Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

BackgroundMandatory COVID-19 certification, showing proof of vaccination, negative test, or recent infection to access to public venues, was introduced at different times in the four countries of the UK. We aim to study its effects on the incidence of cases and hospital admissions.MethodsWe performed Negative binomial segmented regression and ARIMA analyses for four countries (England, Northern Ireland, Scotland and Wales), and fitted Difference-in-Differences models to compare the latter three to England, as a negative control group, since it was the last country where COVID-19 certification was introduced. The main outcome was the weekly averaged incidence of COVID-19 cases and hospital admissions.ResultsCOVID-19 certification led to a decrease in the incidence of cases and hospital admissions in Northern Ireland, as well as in Wales during the second half of November. The same was seen for hospital admissions in Wales and Scotland during October. In Wales the incidence rate of cases in October already had a decreasing tendency, as well as in England, hence a particular impact of COVID-19 certification was less obvious. Method assumptions for the Difference-in-Differences analysis did not hold for Scotland. Additional NBSR and ARIMA models suggest similar results, while also accounting for correlation in the latter. The assessment of the effect in England itself leads one to believe that this intervention might not be strong enough for the Omicron variant, which was prevalent at the time of introduction of COVID-19 certification in the country.ConclusionsMandatory COVID-19 certification reduced COVID-19 transmission and hospitalizations when Delta predominated in the UK, but lost efficacy when Omicron became the most common variant.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

In late-November 2021, the Omicron variant of SARS-CoV-2 (the virus which causes COVID-19) was designated as a variant of concern by the World Health Organization due to fears about a higher transmissibility from the variant and a possible decrease in the effectiveness of vaccines against it. The Omicron variant has been detected in multiple countries since the discovery, and as of April 1, 2022, almost 965 thousand cases have been sequenced in the United Kingdom.

Time series of Covid-19 Case Fatality Rate (CFR) for Spain, the United Kingdom, and the United States.

Snapshot img

Europe Coronavirus Test Kits Market Size 2024-2028

The coronavirus test kits market in Europe size is forecast to decrease by USD 1.89 billion at a CAGR of -72.5% between 2023 and 2028.

The European coronavirus test kits market is experiencing significant growth due to the increasing demand for rapid diagnostic solutions. The emergence of SARS-CoV-2 variants, such as the Delta variant, has highlighted the importance of accurate and timely testing. Oropharyngeal swabs, nasal swabs, and sputum samples are commonly used for diagnosing COVID-19 infections. Point-of-Care (PoC) kits have gained popularity due to their convenience and quick results. However, the accuracy of diagnostic tests remains a challenge, with the Indian Council of Medical Research (ICMR) and the Health Ministry reporting false positives and negatives. The market is expected to continue its expansion as the world navigates the ongoing pandemic.

What will be the Size of the Market During the Forecast Period?

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The European coronavirus test kits market is witnessing significant growth due to the ongoing pandemic caused by SARS-CoV-2. The demand for test kits is driven by the need for early detection and rapid screening of infected individuals to prevent the spread of the virus within communities. According to the medical device database from GlobalData, RT-PCR tests remain the gold standard for diagnosing SARS-CoV-2 infection. These tests detect viral genetic material from human nasal samples, providing accurate results. However, the time-consuming nature of these tests and the requirement for specialized equipment have led to the emergence of alternative solutions, such as SARS-CoV-2 antigen tests.
Moreover, rapid antigen tests, also known as point-of-care (PoC) kits, offer user-friendly solutions for healthcare systems. These tests provide results within minutes, making them ideal for mass screening in various settings, including schools, workplaces, and airports. The Delta variant and the emerging Omicron variant of SARS-CoV-2 have added to the urgency for effective testing solutions. The European Union has been proactive in addressing this need, with initiatives such as the European Health Union and the EU Digital COVID Certificate system. The European coronavirus test kits market is expected to continue its growth trajectory, driven by the ongoing pandemic and the need for regular testing to ensure public health and safety

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Government
  Non government


Type

  Rapid test kit
  RT-PCR
  Others


Geography

  Europe

    Germany
    UK
    France

By End-user Insights

The government segment is estimated to witness significant growth during the forecast period.

In Europe, various diagnostic techniques are utilized to identify COVID-19 cases, with WHO recommending that countries with limited testing capacity or inexperienced national laboratories send their initial positive and negative samples to five referral laboratories in Europe for confirmatory testing. These laboratories include the German coronavirus diagnostic working group at Charite and Robert Koch Institute in Berlin, Erasmus Medical Center in Rotterdam, the Institute Pasteur in Paris, and the Respiratory Virus Unit at Public Health England. Additionally, several other laboratories in Belgium, Luxembourg, the Netherlands, and Spain offer diagnostic testing support. In the UK, Public Health England (PHE) regional laboratories provide testing facilities alongside WHO referral laboratories. As the world awaits vaccinations and booster doses, public awareness remains crucial. During the flu season, mask mandates and social distancing measures continue to be essential preventative measures.

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Market Dynamics

Our Europe Coronavirus Test Kits Market researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in the adoption of the European coronavirus Test Kits Market?

Rising adoption of rapid coronavirus test kits is the key driver of the market.

In Europe, the coronavirus pandemic has put immense pressure on healthcare systems, particularly in terms of diagnostic capabilities. To mitigate this challenge, European governments have prioritized expanding their testing capacity through various means. In 2022, there was a significant push to distribute coronavirus test kits acro

Higher Education Graduate Outcomes Statistics: UK, 2020/21 This Statistical Bulletin is the annual first release of Graduate Outcomes survey data. These experimental statistics cover UK higher education providers (HEPs) including alternative providers (APs) and further education colleges (FECs) in England, Wales and Northern Ireland. Data is collected approximately 15 months after HE course completion. The 2020/21 Graduate Outcomes cohort finished their qualifications in the second academic year affected by COVID-19. While Cohort A finished their qualifications during late summer and early autumn 2020, in a period of relatively loose restrictions, restrictions began to increase over the course of the academic year. Cohort B graduated into a period of short national lockdowns, followed by the start of the second national lockdown in January 2021. Cohort C likewise graduated in lockdown, but the progress of the vaccination programme led to a gradual easing of restrictions as spring progressed; by the time Cohort D, the largest Graduate Outcomes cohort, began to finish their qualifications in May 2021, most adults had been offered a first vaccine dose, and restrictions were gradually being phased out across the UK. The circumstances under which 2020/21 graduates were surveyed were quite different. As surveying for Cohort A opened in December 2021, Omicron variant cases were rising and new guidance was being issued requiring masks in indoor spaces and encouraging people to work from home where possible, the new restrictions were considerably more lenient than those which were introduced a year previously. By the time the Cohort B survey period opened in March 2022, all legal restrictions had been lifted in England, and remaining restrictions were phased out in other nations over the next few months. Although COVID cases rose from the start of June to a summer peak in early July, no legal restrictions were in place during the survey periods for Cohorts C and D. An insight briefing provides further detail on analysis undertaken to explore the impact of the pandemic, and the conclusions identified. This statistical bulletin has been produced by HESA in collaboration with statisticians from the Office for Students, the Department for Education, the Welsh Government, the Scottish Government and the Department for the Economy Northern Ireland. It has been released according to the arrangements approved by the UK Statistics Authority.

Results for Covid-19 simulation with data from Brazil, Spain, United Kingdom, and United States.

Epidemiological time series of Covid-19 for Spain, the United Kingdom, and the United States.

COVID-19 infection rates remain high in South Africa. Clinical prediction models may be helpful for rapid triage, and supporting clinical decision making, for patients with suspected COVID-19 infection. The Western Cape, South Africa, has integrated electronic health care data facilitating large-scale linked routine datasets. The aim of this study was to develop a machine learning model to predict adverse outcome in patients presenting with suspected COVID-19 suitable for use in a middle-income setting. A retrospective cohort study was conducted using linked, routine data, from patients presenting with suspected COVID-19 infection to public-sector emergency departments (EDs) in the Western Cape, South Africa between 27th August 2020 and 31st October 2021. The primary outcome was death or critical care admission at 30 days. An XGBoost machine learning model was trained and internally tested using split-sample validation. External validation was performed in 3 test cohorts: Western Cape patients presenting during the Omicron COVID-19 wave, a UK cohort during the ancestral COVID-19 wave, and a Sudanese cohort during ancestral and Eta waves. A total of 282,051 cases were included in a complete case training dataset. The prevalence of 30-day adverse outcome was 4.0%. The most important features for predicting adverse outcome were the requirement for supplemental oxygen, peripheral oxygen saturations, level of consciousness and age. Internal validation using split-sample test data revealed excellent discrimination (C-statistic 0.91, 95% CI 0.90 to 0.91) and calibration (CITL of 1.05). The model achieved C-statistics of 0.84 (95% CI 0.84 to 0.85), 0.72 (95% CI 0.71 to 0.73), and 0.62, (95% CI 0.59 to 0.65) in the Omicron, UK, and Sudanese test cohorts. Results were materially unchanged in sensitivity analyses examining missing data. An XGBoost machine learning model achieved good discrimination and calibration in prediction of adverse outcome in patients presenting with suspected COVID19 to Western Cape EDs. Performance was reduced in temporal and geographical external validation.

Time-varying model parameters fitted for Covid-19 in Spain, United Kingdom, and United States.

BackgroundUneven vaccination and less resilient health care systems mean hospitals in LMICs are at risk of being overwhelmed during periods of increased COVID-19 infection. Risk-scores proposed for rapid triage of need for admission from the emergency department (ED) have been developed in higher-income settings during initial waves of the pandemic.MethodsRoutinely collected data for public hospitals in the Western Cape, South Africa from the 27th August 2020 to 11th March 2022 were used to derive a cohort of 446,084 ED patients with suspected COVID-19. The primary outcome was death or ICU admission at 30 days. The cohort was divided into derivation and Omicron variant validation sets. We developed the LMIC-PRIEST score based on the coefficients from multivariable analysis in the derivation cohort and existing triage practices. We externally validated accuracy in the Omicron period and a UK cohort.ResultsWe analysed 305,564 derivation, 140,520 Omicron and 12,610 UK validation cases. Over 100 events per predictor parameter were modelled. Multivariable analyses identified eight predictor variables retained across models. We used these findings and clinical judgement to develop a score based on South African Triage Early Warning Scores and also included age, sex, oxygen saturation, inspired oxygen, diabetes and heart disease. The LMIC-PRIEST score achieved C-statistics: 0.82 (95% CI: 0.82 to 0.83) development cohort; 0.79 (95% CI: 0.78 to 0.80) Omicron cohort; and 0.79 (95% CI: 0.79 to 0.80) UK cohort. Differences in prevalence of outcomes led to imperfect calibration in external validation. However, use of the score at thresholds of three or less would allow identification of very low-risk patients (NPV ≥0.99) who could be rapidly discharged using information collected at initial assessment.ConclusionThe LMIC-PRIEST score shows good discrimination and high sensitivity at lower thresholds and can be used to rapidly identify low-risk patients in LMIC ED settings.