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.

DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2 As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well. With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county). This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity). A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case. These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020. Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

This dataset includes a count and rate per 100,000 population for COVID-19 cases, a count of COVID-19 molecular diagnostic tests, and a percent positivity rate for tests among people living in community settings for the previous two-week period. Dates are based on date of specimen collection (cases and positivity).

A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

Percent positivity is calculated as the number of positive tests among community residents conducted during the 14 days divided by the total number of positive and negative tests among community residents during the same period. If someone was tested more than once during that 14 day period, then those multiple test results (regardless of whether they were positive or negative) are included in the calculation.

These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf).

DPH note about change from 7-day to 14-day metrics: Prior to 10/15/2020, these metrics were calculated using a 7-day average rather than a 14-day average. The 7-day metrics are no longer being updated as of 10/15/2020 but the archived dataset can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/s22x-83rd

As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

Additional notes: As of 11/5/2020, CT DPH has added antigen testing for SARS-CoV-2 to reported test counts in this dataset. The tests included in this dataset include both molecular and antigen datasets. Molecular tests reported include polymerase chain reaction (PCR) and nucleic acid amplicfication (NAAT) tests.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Data suppression is applied when the rate is <5 cases per 100,000 or if there are <5 cases within the town. Information on why data suppression rules are applied can be found online here: https://www.cdc.gov/cancer/uscs/technical_notes/stat_methods/suppression.htm

Covid-19 Antigen Testing Kits Market Outlook

The global Covid-19 antigen testing kits market size was valued at $5.3 billion in 2023 and is projected to reach $8.6 billion by 2032, growing at a CAGR of 5.4% during the forecast period. The primary growth factors for this market include the ongoing need for effective Covid-19 testing amid potential new waves of infection, increasing government initiatives for mass testing, and advancements in diagnostic technologies.

The demand for Covid-19 antigen testing kits is being driven by several growth factors. One of the pivotal drivers is the necessity for rapid and reliable testing solutions to manage and mitigate the spread of the virus. Governments and healthcare organizations across the globe continue to emphasize extensive testing as a crucial strategy for controlling Covid-19 outbreaks. Rapid antigen tests, in particular, offer the advantage of quick results, often within 15-30 minutes, which is essential for timely isolation and treatment measures. Moreover, the development of new variants of Covid-19 has necessitated continuous and widespread testing, further propelling the market growth.

Another significant factor contributing to market growth is the increasing adoption of home testing kits. With advancements in technology and an emphasis on convenience, more individuals are opting for home-based antigen tests. This trend is particularly prominent in developed regions where consumers have easy access to diagnostic tools and prefer the comfort and privacy of home testing. Additionally, governments and health agencies are endorsing home testing kits to reduce the burden on healthcare facilities and make testing more accessible to the general population.

Technological advancements are also playing a crucial role in the expansion of the Covid-19 antigen testing kits market. Innovations in diagnostic technologies have led to the development of more accurate, reliable, and user-friendly testing kits. Companies are focusing on improving the sensitivity and specificity of antigen tests to ensure they can detect even low viral loads effectively. Moreover, research into new materials and methodologies is resulting in the production of cost-effective testing kits, making them more affordable and widely available, especially in low and middle-income countries.

The introduction and widespread use of Covid 19 Rapid Antigen tests have revolutionized the approach to managing the pandemic. These tests are designed to quickly detect the presence of the virus, providing results in a matter of minutes. This rapid turnaround is crucial in settings where immediate decisions are needed, such as in airports, schools, and workplaces. The ability to deliver quick results helps in the timely isolation of positive cases, thereby reducing the potential for further transmission. Moreover, the ease of use associated with rapid antigen tests has made them a preferred option for mass screening programs, enabling large-scale testing with minimal logistical challenges.

Regionally, North America holds a significant share of the Covid-19 antigen testing kits market due to robust healthcare infrastructure, high testing rates, and substantial government funding. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period. This can be attributed to the increasing number of Covid-19 cases, rising awareness about the importance of testing, and supportive government initiatives. Countries like India, China, and Japan are leading the adoption of antigen tests, driven by large populations and ongoing efforts to control the pandemic.

Product Type Analysis

The Covid-19 antigen testing kits market can be segmented based on product type into Rapid Antigen Test Kits and Laboratory-Based Antigen Test Kits. Rapid Antigen Test Kits are designed for quick and straightforward use, often delivering results within minutes. These kits are highly valuable in settings where time is of the essence, such as airports, workplaces, and schools. The ease of use and rapid turnaround time have made rapid antigen tests a preferred choice for mass screening and point-of-care testing. Innovations in this segment are focused on enhancing sensitivity and reducing false negatives, which are critical for effective disease management.

Laboratory-Based Antigen Test Kits, on the other hand, are used primarily in clinical settings where higher accuracy and confirmation of rapid te

Covid-19 Testing Kits Market Outlook

The global market size for Covid-19 testing kits was valued at approximately $25 billion in 2023 and is projected to reach about $45 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5%. The growth in this market is driven by continuous advancements in testing technologies and the increasing need for mass testing to monitor and manage the spread of Covid-19.

A significant growth factor for the Covid-19 testing kits market is the persistent prevalence of the virus, which necessitates ongoing mass and targeted testing initiatives. Despite global vaccination efforts, new variants of the virus continue to emerge, making regular testing an essential part of public health strategies. Countries are adopting extensive testing protocols to quickly identify and isolate new cases, thereby preventing further outbreaks. These measures drive the demand for various types of Covid-19 testing kits, including PCR, antigen, and antibody tests.

Another major factor contributing to the market's growth is the technological advancements in testing methodologies. Innovations such as rapid antigen tests, at-home test kits, and next-generation sequencing have made Covid-19 testing more accessible, faster, and reliable. These technological advancements have not only reduced the time required for obtaining results but also increased the accuracy and ease of use of these tests. Additionally, the integration of AI and machine learning in diagnostic tools is expected to further revolutionize the market, offering real-time data analysis and better predictive capabilities.

Increased funding and investments from governments and private sectors have also played a crucial role in the market's expansion. Governments worldwide have been allocating substantial budgets to enhance their testing capabilities as part of their pandemic response strategies. This financial support has facilitated the scaling up of production capacities and the development of innovative testing solutions. Furthermore, collaborations between public health organizations and private companies have led to the rapid deployment of testing kits and infrastructure, ensuring a wider reach and availability.

The demand for COVID-19 Test Kits has surged in recent years due to the ongoing need for efficient and widespread testing. These kits have become a cornerstone in the global effort to manage and mitigate the spread of the virus. With the ability to provide accurate and timely results, COVID-19 Test Kits have empowered healthcare providers to make informed decisions regarding patient care and public health strategies. The development of these kits has been marked by significant advancements in diagnostic technology, enabling faster and more reliable testing processes. As the pandemic continues to evolve, the role of COVID-19 Test Kits remains critical in identifying and controlling outbreaks, thus safeguarding communities and supporting the return to normalcy.

Regionally, North America has been a major contributor to the market, primarily due to its advanced healthcare infrastructure and high testing rates. However, Asia Pacific is expected to witness the highest growth rate during the forecast period. The region's large population base, coupled with increased government initiatives for mass testing and rising healthcare expenditures, is driving the demand for Covid-19 testing kits. Europe, Latin America, and the Middle East & Africa also continue to be significant markets, driven by ongoing testing requirements and efforts to manage Covid-19 outbreaks.

Product Type Analysis

The Covid-19 testing kits market can be segmented based on product type into PCR kits, antigen kits, antibody kits, and others. PCR kits, which stand for polymerase chain reaction kits, have been the gold standard in Covid-19 testing due to their high accuracy and reliability. These kits detect the presence of viral RNA and are widely used in both clinical and laboratory settings. The high sensitivity of PCR kits makes them indispensable for confirming active infections, especially in symptomatic patients and high-risk populations.

Antigen kits have gained significant traction due to their ability to provide rapid results. These tests detect viral proteins and are often used for mass screening and in settings where immediate results are needed. Antigen tests are less sensitive than PCR tests but are highly valuable for point-

This dataset is no longer being updated as of 6/30/2022. It is being retained on the Open Data Portal for its potential historical interest.

In November 2020, the City of Cambridge began collecting and analyzing COVID-19 data from municipal wastewater, which can serve as an early indicator of increased COVID-19 infections in the city. The Cambridge Public Health Department and Cambridge Department of Public Works are using technology developed by Biobot, a Cambridge based company, and partnering with the Massachusetts Water Resources Authority (MWRA). This Cambridge wastewater surveillance initiative is funded through a $175,000 appropriation from the Cambridge City Council.

This dataset indicates the presence of the COVID-19 virus (measured as viral RNA particles from the novel coronavirus per ml) in municipal wastewater. The Cambridge site data here were collected as a 24-hour composite sample, which is taken weekly. The MWRA site data ere were collected as a 24-hour composite sample, which is taken daily. MWRA and Cambridge data are listed here in a single table.

An interactive graph of this data is available here: https://cityofcambridge.shinyapps.io/COVID19/?tab=wastewater

All areas within the City of Cambridge are captured across four separate catchment areas (or sewersheds) as indicated on the map viewable here: https://cityofcambridge.shinyapps.io/COVID19/_w_484790f7/BioBot_Sites.png. The North and West Cambridge sample also includes nearly all of Belmont and very small areas of Arlington and Somerville (light yellow). The remaining collection sites are entirely -- or almost entirely -- drawn from Cambridge households and workplaces.

Data are corrected for wastewater flow rate, which adjusts for population in general. Data listed are expected to reflect the burden of COVID-19 infections within each of the four sewersheds. A lag of approximately 4-7 days will occur before new transmissions captured in wastewater data would result in a positive PCR test for COVID-19, the most common testing method used. While this wastewater surveillance tool can provide an early indication of major changes in transmission within the community, it remains an emerging technology. In assessing community transmission, wastewater surveillance data should only be considered in conjunction with other clinical measures, such as current infection rates and test positivity.

Each location is selected because it reflects input from a distinct catchment area (or sewershed) as identified on the color-coded map. Viral data collected from small catchment areas like these four Cambridge sites are more variable than data collected from central collection points (e.g., the MWRA facility on Deer Island) where wastewater from dozens of communities are joined and mixed. Data from each catchment area will be impacted by daily activity among individuals living in that area (e.g., working from home vs. traveling to work) and by daytime activities that are not from residences (businesses, schools, etc.) As such, the Regional MWRA data provides a more stable measure of regional viral counts. COVID wastewater data for Boston North and Boston South regions is available at https://www.mwra.com/biobot/biobotdata.htm

The global Coronavirus Disease 2019 (COVID-19) Test Kit market size was valued at USD 15.75 billion in 2025 and is expected to expand at a compound annual growth rate (CAGR) of 5.0% from 2025 to 2033. The market growth is primarily driven by the increasing prevalence of COVID-19 infections, government initiatives for mass testing, and technological advancements in diagnostic methods. The market is segmented based on application into hospitals, scientific research, and diagnostic centers, with hospitals accounting for the largest share due to the high volume of patient testing. The competitive landscape of the COVID-19 Test Kit market is characterized by the presence of established players such as Thermo Fisher Scientific, LabCorp, Cepheid, Hologic, and Danaher. These companies hold significant market share and are actively involved in research and development to introduce innovative products. The market also includes regional players and emerging companies that are offering cost-effective and accessible testing solutions, particularly in emerging economies. Key trends in the market include the development of rapid and point-of-care testing devices, the use of artificial intelligence for data analysis, and the increasing adoption of molecular diagnostic techniques.

The COVID-19 Rapid Diagnostic Test market, valued at $11.84 billion in 2025, is experiencing a decline, reflected in its -10.90% CAGR. This contraction follows the peak demand during the pandemic's initial phases. While the acute phase of the pandemic has subsided, residual demand persists due to ongoing surveillance and the potential for future outbreaks. Market drivers include the need for rapid diagnosis to facilitate timely treatment and infection control, particularly in resource-constrained settings. However, the market is challenged by reduced government funding for mass testing programs and the transition towards routine healthcare practices post-pandemic. Several market segments are contributing to this dynamic landscape. Molecular tests, initially dominant, are witnessing a decline in favor of more cost-effective antigen tests, which offer faster results, though with potentially lower sensitivity. Hospitals and clinics remain the largest end-users, but the role of laboratories and diagnostic centers is also crucial for large-scale testing initiatives. Geographic distribution shows North America and Europe maintaining a significant market share, with the Asia-Pacific region exhibiting slower growth due to varied levels of healthcare infrastructure and testing protocols across different countries. The competitive landscape is fiercely contested, with major players like Abbott Laboratories, Thermo Fisher Scientific, and Roche leading the market due to their established distribution networks and diverse product portfolios. Smaller companies are focusing on niche applications and technological advancements to remain competitive. The forecast period (2025-2033) anticipates a continued, albeit moderated, decline in the market size. This is due to a combination of factors including the ongoing transition to endemic management strategies for COVID-19, the emergence of new variants requiring ongoing adaptation in diagnostic technology, and the cost-effectiveness of different testing methodologies. The market will likely experience a gradual shift towards a more sustainable market size, driven by a need for ongoing surveillance, routine testing in specific healthcare sectors, and preparedness for potential future outbreaks. Innovation in diagnostic technologies, such as improved point-of-care testing and the integration of artificial intelligence in diagnostic tools, could partially offset the overall market decline, creating opportunities for strategic partnerships and acquisitions within the industry. Recent developments include: In January 2023, the Government of Canada approved Artron Laboratories COVID-19 Antigen Home Test, a rapid self-testing of COVID antigens., In January 2023, the Government of Canada approved the Biomedomics Cov-scan Rapid Antigen Test for point-of-care tests.. Key drivers for this market are: Increasing Number of Approvals for New and Advanced COVID-19 Rapid Diagnostic Tests, Rising Cases of COVID-19 and its New Variants. Potential restraints include: Increasing Number of Approvals for New and Advanced COVID-19 Rapid Diagnostic Tests, Rising Cases of COVID-19 and its New Variants. Notable trends are: Molecular Tests Segment is Expected to Register a Significant CAGR Over the Forecast Period.

This dataset shows the results of the SARS-CoV-2 tests, which were carried out on pupils in baselstadt secondary schools. Individual tests are carried out at this school level. More information about testing in schools: https://www.coronavirus.bs.ch/testen/testen-in-schulen.htmlDieser Dataset has not been updated since the end of February 2022. Since mid-March 2022, data on tests in Basler schools will be published in a new dataset: https://data.bs.ch/explore/dataset/100183

Objectives: To investigate uptake of lateral flow testing, reporting of test results and psychological, contextual and socio-demographic factors associated with testing.Design: A series of four fortnightly online cross-sectional surveys.Setting: Data collected from 19 April 2021 to 2 June 2021.Participants: People living in England and Scotland, aged 18 years or over, excluding those who reported their most recent test was a polymerase chain reaction (PCR) test (n=6646, n≈1600 per survey).Main outcome measures: Having completed at least one lateral flow test (LFT) in the last 7 days.Results: We used binary logistic regressions to investigate factors associated with having taken at least one LFT. Increased uptake of testing was associated with being vaccinated (adjusted ORs (aORs)=1.52–2.45, 95% CI 1.25 to 3.07, analysed separately by vaccine dose), employed (aOR=1.94, 95% CI 1.63 to 2.32), having been out to work in the last week (aOR=2.30, 95% CI 1.94 to 2.73) and working in a sector that adopted LFT early (aOR=2.54, 95% CI 2.14 to 3.02) . Uptake was higher in people who reported cardinal COVID-19 symptoms in the last week (aOR=1.89, 95% CI 1.34 to 2.66). People who had heard more about LFTs (aOR=2.28, 95% CI 2.06 to 2.51) and knew they were eligible to receive regular LFTs (aOR=2.98, 95% CI 2.35 to 3.78) were also more likely to have tested. Factors associated with not taking a test included agreeing that you do not need to test for COVID-19 unless you have come into contact with a case (aOR=0.51, 95% CI 0.47 to 0.55).Conclusions: Uptake of lateral flow testing is low. Encouraging testing through workplaces and places of study is likely to increase uptake, although care should be taken not to pressurise employees and students. Increasing knowledge that everyone is eligible for regular asymptomatic testing and addressing common misconceptions may drive uptake.

BackgroundScreening programs that pre-emptively and routinely test population groups for disease at a massive scale were first implemented during the COVID-19 pandemic in a handful of countries. One of these countries was Greece, which implemented a mass self-testing program during 2021. In contrast to most other non-pharmaceutical interventions (NPIs), mass self-testing programs are particularly attractive for their relatively small financial and social burden, and it is therefore important to understand their effectiveness to inform policy makers and public health officials responding to future pandemics. This study aimed to estimate the number of deaths and hospitalizations averted by the program implemented in Greece and evaluate the impact of several operational decisions.MethodsGranular data from the mass self-testing program deployed by the Greek government between April and December 2021 were obtained. The data were used to fit a novel compartmental model that was developed to describe the dynamics of the COVID-19 pandemic in Greece in the presence of self-testing. The fitted model provided estimates on the effectiveness of the program in averting deaths and hospitalizations. Sensitivity analyses were used to evaluate the impact of operational decisions, including the scale of the program, targeting of sub-populations, and sensitivity (i.e., true positive rate) of tests.ResultsConservative estimates show that the program reduced the reproduction number by 4%, hospitalizations by 25%, and deaths by 20%, translating into approximately 20,000 averted hospitalizations and 2,000 averted deaths in Greece between April and December 2021.ConclusionMass self-testing programs are efficient NPIs with minimal social and financial burden; therefore, they are invaluable tools to be considered in pandemic preparedness and response.

Analysis of ‘Coronavirus (Covid-19): Mass tests at primary and lower secondary schools’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/100145-kanton-basel-stadt on 18 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset shows the class pools tested on SARS-CoV-2 from primary and lower secondary schools in basel urban schools. The number of pools tested and the test sensitivity rate per week are given. For more information on testing in schools: https://www.coronavirus.bs.ch/testen/testen-in-schulen.html

--- Original source retains full ownership of the source dataset ---

Coronavirus Rapid Testing Kits Market Outlook

The global market size for Coronavirus Rapid Testing Kits in 2023 is estimated to be valued at USD 5.2 billion and is projected to reach USD 8.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.1% during the forecast period. This growth is primarily attributed to the continued need for rapid and reliable testing solutions amid ongoing waves of infection and the increasing emphasis on early detection and containment strategies.

The growth factors contributing to the expansion of the Coronavirus Rapid Testing Kits market are manifold. Firstly, the persistent threat of new variants of the virus necessitates the development and distribution of advanced testing kits that can quickly identify infections and guide timely treatment. Governments and healthcare institutions worldwide are investing heavily in testing infrastructure to mitigate the spread of the virus. This substantial financial backing is a significant driver for market growth. Additionally, the increased awareness and adoption of testing kits among the general population have led to a higher demand for these products, further driving market expansion.

Secondly, technological advancements in diagnostic tools have greatly enhanced the accuracy and speed of rapid testing kits, making them more reliable and user-friendly. Innovations in molecular diagnostics, such as PCR and antigen tests, have played a crucial role in the increased uptake of these testing kits. Such advancements are not only improving the performance of tests but are also reducing the costs associated with them, making rapid testing more accessible to developing regions. The growing emphasis on point-of-care testing is also propelling the market forward as it facilitates immediate results and faster clinical decision-making.

Moreover, the strategic initiatives taken by key market players, including collaborations, mergers, and acquisitions, have significantly contributed to market growth. Companies are focusing on expanding their product portfolios and increasing their market presence through these strategic moves. The competitive landscape has become increasingly dynamic, with both established players and new entrants striving to introduce innovative testing solutions. This competitive environment fosters continuous improvements and innovations, which, in turn, drive market growth.

Regionally, the market outlook shows significant variations. North America remains a dominant player due to its advanced healthcare infrastructure and substantial government funding for healthcare initiatives. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, driven by the large population base, rising healthcare awareness, and increased government initiatives for mass testing. Europe also shows steady growth, supported by robust healthcare systems and increased testing capacities. The Middle East & Africa and Latin America are expected to witness moderate growth due to improving healthcare infrastructure and rising awareness about early detection and testing.

The COVID 19 IgM IgG Antibody Rapid Test Kits Sales have seen a remarkable surge as these kits provide crucial insights into the immune response against the virus. These antibody tests are instrumental in determining whether an individual has been previously infected with COVID-19 and has developed antibodies, offering valuable data for epidemiological studies and vaccine efficacy assessments. The demand for these kits is driven by the need for comprehensive serological surveys and the evaluation of long-term immunity post-vaccination. As healthcare systems across the globe strive to understand the dynamics of immunity, the sales of IgM and IgG antibody test kits are expected to grow, supported by ongoing research and public health initiatives aimed at monitoring population immunity levels.

Product Type Analysis

The product type segment of the Coronavirus Rapid Testing Kits market is broadly categorized into Antigen Test Kits, Antibody Test Kits, and PCR Test Kits. Antigen test kits are widely used for their ability to provide results within minutes, making them ideal for mass testing scenarios, such as airport screenings and large gatherings. These kits detect the presence of viral proteins and are favored for their rapid turnaround time, which is crucial for timely isolation and treatment of infected individuals. The growing n

United States SB: MA: COVID Test/Vaccine: Negative COVID Test: Yes data was reported at 5.900 % in 11 Apr 2022. This records a decrease from the previous number of 6.600 % for 04 Apr 2022. United States SB: MA: COVID Test/Vaccine: Negative COVID Test: Yes data is updated weekly, averaging 8.750 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 18.400 % in 03 Jan 2022 and a record low of 3.500 % in 14 Mar 2022. United States SB: MA: COVID Test/Vaccine: Negative COVID Test: Yes data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

Analysis of ‘Coronavirus (Covid-19): Mass tests at upper secondary schools’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/100153-kanton-basel-stadt on 15 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset shows the results of the SARS-CoV-2 tests carried out at Schüler:innen and teachers in lower secondary schools. Individual tests are carried out at this school level. For more information on testing in schools: https://www.coronavirus.bs.ch/testen/testen-in-schulen.html

--- Original source retains full ownership of the source dataset ---

United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data was reported at 77.600 % in 11 Apr 2022. This records an increase from the previous number of 73.900 % for 04 Apr 2022. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data is updated weekly, averaging 72.700 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 77.600 % in 11 Apr 2022 and a record low of 65.500 % in 03 Jan 2022. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data was reported at 13.200 % in 11 Apr 2022. This records a decrease from the previous number of 14.100 % for 04 Apr 2022. SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data is updated weekly, averaging 14.050 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 19.100 % in 14 Mar 2022 and a record low of 9.000 % in 22 Nov 2021. SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

COVID-19 plasma samples spectrometry datasets for machine learning input. Used in the work of article Covid-19 automated diagnosis and risk assessment through Metabolomics and Machine Learning, currently under submittion.

Abstract:

COVID-19 is still placing a heavy health and financial burden worldwide. Impairments in patient screening and risk management play a fundamental role on how governments and authorities are directing resources, planning reopening, as well as sanitary countermeasures, especially in regions where poverty is a major component in the equation. An efficient diagnostic method must be highly accurate, while having a cost-effective profile. We combined a machine learning-based algorithm with mass spectrometry to create an expeditious platform that discriminate COVID-19 in plasma samples within minutes, while also providing tools for risk assessment, to assist healthcare professionals in patient management and decision-making. A cross-sectional study with 815 patients (442 COVID-19, 350 controls and 23 COVID-19 suspicious) was enrolled from three Brazilian epicenters from April to July 2020. We were able to elect and identify 19 molecules that are related to the disease’s pathophysiology and several discriminating features to patient’s health-related outcomes. The method applied for COVID-19 diagnosis showed specificity >96% and sensitivity >83%, and specificity >80% and sensitivity >85% during risk assessment, both from blinded data. Our method introduced a new approach for COVID-19 screening, providing the indirect detection of infection through metabolites and contextualizing the findings the disease’s pathophysiology. The pairwise analysis of biomarkers brought robustness to the model developed using Machine Learning algorithms, transforming this screening approach in a tool with great potential for real-world application.

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.