Italy experienced a sharp rise in the number of positive infections shortly after confirming its 100th coronavirus case. In the space of just 17 days, the number of cases in Italy had soared to more than 12,000. In comparison, the spread of the virus was much slower in Japan.

The COVID-19 outbreak in Italy Italy was the first European nation to be severely impacted by COVID-19. There had been approximately 35,400 coronavirus-related deaths recorded in the country as of August 17, 2020. Following a two-month lockdown period, restrictions in Italy were eased in early May, and citizens are now permitted to travel between regions and abroad. However, the risk of a resurgence remains, and the country’s state of emergency has been extended until October 15, 2020. It is looking increasingly likely that restrictions will not be completely lifted until a vaccine for the disease is discovered.

Pfizer confident of vaccine success Pfizer and BioNTech are jointly developing one candidate vaccine that is under clinical evaluation. In July 2020, the two companies announced an agreement with the U.S. government that will bring millions of doses to the American people. The BNT162 mRNA-based vaccine is currently being produced even though it has not received regulatory approval from the FDA. This is a risky approach and is one that could cost the companies millions of dollars should the vaccine be rejected. However, if regulatory approval is received, the safe and effective vaccine can be shipped quickly.

Linear regression models for growth in mean daily COVID-19-attributed deaths before versus after implementation of the first statewide social distancing measure and statewide restrictions on internal movement, assuming a range of expected days between symptom onset and death.

The coronavirus (COVID-19) pandemic, has had a significant impact on the global economy. In 2020, global Gross Domestic Product (GDP) decreased by *** percent, while the forecast initially was *** percent GDP growth. As the world's governments are working towards a fast economic recovery, the GDP increased again in 2021 by *** percent. Global GDP increased by over ***** percent in 2022, but it is still not clear to what extent Russia's war in Ukraine will impact the global economy. Global GDP growth is expected to slow somewhat in 2023.

Context

This data was collected as part of a university research paper where COVID-19 cases were analysed using a cross-sectional regression model as at 17th May 2020. In order to better understand COVID-19 cases growth at a country level I decided to create a dataset containing key dates in the progression of the virus globally.

Content

210 rows, 6 columns.

This dataset contains data relating to COVID-19 cases for 210 countries globally. Data was collected using the most recent and reliable information as at 17th May 2020. The majority of data was collected from Worldometer. https://www.worldometers.info/coronavirus/#countries

This dataset contains dates for the 1st coronavirus case, 100th coronavirus case, and (50th coronavirus case per 1 million people) for 210 countries. Data is also provided for the number of days between the 1st case and the 100th as well as the 1st case and the 50th per 1 million people.

Data prior to 15th February 2020, was not easily accessible at the country level from Worldometer. Therefore any dates prior to 15th February 2020 were not sourced from Worldometer but reputable government and local media sources.

Blanks (null values) indicate that the country in question has not reached either 50 coronavirus cases per 1 million people or 100 coronavirus cases. These were left blank.

Acknowledgements

I would like to acknowledge Worldometer for providing the vast majority of the data in this file. Worldometer is a website that provides real time statistics on topics such as coronavirus cases. Its sources include government official reports as well as trusted local media sources all of which are referenced on their website.

Inspiration

Hopefully this data can be used to better understand the growth of COVID-19 cases globally.

ByteDance's Lark app experienced an year-on-year increase in downloads of over 6,000 percent from January 22 through February 20, amid the COVID-19 outbreak in China. The other two apps, Lark's more heavy-weight competitors DingTalk and WeChat Work, also benefitted from the influx in remote working in China.

The effects of social capital on infections and the spread of COVID-19.

The global coronavirus diagnostics market is projected to reach a valuation of USD 15.2 billion by 2033, growing at a compound annual growth rate (CAGR) of 6.8% from 2025 to 2033.

ABSTRACT Objective: To analyse the measures adopted by countries that have shown control over the transmission of coronavirus disease 2019 (COVID-19) and how each curve of accumulated cases behaved after the implementation of those measures. Methods: The methodology adopted for this study comprises three phases: systemizing control measures adopted by different countries, identifying structural breaks in the growth of the number of cases for those countries, and analyzing Brazilian data in particular. Results: We noted that China (excluding Hubei Province), Hubei Province, and South Korea have been effective in their deceleration of the growth rates of COVID-19 cases. The effectiveness of the measures taken by these countries could be seen after 1 to 2 weeks of their application. In Italy and Spain, control measures at the national level were taken at a late stage of the epidemic, which could have contributed to the high propagation of COVID-19. In Brazil, Rio de Janeiro and São Paulo adopted measures that could be effective in slowing the propagation of the virus. However, we only expect to see their effects on the growth of the curve in the coming days. Conclusion: Our results may help decisionmakers in countries in relatively early stages of the epidemic, especially Brazil, understand the importance of control measures in decelerating the growth curve of confirmed cases.

The global COVID-19 sample collection tools market is projected to reach a valuation of USD 5.8 billion by 2033, growing at a compound annual growth rate (CAGR) of 6.2% from 2025 to 2033.

Updates

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

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

• April 9, 2020

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

• April 20, 2020

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

• April 29, 2020

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

• September 1st, 2020

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

• February 12, 2021

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

• February 16, 2021

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

  Overview

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

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

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

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

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

Queries

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

• Filter cases by state here

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

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

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

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

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

Interactive

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

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

Interactive Embed Code

<iframe title="USA counties (2018) choropleth map Mapping COVID-19 cases by county" aria-describedby="" id="datawrapper-chart-nRyaf" src="https://datawrapper.dwcdn.net/nRyaf/10/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important;" height="400"></iframe><script type="text/javascript">(function() {'use strict';window.addEventListener('message', function(event) {if (typeof event.data['datawrapper-height'] !== 'undefined') {for (var chartId in event.data['datawrapper-height']) {var iframe = document.getElementById('datawrapper-chart-' + chartId) || document.querySelector("iframe[src*='" + chartId + "']");if (!iframe) {continue;}iframe.style.height = event.data['datawrapper-height'][chartId] + 'px';}}});})();</script>

Caveats

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

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

Attribution

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

Due to the coronavirus, the estimated number of paid SVoD users worldwide by the end of 2020 has been increaed by ** million, according to the most recently available data. Previously, it was anticipated that there would be just over *** million SVoD subscribers globally. However, the pandemic has led to an increase in online TV and video consumption as the coronavirus has taken hold in countries around the world and consumers are confined to their homes. As a result, the source reevaluated its estimate and now suggests that the number could amount to *** million by the end of the year.

This dataset contains the predicted prices of the asset Coronavirus 2019 over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This a data about the corona virus COVID-19. It contains the actual reported data. Also, it includes the predicted COVID-19 data in the future based on a model developed to predict in the future. The model used will be published in one of the journals later and will be found on my profile with title "Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis". The daily folder contains the daily data. The predicted folder contains the predicted data for each country. The total cases folder contains the total cases for each country. he section folder contains a latex code for plotting the figures for each country. Also the source file from European Centre for Disease Prevention and Control is included. More updated files available in the website of European Centre for Disease Prevention and Control.

Dataset

This dataset was created by Robert Badgett

Released under CC BY-NC-SA 4.0

Contents

This dataset contains the predicted prices of the asset Covid-2025 over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Coronavirus Testing Kits Market Outlook

As of 2023, the global market size for Coronavirus Testing Kits is estimated to be approximately $18.7 billion, and it is projected to reach $25.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 3.5%. This steady growth is driven primarily by the ongoing need for effective and efficient testing solutions to manage and mitigate the spread of COVID-19 and other emerging infectious diseases.

One of the primary growth factors in the Coronavirus Testing Kits market is the continuous mutation and evolution of the virus, which necessitates ongoing testing to detect new variants promptly. Governments and healthcare organizations worldwide are investing heavily in robust testing infrastructures to quickly identify and isolate infected individuals. This proactive approach is essential to contain outbreaks and prevent healthcare systems from becoming overwhelmed. Additionally, the increasing availability of at-home testing kits, which provide convenience and reduce the risk of exposure in clinical settings, is another significant driver.

Technological advancements in diagnostic tools have also significantly propelled the market. Innovations such as rapid test kits that deliver results within minutes and high-throughput testing systems that can process thousands of samples daily are making testing more accessible and efficient. The integration of artificial intelligence and machine learning in data analysis and result interpretation is further enhancing the accuracy and speed of these testing kits. Moreover, ongoing research and development efforts aimed at improving the sensitivity and specificity of tests continue to open new avenues for market growth.

Another critical factor contributing to the market's expansion is the global emphasis on preparedness for future pandemics. The COVID-19 pandemic has underscored the importance of having a well-equipped diagnostic framework in place. Consequently, there is a heightened focus on developing versatile testing kits that can be quickly adapted to detect various pathogens. This preparedness not only aids in handling COVID-19 but also serves as a valuable asset in combating other infectious diseases that may arise in the future.

The role of Covid 19 Medical Testing Kits has been pivotal in the global response to the pandemic. These kits, encompassing a range of diagnostic tools, have enabled healthcare professionals to swiftly identify and isolate cases, thereby curbing the spread of the virus. The development and deployment of these testing kits have been supported by significant investments from both public and private sectors, highlighting their critical importance in managing the pandemic. As the virus continues to evolve, the adaptability of these kits to detect new variants remains a top priority for manufacturers and researchers alike. The ongoing innovation in this field is not only enhancing the accuracy and speed of testing but also ensuring that testing remains a cornerstone of public health strategies worldwide.

Regionally, North America holds a significant share of the market due to its advanced healthcare infrastructure and substantial government funding for healthcare initiatives. Europe follows closely, driven by similar factors and strong regulatory support. The Asia Pacific region is expected to exhibit the highest growth rate due to increasing healthcare investments and the rising prevalence of infectious diseases. Latin America and the Middle East & Africa regions are also witnessing steady growth, albeit at a slower pace, primarily due to improvements in healthcare access and infrastructure.

Product Type Analysis

The Coronavirus Testing Kits market is segmented by product type into PCR Kits, Antigen Kits, Antibody Kits, and Others. PCR kits dominate the market due to their high accuracy and reliability in detecting the virus's genetic material. These kits are considered the gold standard for COVID-19 testing, providing definitive results. The continuous demand for PCR kits is fueled by their use in both clinical settings and research laboratories, where precise detection is crucial for patient management and epidemiological studies.

Antigen kits, on the other hand, offer a faster and more convenient testing solution, which is particularly beneficial for large-scale screening programs. They are less expensive and easier to administer than PCR tests, making them ideal for q

Sales of larger package sizes of cannabis flower grew at larger rates during the outbreak of coronavirus in Washington state in March 2020, suggesting that consumers were stockpiling in anticipation of social distancing requirements. The largest growth (106%) was seen in the 28 gram (1 ounce) package size.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Averaged temperatures and estimated exponential rates of US regions.

Estimates of the growth rate and doubling time during the growth phase in Madrid, Catalonia, and Spain.

Estimates of the growth rate and doubling time during the growth phase in Lombardy and Italy.