by the increasing prevalence of COVID-19 infections, the introduction of advanced diagnostic technologies, and the growing need for accurate and timely diagnosis. Additionally, government initiatives and funding for COVID-19 research and development are further contributing to market expansion. Regional analysis reveals that North America held the largest market share in 2025, followed by Europe and Asia Pacific. The high prevalence of COVID-19 cases, well-established healthcare infrastructure, and access to advanced diagnostic technologies in these regions are key growth factors. Asia Pacific is expected to witness significant growth over the forecast period, owing to the increasing population, rising healthcare expenditure, and growing awareness of COVID-19 diagnosis. Key players in the market include Cepheid, Abbott, Mesa Biotech, Microsens Dx, GenMark Diagnostics, Credo, Quest Diagnostics, LabCorp, Roche Diagnostics, Thermo Fisher Scientific, BD, PerkinElmer, Quidel, and Abbott. These companies are focusing on developing innovative diagnostic technologies, expanding their geographic reach, and collaborating with healthcare providers to strengthen their market position.

Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov. Estimates of excess deaths can provide information about the burden of mortality potentially related to COVID-19, beyond the number of deaths that are directly attributed to COVID-19. Excess deaths are typically defined as the difference between observed numbers of deaths and expected numbers. This visualization provides weekly data on excess deaths by jurisdiction of occurrence. Counts of deaths in more recent weeks are compared with historical trends to determine whether the number of deaths is significantly higher than expected. Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). For each jurisdiction, a model is used to generate a set of expected counts, and the upper bound of the 95% Confidence Intervals (95% CI) of these expected counts is used as a threshold to estimate excess deaths. Observed counts are compared to these upper bound estimates to determine whether a significant increase in deaths has occurred. Provisional counts are weighted to account for potential underreporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes.

According to Cognitive Market Research, the global COVID-19 diagnostics market size will be USD 33562.6 million in 2025. It will expand at a compound annual growth rate (CAGR) of 22.10% from 2025 to 2033.

North America held the major market share for more than 40% of the global revenue with a market size of USD 13425.04 million in 2025 and will grow at a compound annual growth rate (CAGR) of 20.3% from 2025 to 2033.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 10068.78 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 7719.40 million in 2025 and will grow at a compound annual growth rate (CAGR) of 24.1% from 2025 to 2033.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1678.13 million in 2025 and will grow at a compound annual growth rate (CAGR) of 21.5% from 2025 to 2033.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 671.25 million in 2025 and will grow at a compound annual growth rate (CAGR) of 21.8% from 2025 to 2033.
The hospitals category led the COVID-19 diagnostics market.

Market Dynamics of COVID-19 Diagnostics Market

Key Drivers for COVID-19 Diagnostics Market

Growing Coronavirus Disease Frequency to Boost Market Growth

The need for COVID-19 diagnostic tools and techniques has increased as a result of the abrupt increase in the infectious coronavirus illness that caused a worldwide epidemic. In addition to raising security issues and necessitating the diagnosis and isolation of infected individuals, the increasing number of potential infections and the requirement to verify test findings have led to a rise in interest in more kits, which is anticipated to propel market expansion. The sales of kits and reagents used to identify coronavirus infections are likely to rise as a result of these causes. Furthermore, increasing R&D efforts is likely to fuel market expansion. For instance, In August 2022, Thermo Fisher Scientific, the global leader in academic services, revealed the release of its newest assurance of quality tool, the Thermo Scientific AcroMetrix Coronavirus (COVID-19) RNA Management, to monitor and verify the COVID-19 molecular diagnostic procedures

(Source: https://newsroom.thermofisher.com/newsroom/press-releases/press-release-details/2020/Thermo-Fisher-Scientific-Launches-New-AcroMetrix-Coronavirus-2019-COVID-19-RNA-Control-RUO-03-31-2020/default.aspx/)

Innovative Technology Integrating in Diagnosis to Drive Market Growth

The COVID-19 diagnostics market is developing as a result of the use of technological methods, such as artificial intelligence and cloud-based platforms. Tools with AI capabilities evaluate test data more quickly and precisely, lowering the possibility of human mistakes. Digital platforms have also made it easier to gather data for epidemiological investigations, trace contacts, and share results remotely. The ability of AI to identify COVID-19 infection from lung X-rays with a reliability that surpasses proving its usefulness in diagnostics was demonstrated in research that has appeared in Nature. Consequently, the growing use of cutting-edge technologies in diagnostics drives the growth of the COVID-19 diagnostics market.

Restraint Factor for the COVID-19 Diagnostics Market

Inadequate Facilities for Healthcare, will Limit Market Growth

The expansion of the COVID-19 diagnostics market is largely restricted by insufficient medical infrastructures, particularly in frontier regions. Complicated and pure reagents, including digestive enzymes, primers, and instruments, are essential for conducting studies in clinical labs. Shortages of these reagents have been caused by a number of circumstances, including hoarding, export restrictions, and an abrupt increase in demand. Furthermore, these reagents are produced by restricted enterprises, which results in a lack of supply because of insufficient manufacturing resources. Consequently, it is projected that the inadequate global reagent demand-to-supply ratio would negatively impact the overall diagnostic rate and hinder market expansion.

Market Trends in COVID-19 Diagnostics Market

The Absolute Importance of Test Kits in Medical Facilities

The global expansion of the coronavirus has increased the demand for coronavirus testing equipment. Coronav...

COVID-19 Diagnosis Market Outlook

The global COVID-19 diagnosis market size was valued at USD 84.5 billion in 2023 and is projected to reach USD 98.3 billion by 2032, growing at a CAGR of 1.6% from 2024 to 2032. The market's growth is primarily driven by the increasing demand for rapid and accurate diagnostic testing to control the spread of COVID-19 and the ongoing development of innovative diagnostic technologies.

One of the key growth factors for the COVID-19 diagnosis market is the urgent need for effective disease management during pandemics. The unprecedented scale of the COVID-19 pandemic highlighted significant gaps in global diagnostic capabilities, prompting both governments and private sectors to invest heavily in diagnostic infrastructure. The rapid development and deployment of various diagnostic tests, such as molecular, antigen, and antibody tests, have been crucial in identifying and isolating infected individuals, thereby mitigating the spread of the virus.

Another significant factor contributing to market growth is the continuous advancements in diagnostic technology. Innovations such as high-throughput sequencing, CRISPR-based diagnostics, and advanced point-of-care testing devices have significantly improved the accuracy, speed, and ease of COVID-19 detection. This technological progression has not only enhanced the ability to diagnose the disease promptly but has also paved the way for broader applications in the diagnosis of other infectious diseases, potentially leading to a more resilient healthcare system in the future.

The growing awareness and importance of early detection and monitoring of COVID-19 infections are also fueling the market. Public health campaigns and educational initiatives have emphasized the critical role of testing in controlling the pandemic. As a result, there has been a notable increase in testing rates globally, further driving the demand for diagnostic tests. Additionally, the availability of government funding and support for diagnostic research and development has accelerated the introduction of new and improved diagnostic products into the market.

From a regional perspective, North America and Europe have been leading in terms of advanced diagnostic infrastructure and high testing rates. However, significant growth is anticipated in the Asia Pacific region due to increasing investments in healthcare infrastructure and rising awareness about the importance of early diagnosis. Regions such as Latin America and the Middle East & Africa are also expected to witness growth, driven by efforts to improve diagnostic capabilities and manage infectious disease outbreaks more effectively.

Test Type Analysis

The COVID-19 diagnosis market by test type is segmented into molecular tests, antigen tests, and antibody tests. Molecular tests, including RT-PCR, have been the gold standard for COVID-19 diagnosis due to their high sensitivity and specificity. These tests detect the virus's genetic material, making them highly accurate in identifying active infections. The widespread adoption of molecular testing has been driven by the urgent need for precise diagnosis, especially in the early stages of infection when viral loads are high. Moreover, continuous advancements in molecular diagnostic technologies have reduced the turnaround time and increased the throughput, making these tests more accessible and efficient.

Antigen tests offer a rapid and cost-effective alternative to molecular tests. These tests detect specific proteins from the virus, providing results in a shorter time frame, often within minutes to an hour. While antigen tests are generally less sensitive than molecular tests, their ability to deliver quick results has made them invaluable in settings where rapid decision-making is critical, such as airports, schools, and workplaces. The growing demand for mass testing and the need to quickly identify and isolate infected individuals have significantly boosted the adoption of antigen tests worldwide.

Antibody tests, also known as serological tests, detect the presence of antibodies in the blood, indicating past exposure to the virus. These tests are crucial for understanding the spread of the virus within populations and for identifying individuals who may have developed some level of immunity. While not typically used for diagnosing active infections, antibody tests have played a vital role in epidemiological studies and vaccine efficacy assessments. The development of highly sensitive and specific antibody tests has improved the accuracy of these assessments,

Covid-19 Surface Testing Market Outlook

In 2023, the global Covid-19 surface testing market size was valued at approximately USD 1.2 billion and is projected to reach USD 2.5 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 8.3% during the forecast period. The market growth is primarily driven by the ongoing need for effective monitoring and containment of the coronavirus in various environments, including healthcare facilities, public spaces, and commercial establishments.

One of the major growth factors fueling the Covid-19 surface testing market is the heightened awareness of hygiene and sanitation standards. The pandemic has underscored the importance of regular surface testing to prevent the spread of the virus through contaminated surfaces. This has led to a significant increase in demand for surface testing products and technologies across various sectors. Additionally, the implementation of stringent health and safety regulations by governments and health organizations globally has further propelled the market.

Technological advancements in surface testing methodologies are another critical driver of market growth. Innovations such as rapid PCR kits and advanced immunoassays have improved the accuracy and speed of Covid-19 surface testing, making these tests more reliable and efficient. The development of these advanced testing solutions has not only enhanced the detection capabilities but also reduced the time required to obtain results, which is crucial for timely interventions and containment measures.

The expansion of testing infrastructure and services is also contributing significantly to market growth. With the increased demand for surface testing, there has been a corresponding rise in the number of diagnostic laboratories and testing facilities. These facilities are equipped with state-of-the-art technology and skilled personnel to conduct extensive surface testing. Moreover, the establishment of mobile and on-site testing units has made it easier to perform surface testing in various settings, thereby broadening the market reach.

Regionally, North America holds a dominant position in the Covid-19 surface testing market, driven by the presence of well-established healthcare infrastructure and a high level of awareness regarding health and hygiene. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the increasing number of Covid-19 cases, growing healthcare investments, and rising public awareness. Europe also represents a significant market, supported by substantial government initiatives and research activities focused on combating the virus.

Product Type Analysis

The Covid-19 surface testing market can be segmented by product type into test kits, reagents, and consumables. Test kits are the most prominently used product type, given their critical role in detecting the presence of the virus on various surfaces. These kits often include swabs, testing devices, and instructions for use, and are designed to provide quick and accurate results. The increasing demand for rapid and reliable testing methods has led to the widespread adoption of advanced test kits across different end-user segments.

Reagents play an essential role in the testing process, as they are used to detect the virus's genetic material. The market for reagents has seen substantial growth due to the continuous development and production of new testing solutions. High-quality reagents are crucial for ensuring the accuracy and reliability of test results, making them a vital component in the surface testing market. Moreover, the ongoing research efforts to improve reagent formulations are expected to further boost market growth.

Consumables, including items such as sample vials, gloves, and protective gear, are also integral to the Covid-19 surface testing process. These products ensure the safety and efficacy of the testing procedure by preventing contamination and protecting personnel. The demand for consumables has surged in parallel with the increase in surface testing activities, particularly in high-risk environments like hospitals and diagnostic laboratories. Continuous supply and availability of these essential items are crucial for maintaining testing operations.

Overall, the product type segment of the Covid-19 surface testing market is characterized by a diverse range of products that cater to different testing needs and requirements. The ongoing advancements in product development and the introduction of i