COVID-19Plots and analysis relating to the coronavirus pandemic. Includes five sets of plots and associated R code to generate them.1) HeatmapsUpdated every few days - heatmaps of COVID-19 case and death trajectories for Local Authorities (or equivalent) in England, Wales, Scotland, Ireland and Germany.2) All cause mortalityUpdated on Tuesday (for England & Wales), Wednesday (for Scotland) and Friday (for Northern Ireland) - analysis and plots of weekly all-cause deaths in 2020 compared to previous years by country, age, sex and region. Also a set of international comparisons using data from mortality.org3) ExposuresNo longer updated - mapping of potential COVID-19 mortality exposure at local levels (LSOAs) in England based on the age-sex structure of the population and levels of poor health.There is also a Shiny app which creates slightly lower resolution versions of the same plots online, which you can find here: https://victimofmaths.shinyapps.io/covidmapper/, on GitHub https://github.com/VictimOfMaths/COVIDmapper and uploaded to this record4) Index of Multiple Deprivation No longer updated - preliminary analysis of the inequality impacts of COVID-19 based on Local Authority level cases and levels of deprivation. 5) Socioeconomic inequalities. No longer updated (unless ONS release more data) - Analysis of published ONS figures of COVID-19 and other cause mortality in 2020 compared to previous years by deprivation decile.Latest versions of plots and associated analysis can be found on Twitter: https://twitter.com/victimofmathsThis work is described in more detail on the UK Data Service Impact and Innovation Lab blog: https://blog.ukdataservice.ac.uk/visualising-high-risk-areas-for-covid-19-mortality/Adapted from data from the Office for National Statistics licensed under the Open Government Licence v.1.0.http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

On March 4, 2020, the first death as a result of coronavirus (COVID-19) was recorded in the United Kingdom (UK). The number of deaths in the UK has increased significantly since then. As of January 13, 2023, the number of confirmed deaths due to coronavirus in the UK amounted to 202,157. On January 21, 2021, 1,370 deaths were recorded, which was the highest total in single day in the UK since the outbreak began.

Number of deaths among highest in Europe
The UK has had the highest number of deaths from coronavirus in western Europe. In terms of rate of coronavirus deaths, the UK has recorded 297.8 deaths per 100,000 population.

Cases in the UK The number of confirmed cases of coronavirus in the UK was 24,243,393 as of January 13, 2023. The South East has the highest number of first-episode confirmed cases of the virus in the UK with 3,123,050 cases, while London and the North West have 2,912,859 and 2,580,090 confirmed cases respectively. As of January 16, the UK has had 50 new cases per 100,000 in the last seven days.

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

Context

• Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus SARS-CoV2.
• Person to person transmission occurs via several different modes, mainly when people are in close proximity to one another through respiratory droplets.
• Mitigations by various countries have been put into place to limit the spread of this virus.

Content

• ConfirmedCasesByDateReported.csv
• ConfirmedCasesBySpecimenDate.csv
• Deaths.csv
• PatientNewAdmissions.csv
• PatientsInHospital.csv
• PatientsMVBeds.csv
• PCRTesting.csv
• Vaccinations.csv
• VaccinationsDaily.csv

Acknowledgements and Collection Methodology

Data downloaded from https://coronavirus.data.gov.uk

Version

• Version 11 - 25 - Various Files Updated.
• Version 10 - Added VaccinationsDaily File, data upto and including the 20th Jan 2021.
• Version 9 - Updated Deaths file, data upto and including the 20th Jan 2021.
• Version 8 - Updated ConfirmedCasesByDateReported and ConfirmedCasesBySpecimenDate files, data upto and including the 17th to 19th Jan 2021 respectively.
• Version 7 - Updated PatientNewAdmissions, PatientsInHospital and PatientsMVBeds files, data upto and including the 12th to 15th Jan 2020 depending on file.
• Version 6 - Updated PCR Testing file, data upto and including the 14th Jan 2021.
• Version 4 - Updated Vaccinations file, data upto and including the 3rd Jan 2021.
• Version 3 - Updated to include data unto and including the 28th December 2020. Additionally added data on the progress of Vaccinations.
• Version 2 - Updated to include data unto and including the 3rd November 2020.

This dataset shows the provisional COVID-19 Death registrations and occurrences by local authority and health board in England and Wales. This dataset has been prepared by Office for National Statistics.

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.

COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.

Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.

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

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. The number of cases in the UK increased significantly at the end of 2021. On January 13, 2023, the number of confirmed cases in the UK amounted to 24,243,393. COVID deaths among highest in Europe There were 202,157 confirmed coronavirus deaths in the UK as of January 13, 2023. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Current infection rate in Europe The current infection rate in the UK was 50 cases per 100,000 population in the last seven days as of January 16. San Marino had the highest seven day rate of infections in Europe at 336.

This publication was archived on 12 October 2023. Please see the Viral Respiratory Diseases (Including Influenza and COVID-19) in Scotland publication for the latest data. This dataset provides information on number of new daily confirmed cases, negative cases, deaths, testing by NHS Labs (Pillar 1) and UK Government (Pillar 2), new hospital admissions, new ICU admissions, hospital and ICU bed occupancy from novel coronavirus (COVID-19) in Scotland, including cumulative totals and population rates at Scotland, NHS Board and Council Area levels (where possible). Seven day positive cases and population rates are also presented by Neighbourhood Area (Intermediate Zone 2011). Information on how PHS publish small are COVID figures is available on the PHS website. Information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system is provided in this publication. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. COVID-19 was declared a pandemic by the World Health Organisation on 12 March 2020. We now have spread of COVID-19 within communities in the UK. Public Health Scotland no longer reports the number of COVID-19 deaths within 28 days of a first positive test from 2nd June 2022. Please refer to NRS death certificate data as the single source for COVID-19 deaths data in Scotland. In the process of updating the hospital admissions reporting to include reinfections, we have had to review existing methodology. In order to provide the best possible linkage of COVID-19 cases to hospital admissions, each admission record is required to have a discharge date, to allow us to better match the most appropriate COVID positive episode details to an admission. This means that in cases where the discharge date is missing (either due to the patient still being treated, delays in discharge information being submitted or data quality issues), it has to be estimated. Estimating a discharge date for historic records means that the average stay for those with missing dates is reduced, and fewer stays overlap with records of positive tests. The result of these changes has meant that approximately 1,200 historic COVID admissions have been removed due to improvements in methodology to handle missing discharge dates, while approximately 820 have been added to the cumulative total with the inclusion of reinfections. COVID-19 hospital admissions are now identified as the following: A patient's first positive PCR or LFD test of the episode of infection (including reinfections at 90 days or more) for COVID-19 up to 14 days prior to admission to hospital, on the day of their admission or during their stay in hospital. If a patient's first positive PCR or LFD test of the episode of infection is after their date of discharge from hospital, they are not included in the analysis. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. Data visualisation of Scottish COVID-19 cases is available on the Public Health Scotland - Covid 19 Scotland dashboard. Further information on coronavirus in Scotland is available on the Scottish Government - Coronavirus in Scotland page, where further breakdown of past coronavirus data has also been published.

11th January 2020 Change to vaccination data made available by UK gov - now just cumulative number of vaccines delivered are available for both first and second doses. For the devolved nations the cumulative totals are available for the dates from when given, however for the UK as a whole the total doses given is just on the last date of the index, regardless of when those vaccines were given.

4th January 2020 VACCINATION DATA ADDED - New and Cumulative First Dose Vaccination Data added to UK_National_Total_COVID_Dataset.csv and UK_Devolved_Nations_COVID_Dataset.csv

2nd December 2020:

NEW population, land area and population density data added in file NEW_Official_Population_Data_ONS_mid-2019.csv. This data is scraped from the Office for National Statistics and covers the UK, devolved UK nations, regions and local authorities (boroughs).

20th November 2020:

With European governments struggling with a 'second-wave' of rising cases, hospitalisations and deaths resulting from the SARS-CoV-2 virus (COVID-19), I wanted to make a comparative analysis between the data coming out of major European nations since the start of the pandemic.

I started by creating a Sweden COVID-19 dataset and now I'm looking at my own country, the United Kingdom.

The data comes from https://coronavirus.data.gov.uk/ and I used the Developer's Guide to scrape the data, so it was a fairly simple process. The notebook that scapes the data is public and can be found here. Further information about data collection methodologies and definitions can be found here.

The data includes the overall numbers for the UK as a whole, the numbers for each of the devolved UK nations (Eng, Sco, Wal & NI), English Regions and Upper Tier Local Authorities (UTLA) for all of the UK (what we call Boroughs). I have also included a small table with the populations of the 4 devolved UK nations, used to calculate the death rates per 100,000 population.

As I've said for before - I am not an Epidemiologist, Sociologist or even a Data Scientist. I am actually a Mechanical Engineer! The objective here is to improve my data science skills and maybe provide some useful data to the wider community.

Any questions, comments or suggestions are most welcome! I am open to requests and collaborations! Stay Safe!

This open data publication has moved to COVID-19 Statistical Data in Scotland (from 02/11/2022) Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. Clinical presentation may range from mild-to-moderate illness to pneumonia or severe acute respiratory infection. This dataset provides information on demographic characteristics (age, sex, deprivation) of confirmed novel coronavirus (COVID-19) cases, as well as trend data regarding the wider impact of the virus on the healthcare system. Data includes information on primary care out of hours consultations, respiratory calls made to NHS24, contact with COVID-19 Hubs and Assessment Centres, incidents received by Scottish Ambulance Services (SAS), as well as COVID-19 related hospital admissions and admissions to ICU (Intensive Care Unit). Further data on the wider impact of the COVID-19 response, focusing on hospital admissions, unscheduled care and volume of calls to NHS24, is available on the COVID-19 Wider Impact Dashboard. There is a large amount of data being regularly published regarding COVID-19 (for example, Coronavirus in Scotland - Scottish Government and Deaths involving coronavirus in Scotland - National Records of Scotland. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications. Data visualisation is available to view in the interactive dashboard accompanying the COVID-19 Statistical Report. Please note information on COVID-19 in children and young people of educational age, education staff and educational settings is presented in a new COVID-19 Education Surveillance dataset going forward.

Estimates of the risk of hospital admission for coronavirus (COVID-19) and death involving COVID-19 by vaccination status, overall and by age group, using anonymised linked data from Census 2021. Experimental Statistics.

Outcome definitions

For this analysis, we define a death as involving COVID-19 if either of the ICD-10 codes U07.1 (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified) is mentioned on the death certificate. Information on cause of death coding is available in the User Guide to Mortality Statistics. We use date of occurrance rather than date of registration to give the date of the death.

We define COVID-109 hospitalisation as an inpatient episode in Hospital Episode Statistics where the primary diagnosis was COVID-19, identified by the ICD-19 codes (COVID-19, virus identified) or U07.2 (COVID-19, virus not identified). Where an individual had experienced more than one COVID-19 hospitalisation, the earliest that occurred within the study period was used. We define the date of COVID-19 hospitalisation as the start of the hospital episode.

ICD-10 code

U07.1 :

COVID-19, virus identified

U07.2:

COVID-19, virus not identified

Vaccination status is defined by the dose and the time since the last dose received

Unvaccinated:

no vaccination to less than 21 days post first dose

First dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post first dose or less than 21 days post second dose

First dose 3+ months:

more than or equal to 91 days post first dose to less than 21 days post second dose

Second dose 21 days to 3 months:

more than or equal to 21 days post second dose to earliest of less than 91 days post second dose or less than 21 days post third dose

Second dose 3-6 months:

more than or equal to 91 days post second dose to earliest of less than 182 days post second dose or less than 21 days post third dose

Second dose 6+ months:

more than or equal to 182 days post second dose to less than 21 days post third dose

Third dose 21 days to 3 months:

more than or equal to 21 days post third dose to less than 91 days post third dose

Third dose 3+ months:

more than or equal to 91 days post third dose

Model adjustments

Three sets of model adjustments were used

Age adjusted:

age (as a natural spline)

Age, socio-demographics adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status)

Fully adjusted:

age (as a natural spline), plus socio-demographic characteristics (sex, region, ethnicity, religion, IMD decile, NSSEC category, highest qualification, English language proficiency, key worker status), plus health-related characteristics (disability, self-reported health, care home residency, number of QCovid comorbidities (grouped), BMI category, frailty flag and hospitalisation within the last 21 days.

Age

Age in years is defined on the Census day 2021 (21 March 2021). Age is included in the model as a natural spline with boundary knots at the 10th and 90th centiles and internal knots at the 25th, 50th and 75th centiles. The positions of the knots are calculated separately for the overall model and for each age group for the stratified model.

CVD-COVID-UK, co-ordinated by the British Heart Foundation (BHF) Data Science Centre (https://bhfdatasciencecentre.org/), is one of the NIHR-BHF Cardiovascular Partnership’s National Flagship Projects.

CVD-COVID-UK aims to understand the relationship between COVID-19 and cardiovascular diseases through analyses of de-identified, pseudonymised, linked, nationally collated health datasets across the four nations of the UK. The consortium has over 400 members across more than 50 institutions including data custodians, data scientists and clinicians, all of whom have signed up to an agreed set of principles with an inclusive, open and transparent ethos.

Approved researchers access data within secure trusted/secure research environments (TREs/SDEs) provided by NHS England (England), the National Safe Haven (Scotland), the Secure Anonymised Information Linkage (SAIL) Databank (Wales) and the Honest Broker Service (Northern Ireland). A dashboard of datasets available in each nation’s TRE can be found here: https://bhfdatasciencecentre.org/areas/cvd-covid-uk-covid-impact/

This dataset represents the linked datasets in SAIL Databank’s TRE for Wales and contains the following datasets: • Welsh Longitudinal GP Dataset - Welsh Primary Care (Daily COVID codes only) (GPCD) • Welsh Longitudinal General Practice Dataset (WLGP) - Welsh Primary Care • Critical Care Dataset (CCDS) • Emergency Department Dataset Daily (EDDD) • Emergency Department Dataset (EDDS) • Outpatient Database for Wales (OPDW) • Outpatient Referral (OPRD) • Patient Episode Dataset for Wales (PEDW) • COVID-19 Test Results (PATD) • COVID-19 Test Trace and Protect (CTTP) - Legacy • COVID-19 Shielded People List (CVSP) • SARS-CoV-2 viral sequencing data (COG-UK data)-Lineage/Variant Data-Wales (CVSD) • Covid Vaccination Dataset (CVVD) • Annual District Death Daily (ADDD) • Annual District Death Extract (ADDE) • COVID-19 Consolidated Deaths (CDDS) • Intensive Care National Audit and Research Centre (ICCD) - Legacy - COVID only • Intensive Care National Audit and Research Centre (ICNC) • Welsh Dispensing Dataset (WDDS) - Legacy • Annual District Birth Extract (ADBE) • Maternity Indicators Dataset (MIDS) • National Community Child Health Database (NCCHD) • Care Home Dataset (CARE) • Congenital Anomaly Register and Information Service (CARS) • Referral to Treatment Times (RTTD) • SAIL Dementia e-Cohort (SDEC) • Welsh Ambulance Services NHS Trust (WASD) • Welsh Demographic Service Dataset (WDSD) • Welsh Results Reports Service (WRRS)

Context

A new coronavirus designated 2019-nCoV was first identified in Wuhan, the capital of China's Hubei province. People developed pneumonia without a clear cause and for which existing vaccines or treatments were not effective. The virus has shown evidence of human-to-human transmission. You can use this data for Analysis

Content

City Province Country LastUpdate keyID Confirmed Deaths

Acknowledgements

https://rapidapi.com/KishCom/api/covid-19-coronavirus-statistics

Cover Image

https://c.files.bbci.co.uk/D505/production/_115033545_gettyimages-1226314512.jpg

Inspiration

You can use this dataset for analyzing the Covid19 cases in different countries...

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

BackgroundThis paper asks whether Dynamic Causal modelling (DCM) can predict the long-term clinical impact of the COVID-19 epidemic. DCMs are designed to continually assimilate data and modify model parameters, such as transmissibility of the virus, changes in social distancing and vaccine coverage—to accommodate changes in population dynamics and virus behavior. But as a novel way to model epidemics do they produce valid predictions? We presented DCM predictions 12 months ago, which suggested an increase in viral transmission was accompanied by a reduction in pathogenicity. These changes provided plausible reasons why the model underestimated deaths, hospital admissions and acute-post COVID-19 syndrome by 20%. A further 12-month validation exercise could help to assess how useful such predictions are.Methodswe compared DCM predictions—made in October 2022—with actual outcomes over the 12-months to October 2023. The model was then used to identify changes in COVID-19 transmissibility and the sociobehavioral responses that may explain discrepancies between predictions and outcomes over this period. The model was then used to predict future trends in infections, long-COVID, hospital admissions and deaths over 12-months to October 2024, as a prelude to future tests of predictive validity.FindingsUnlike the previous predictions—which were an underestimate—the predictions made in October 2022 overestimated incidence, death and admission rates. This overestimation appears to have been caused by reduced infectivity of new variants, less movement of people and a higher persistence of immunity following natural infection and vaccination.Interpretationdespite an expressive (generative) model, with time-dependent epidemiological and sociobehavioral parameters, the model overestimated morbidity and mortality. Effectively, the model failed to accommodate the “law of declining virulence” over a timescale of years. This speaks to a fundamental issue in long-term forecasting: how to model decreases in virulence over a timescale of years? A potential answer may be available in a year when the predictions for 2024—under a model with slowly accumulating T-cell like immunity—can be assessed against actual outcomes.

The relationship between prevalence of infection and severe outcomes such as hospitalisation and death changed over the course of the COVID-19 pandemic. Reliable estimates of the infection fatality ratio (IFR) and infection hospitalisation ratio (IHR) along with the time-delay between infection and hospitalisation/death can inform forecasts of the numbers/timing of severe outcomes and allow healthcare services to better prepare for periods of increased demand. The REal-time Assessment of Community Transmission-1 (REACT-1) study estimated swab positivity for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in England approximately monthly from May 2020 to March 2022. Here, we analyse the changing relationship between prevalence of swab positivity and the IFR and IHR over this period in England, using publicly available data for the daily number of deaths and hospitalisations, REACT-1 swab positivity data, time-delay models, and Bayesian P-spline models. We analyse data for all age groups together, as well as in 2 subgroups: those aged 65 and over and those aged 64 and under. Additionally, we analysed the relationship between swab positivity and daily case numbers to estimate the case ascertainment rate of England’s mass testing programme. During 2020, we estimated the IFR to be 0.67% and the IHR to be 2.6%. By late 2021/early 2022, the IFR and IHR had both decreased to 0.097% and 0.76%, respectively. The average case ascertainment rate over the entire duration of the study was estimated to be 36.1%, but there was some significant variation in continuous estimates of the case ascertainment rate. Continuous estimates of the IFR and IHR of the virus were observed to increase during the periods of Alpha and Delta’s emergence. During periods of vaccination rollout, and the emergence of the Omicron variant, the IFR and IHR decreased. During 2020, we estimated a time-lag of 19 days between hospitalisation and swab positivity, and 26 days between deaths and swab positivity. By late 2021/early 2022, these time-lags had decreased to 7 days for hospitalisations and 18 days for deaths. Even though many populations have high levels of immunity to SARS-CoV-2 from vaccination and natural infection, waning of immunity and variant emergence will continue to be an upwards pressure on the IHR and IFR. As investments in community surveillance of SARS-CoV-2 infection are scaled back, alternative methods are required to accurately track the ever-changing relationship between infection, hospitalisation, and death and hence provide vital information for healthcare provision and utilisation.

Over 12 million people in the United States died from all causes between the beginning of January 2020 and August 21, 2023. Over 1.1 million of those deaths were with confirmed or presumed COVID-19.

Vaccine rollout in the United States Finding a safe and effective COVID-19 vaccine was an urgent health priority since the very start of the pandemic. In the United States, the first two vaccines were authorized and recommended for use in December 2020. One has been developed by Massachusetts-based biotech company Moderna, and the number of Moderna COVID-19 vaccines administered in the U.S. was over 250 million. Moderna has also said that its vaccine is effective against the coronavirus variants first identified in the UK and South Africa.

Sepsis is a syndrome with high mortality, which seriously threatens human health. During the pandemic of coronavirus disease 2019 (COVID-19), some severe and critically ill COVID-19 patients with multiple organ dysfunction developed characteristics typical of sepsis and met the diagnostic criteria for sepsis. Timely detection of cytokine storm and appropriate regulation of inflammatory response may be significant in the prevention and treatment of sepsis. This study evaluated the efficacy and safety of specific interleukin (IL)-1 inhibitors, specific IL-6 inhibitors, and GM-CSF blockades in the treatment of COVID-19 (at the edge of sepsis) patients through systematic review and meta-analysis. Methodology: A literature search was conducted on PubMed, EMBASE, Clinical Key, Cochrane Library, CNKI, and Wanfang Database using proper keywords such as “SARS-CoV-2,” “Corona Virus Disease 2019,” “COVID-19,” “anakinra,” “tocilizumab,” “siltuximab,” “sarilumab,” “mavrilimumab,” “lenzilumab,” and related words for publications released until August 22, 2021. Other available resources were also used to identify relevant articles. The present systematic review was performed based on PRISMA protocol. Results: Based on the inclusion and exclusion criteria, 43 articles were included in the final review. The meta-analysis results showed that tocilizumab could reduce the mortality of patients with COVID-19 (at the edge of sepsis) [randomized controlled trials, RCTs: odds ratio (OR) 0.71, 95%CI: 0.52–0.97, low-certainty evidence; non-RCTs: risk ratio (RR) 0.68, 95%CI: 0.55–0.84, very low-certainty evidence) as was anakinra (non-RCTs: RR 0.47, 95%CI: 0.34–0.66, very low-certainty evidence). Sarilumab might reduce the mortality of patients with COVID-19 (at the edge of sepsis), but there was no statistical significance (OR 0.65, 95%CI: 0.36–1.2, low-certainty evidence). For safety outcomes, whether tocilizumab had an impact on serious adverse events (SAEs) was very uncertain (RCTs: OR 0.87, 95%CI: 0.38–2.0, low-certainty evidence; non-RCTs 1.18, 95%CI: 0.83–1.68, very low-certainty evidence) as was on secondary infections (RCTs: OR 0.71, 95%CI: 0.06–8.75, low-certainty evidence; non-RCTs: RR 1.15, 95%CI: 0.89–1.49, very low-certainty evidence). Conclusions: This systematic review showed that tocilizumab, sarilumab, and anakinra could reduce the mortality of people with COVID-19 (at the edge of sepsis), and tocilizumab did not significantly affect SAEs and secondary infections. The current evidence of the studies on patients treated with siltuximab, mavrilimumab, and lenzilumab is insufficient. In order to establish evidence with stronger quality, high-quality studies are needed.Systematic Review Registration: PROSPERO (https://www.crd.york.ac.uk/prospero/), identifier CRD42020226545