52 datasets found
  1. Total cases of COVID-19 infections Singapore 2020-2022

    • statista.com
    Updated Jun 9, 2020
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    Statista (2020). Total cases of COVID-19 infections Singapore 2020-2022 [Dataset]. https://www.statista.com/statistics/1098985/singapore-covid-19-total-cases/
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    Dataset updated
    Jun 9, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 23, 2020 - Apr 7, 2022
    Area covered
    Singapore
    Description

    As of April 7, 2022, the total number of COVID-19 cases in Singapore amounted to around 1.1 million. There has been a decrease in daily cases in Singapore this week, though the number is still expected to rise largely due to the highly-contagious Omicron variant.

    Overcoming the COVID-19 pandemic Singapore was one of the few countries worldwide that had managed to successfully control the spread of COVID-19. This was done through imposing a strict lockdown period during the beginning of the pandemic in 2020, introducing and enforcing hygiene and social-distancing rules, and effective contact tracing, among others. The measures in place had the intended impact, as the number of daily recorded cases have decreased to manageable levels. Furthermore, community transmission has been reduced to just several cases a week; the majority of the daily new cases of COVID-19 recorded were from overseas arrivals.

    Recovering from the economic impact of COVID-19 The closure of businesses, compounded by the global restrictions on movement, had had an adverse effect on its economy. Singapore went through its worse recession on record, while the resident unemployment rate increased. However, with restrictions in the country easing, economists have raised their forecasts for economic growth in Singapore for 2021.

    Singapore is currently one out of more than 200 countries and territories battling the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  2. d

    Number of COVID-19 deaths by month

    • data.gov.sg
    Updated Jun 6, 2024
    + more versions
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    Ministry of Health (2024). Number of COVID-19 deaths by month [Dataset]. https://data.gov.sg/datasets/d_abeeab6fb3b739d7b234e7452bafd07c/view
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    Dataset updated
    Jun 6, 2024
    Dataset authored and provided by
    Ministry of Health
    License

    https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence

    Time period covered
    Jan 2023 - Sep 2023
    Description

    Dataset from Ministry of Health. For more information, visit https://data.gov.sg/datasets/d_abeeab6fb3b739d7b234e7452bafd07c/view

  3. New cases per day of COVID-19 Singapore 2021-2022

    • statista.com
    Updated Sep 30, 2024
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    Statista (2024). New cases per day of COVID-19 Singapore 2021-2022 [Dataset]. https://www.statista.com/statistics/1098959/singapore-new-cases-of-covid-19/
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    Dataset updated
    Sep 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 4, 2021 - Nov 4, 2022
    Area covered
    Singapore
    Description

    On November 4, 2022, Singapore recorded 3,128 new confirmed cases of COVID-19. Although the number of daily cases is started to decline, Singapore is still expecting a rise in cases caused by the highly-contagious Omicron variant.

    Singapore is currently one out of more than 200 countries and territories battling the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  4. T

    Singapore Coronavirus COVID-19 Cases

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). Singapore Coronavirus COVID-19 Cases [Dataset]. https://tradingeconomics.com/singapore/coronavirus-cases
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    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 4, 2020 - May 17, 2023
    Area covered
    Singapore
    Description

    Singapore recorded 2414394 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Singapore reported 1722 Coronavirus Deaths. This dataset includes a chart with historical data for Singapore Coronavirus Cases.

  5. Coronavirus COVID-19 Global Cases

    • redivis.com
    application/jsonl +7
    Updated Jul 13, 2020
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    Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
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    sas, csv, application/jsonl, spss, stata, parquet, arrow, avroAvailable download formats
    Dataset updated
    Jul 13, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    Abstract

    JHU Coronavirus COVID-19 Global Cases, by country

    Documentation

    PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

    This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

    Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    Section 2

    Included Data Sources are:

    %3C!-- --%3E

    Section 3

    **Terms of Use: **

    This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

    Section 4

    **U.S. county-level characteristics relevant to COVID-19 **

    Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

    https://github.com/mkiang/county_preparedness/

  6. Breakdown of COVID-19 hospitalization cases Singapore 2022

    • statista.com
    Updated May 29, 2024
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    Statista (2024). Breakdown of COVID-19 hospitalization cases Singapore 2022 [Dataset]. https://www.statista.com/statistics/1103601/singapore-coronavirus-active-cases-breakdown/
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    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 7, 2022
    Area covered
    Singapore
    Description

    As of April 7, 2022, 416 people in Singapore were hospitalized due to COVID-19. Out of these, 44 cases required oxygen supplementation, while 15 in the ICU. To date, 1,290 deaths have so far been attributed to COVID-19.

    State of the coronavirus (COVID-19) pandemic in Singapore As of February 2, 2022, Singapore had registered more than 362 thousand confirmed cases of COVID-19. Despite having an 88 percent COVID-19 vaccination rate, the country has been going through a surge in COVID-19 infections now caused by the highly-contagious Omicron variant. This has led to delays in its plans to reopen the country for a 'return to normal'.

    Gradual return to normalcy? Due to the current increase in COVID-19 infections, Singapore has pushed back plans to remove the restrictions imposed to control the pandemic, with the Prime Minister estimating that it would be another three to six months before the 'new normal' could begin. This was to prevent the healthcare system from being overstressed. While vaccination rates remain high, hospitalization rates have increased, with the majority of those hospitalized being unvaccinated.

    Singapore is currently one out of more than 200 countries and territories battling the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  7. Local and imported COVID-19 cases breakdown Singapore 2020

    • statista.com
    Updated Mar 23, 2020
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    Statista (2020). Local and imported COVID-19 cases breakdown Singapore 2020 [Dataset]. https://www.statista.com/statistics/1103972/singapore-covid-19-local-and-imported-cases-breakdown/
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    Dataset updated
    Mar 23, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 11, 2020 - Mar 23, 2020
    Area covered
    Singapore
    Description

    On March 23, 2020, there were 48 imported cases of COVID-19 compared to six cases of local transmission. Imported cases are those in which the patient contracted the novel coronavirus while overseas. Singapore, along with Taiwan, Hong Kong, and China, is experiencing a so-called second wave of COVID-19 infections, brought into the country by Singapore citizens and residents returning from overseas.

  8. d

    Number of COVID-19 infections by Epi-week

    • data.gov.sg
    Updated Jun 6, 2024
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    Ministry of Health (2024). Number of COVID-19 infections by Epi-week [Dataset]. https://data.gov.sg/datasets/d_11e68bba3b3c76733475a72d09759eeb/view
    Explore at:
    Dataset updated
    Jun 6, 2024
    Dataset authored and provided by
    Ministry of Health
    License

    https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence

    Time period covered
    Jan 2023 - Jan 2024
    Description

    Dataset from Ministry of Health. For more information, visit https://data.gov.sg/datasets/d_11e68bba3b3c76733475a72d09759eeb/view

  9. f

    Projected time to peak infection, duration of infection, cumulative...

    • figshare.com
    xls
    Updated Jun 11, 2023
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    John P. Ansah; David Bruce Matchar; Sean Lam Shao Wei; Jenny G. Low; Ahmad Reza Pourghaderi; Fahad Javaid Siddiqui; Tessa Lui Shi Min; Aloysius Chia Wei-Yan; Marcus Eng Hock Ong (2023). Projected time to peak infection, duration of infection, cumulative infection, proportion infected and total deaths. [Dataset]. http://doi.org/10.1371/journal.pone.0248742.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    John P. Ansah; David Bruce Matchar; Sean Lam Shao Wei; Jenny G. Low; Ahmad Reza Pourghaderi; Fahad Javaid Siddiqui; Tessa Lui Shi Min; Aloysius Chia Wei-Yan; Marcus Eng Hock Ong
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Projected time to peak infection, duration of infection, cumulative infection, proportion infected and total deaths.

  10. M

    Project Tycho Dataset; Counts of COVID-19 Reported In SINGAPORE: 2019-2021

    • catalog.midasnetwork.us
    • tycho.pitt.edu
    csv, zip
    Updated Aug 25, 2025
    + more versions
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    MIDAS Coordination Center (2025). Project Tycho Dataset; Counts of COVID-19 Reported In SINGAPORE: 2019-2021 [Dataset]. http://doi.org/10.25337/T7/ptycho.v2.0/SG.840539006
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Aug 25, 2025
    Dataset provided by
    MIDAS COORDINATION CENTER
    Authors
    MIDAS Coordination Center
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Time period covered
    Dec 30, 2019 - Jul 31, 2021
    Area covered
    Country, Singapore
    Variables measured
    Viruses, disease, COVID-19, pathogen, mortality data, Population count, infectious disease, viral Infectious disease, vaccine-preventable Disease, viral respiratory tract infection, and 1 more
    Dataset funded by
    National Institute of General Medical Sciences
    Description

    This Project Tycho dataset includes a CSV file with COVID-19 data reported in SINGAPORE: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

  11. COVID-19 Country Level Timeseries

    • kaggle.com
    Updated Mar 29, 2020
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    Arpan Das (2020). COVID-19 Country Level Timeseries [Dataset]. https://www.kaggle.com/arpandas65/covid19-country-level-timeseries/metadata
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 29, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Arpan Das
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Description

    Context

    Amidst the COVID-19 outbreak, the world is facing great crisis in every way. The value and things we built as a human race are going through tremendous challenges. It is a very small effort to bring curated data set on Novel Corona Virus to accelerate the forecasting and analytical experiments to cope up with this critical situation. It will help to visualize the country level out break and to keep track on regularly added new incidents.

    COVID-19 Country Level Timeseries Dataset

    This Dataset contains country wise public domain time series information on COVID-19 outbreak. The Data is sorted alphabetically on Country name and Date of Observation.

    Column Descriptions

    The data set contains the following columns:
    ObservationDate: The date on which the incidents are observed country: Country of the Outbreak Confirmed: Number of confirmed cases till observation date Deaths: Number of death cases till observation date Recovered: Number of recovered cases till observation date New Confirmed: Number of new confirmed cases on observation date New Deaths: Number of New death cases on observation date New Recovered: Number of New recovered cases on observation date latitude: Latitude of the affected country longitude: Longitude of the affected country

    Acknowledgements

    This data set is a cleaner version of the https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset data set with added geo location information and regularly added incident counts. I would like to thank this great effort by SRK.

    Original Data Source

    Johns Hopkins University MoBS lab - https://www.mobs-lab.org/2019ncov.html World Health Organization (WHO): https://www.who.int/ DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia. BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html Macau Government: https://www.ssm.gov.mo/portal/ Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases Ministry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19 Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

  12. r

    covid19_jhu_csse_summary

    • redivis.com
    Updated Feb 13, 2020
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    Stanford Center for Population Health Sciences (2020). covid19_jhu_csse_summary [Dataset]. https://redivis.com/datasets/rxta-4v35cgyzf
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    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    The table covid19_jhu_csse_summary is part of the dataset Coronavirus COVID-19 Global Cases, available at https://stanford.redivis.com/datasets/rxta-4v35cgyzf. It contains 390476 rows across 13 variables.

  13. f

    Data_Sheet_3_Cost benefit analysis of alternative testing and quarantine...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated Jun 7, 2023
    + more versions
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    Jing Lou; Nigel Wei-Han Lim; Celestine Grace XueTing Cai; Borame Sue Lee Dickens; Vinh Anh Huynh; Hwee-Lin Wee (2023). Data_Sheet_3_Cost benefit analysis of alternative testing and quarantine policies for travelers for infection control: A case study of Singapore during the COVID-19 pandemic.docx [Dataset]. http://doi.org/10.3389/fpubh.2023.1101986.s003
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    Frontiers
    Authors
    Jing Lou; Nigel Wei-Han Lim; Celestine Grace XueTing Cai; Borame Sue Lee Dickens; Vinh Anh Huynh; Hwee-Lin Wee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundBorder control mitigates local infections but bears a heavy economic cost, especially for tourism-reliant countries. While studies have supported the efficacy of border control in suppressing cross-border transmission, the trade-off between costs from imported and secondary cases and from lost economic activities has not been studied. This case study of Singapore during the COVID-19 pandemic aims to understand the impacts of varying quarantine length and testing strategies on the economy and health system. Additionally, we explored the impact of permitting unvaccinated travelers to address emerging equity concerns. We assumed that community transmission is stable and vaccination rates are high enough that inbound travelers are not dissuaded from traveling.MethodsThe number of travelers was predicted considering that longer quarantine reduces willingness to travel. A micro-simulation model predicted the number of COVID-19 cases among travelers, the resultant secondary cases, and the probability of being symptomatic in each group. The incremental net monetary benefit (INB) of Singapore was quantified under each border-opening policy compared to pre-opening status, based on tourism receipts, cost/profit from testing and quarantine, and cost and health loss due to COVID-19 cases.ResultsCompared to polymerase chain reaction (PCR), rapid antigen test (ART) detects fewer imported cases but results in fewer secondary cases. Longer quarantine results in fewer cases but lower INB due to reduced tourism receipts. Assuming the proportion of unvaccinated travelers is small (8% locally and 24% globally), allowing unvaccinated travelers will accrue higher INB without exceeding the intensive care unit (ICU) capacity. The highest monthly INB from all travelers is $2,236.24 m, with 46.69 ICU cases per month, achieved with ARTs at pre-departure and on arrival without quarantine. The optimal policy in terms of highest INB is robust under changes to various model assumptions. Among all cost-benefit components, the top driver for INB is tourism receipts.ConclusionsWith high vaccination rates locally and globally alongside stable community transmission, opening borders to travelers regardless of vaccination status will increase economic growth in the destination country. The caseloads remain manageable without exceeding ICU capacity, and costs of cases are offset by the economic value generated from travelers.

  14. b

    COVID-19 Pandemic : worldwide statistics to 31 March 2023

    • opendata.brussels.be
    csv, excel, geojson +1
    Updated Jan 6, 2025
    + more versions
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    (2025). COVID-19 Pandemic : worldwide statistics to 31 March 2023 [Dataset]. https://opendata.brussels.be/explore/dataset/pandemie-covid-19-statistiques-mondiales-arretees-au-31-mars-2023/
    Explore at:
    json, excel, csv, geojsonAvailable download formats
    Dataset updated
    Jan 6, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is the data for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).Data SourcesWorld Health Organization (WHO): https://www.who.int/ DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia. BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html Macau Government: https://www.ssm.gov.mo/portal/ Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-casesMinistry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

  15. Perceived future case numbers COVID-19 outbreak Singapore 2020

    • statista.com
    Updated May 29, 2024
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    Statista (2024). Perceived future case numbers COVID-19 outbreak Singapore 2020 [Dataset]. https://www.statista.com/statistics/1103402/singapore-perceived-future-case-numbers-of-covid-19-outbreak/
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    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 14, 2020 - Feb 17, 2020
    Area covered
    Singapore
    Description

    As of February 2020, 64 percent of Singaporean respondents believed that number of COVID-19 cases would go up locally. Between February 18, the date of the survey, to mid March, the number of people diagnosed with the coronavirus increased from 81 to 178.

  16. o

    Data from: SARS-CoV-2 seroprevalence and transmission risk factors among...

    • omicsdi.org
    Updated Apr 3, 2020
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    (2020). SARS-CoV-2 seroprevalence and transmission risk factors among high-risk close contacts: a retrospective cohort study. [Dataset]. https://www.omicsdi.org/dataset/biostudies/S-EPMC7831879
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    Dataset updated
    Apr 3, 2020
    Variables measured
    Unknown
    Description

    Background The proportion of asymptomatic carriers and transmission risk factors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among household and non-household contacts remains unclear. In Singapore, extensive contact tracing by the Ministry of Health for every diagnosed COVID-19 case, and legally enforced quarantine and intensive health surveillance of close contacts provided a rare opportunity to determine asymptomatic attack rates and SARS-CoV-2 transmission risk factors among community close contacts of patients with COVID-19. Methods This retrospective cohort study involved all close contacts of confirmed COVID-19 cases in Singapore, identified between Jan 23 and April 3, 2020. Household contacts were defined as individuals who shared a residence with the index COVID-19 case. Non-household close contacts were defined as those who had contact for at least 30 min within 2 m of the index case. All patients with COVID-19 in Singapore received inpatient treatment, with access restricted to health-care staff. All close contacts were quarantined for 14 days with thrice-daily symptom monitoring via telephone. Symptomatic contacts underwent PCR testing for SARS-CoV-2. Secondary clinical attack rates were derived from the prevalence of PCR-confirmed SARS-CoV-2 among close contacts. Consenting contacts underwent serology testing and detailed exposure risk assessment. Bayesian modelling was used to estimate the prevalence of missed diagnoses and asymptomatic SARS-CoV-2-positive cases. Univariable and multivariable logistic regression models were used to determine SARS-CoV-2 transmission risk factors. Findings Between Jan 23 and April 3, 2020, 7770 close contacts (1863 household contacts, 2319 work contacts, and 3588 social contacts) linked to 1114 PCR-confirmed index cases were identified. Symptom-based PCR testing detected 188 COVID-19 cases, and 7582 close contacts completed quarantine without a positive SARS-CoV-2 PCR test. Among 7518 (96·8%) of the 7770 close contacts with complete data, the secondary clinical attack rate was 5·9% (95% CI 4·9-7·1) for 1779 household contacts, 1·3% (0·9-1·9) for 2231 work contacts, and 1·3% (1·0-1·7) for 3508 social contacts. Bayesian analysis of serology and symptom data obtained from 1150 close contacts (524 household contacts, 207 work contacts, and 419 social contacts) estimated that a symptom-based PCR-testing strategy missed 62% (95% credible interval 55-69) of COVID-19 diagnoses, and 36% (27-45) of individuals with SARS-CoV-2 infection were asymptomatic. Sharing a bedroom (multivariable odds ratio [OR] 5·38 [95% CI 1·82-15·84]; p=0·0023) and being spoken to by an index case for 30 min or longer (7·86 [3·86-16·02]; p<0·0001) were associated with SARS-CoV-2 transmission among household contacts. Among non-household contacts, exposure to more than one case (multivariable OR 3·92 [95% CI 2·07-7·40], p<0·0001), being spoken to by an index case for 30 min or longer (2·67 [1·21-5·88]; p=0·015), and sharing a vehicle with an index case (3·07 [1·55-6·08]; p=0·0013) were associated with SARS-CoV-2 transmission. Among both household and non-household contacts, indirect contact, meal sharing, and lavatory co-usage were not independently associated with SARS-CoV-2 transmission. Interpretation Targeted community measures should include physical distancing and minimising verbal interactions. Testing of all household contacts, including asymptomatic individuals, is warranted. Funding Ministry of Health of Singapore, National Research Foundation of Singapore, and National Natural Science Foundation of China.

  17. Table S1

    • figshare.com
    xlsx
    Updated Jun 13, 2022
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    Sheikh Taslim Ali (2022). Table S1 [Dataset]. http://doi.org/10.6084/m9.figshare.18517028.v1
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    xlsxAvailable download formats
    Dataset updated
    Jun 13, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Sheikh Taslim Ali
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The timing of the public health social measures implemented in response to COVID-19 in different locations/ countries including mainland China, Hong Kong, Taiwan, South Korea, Singapore, Japan, Italy, Germany, the United Kingdom (UK), and the United States of America (USA) specifically during 2020. These PHSMs are classified into case-based, community-wide, and travel-based control measures

  18. Total number of patients recovered from COVID-19 Singapore 2020

    • statista.com
    Updated Jun 25, 2020
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    Statista (2020). Total number of patients recovered from COVID-19 Singapore 2020 [Dataset]. https://www.statista.com/statistics/1101498/singapore-total-number-of-recovered-cases-covid-19/
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    Dataset updated
    Jun 25, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 4, 2020 - Jun 25, 2020
    Area covered
    Singapore
    Description

    On June 25, 2020, a total of ****** patients with COVID-19 in Singapore have recovered. As of that date, around **** thousand people had been infected with the novel coronavirus in Singapore. The country has since introduced strict restrictions on movement to slow down the spread of the novel coronavirus. Those caught flouting the restrictions would be fined *** Singapore dollars on the spot.

    Singapore is currently one out of more than *** countries and territories battling the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  19. COVID-19: The First Global Pandemic of the Information Age

    • cameroon.africageoportal.com
    • africageoportal.com
    Updated Apr 8, 2020
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    Urban Observatory by Esri (2020). COVID-19: The First Global Pandemic of the Information Age [Dataset]. https://cameroon.africageoportal.com/datasets/UrbanObservatory::covid-19-the-first-global-pandemic-of-the-information-age
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    Dataset updated
    Apr 8, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.-- Esri COVID-19 Trend Report for 3-9-2023 --0 Countries have Emergent trend with more than 10 days of cases: (name : # of active cases) 41 Countries have Spreading trend with over 21 days in new cases curve tail: (name : # of active cases)Monaco : 13, Andorra : 25, Marshall Islands : 52, Kyrgyzstan : 79, Cuba : 82, Saint Lucia : 127, Cote d'Ivoire : 148, Albania : 155, Bosnia and Herzegovina : 172, Iceland : 196, Mali : 198, Suriname : 246, Botswana : 247, Barbados : 274, Dominican Republic : 304, Malta : 306, Venezuela : 334, Micronesia : 346, Uzbekistan : 356, Afghanistan : 371, Jamaica : 390, Latvia : 402, Mozambique : 406, Kosovo : 412, Azerbaijan : 427, Tunisia : 528, Armenia : 594, Kuwait : 716, Thailand : 746, Norway : 768, Croatia : 847, Honduras : 1002, Zimbabwe : 1067, Saudi Arabia : 1098, Bulgaria : 1148, Zambia : 1166, Panama : 1300, Uruguay : 1483, Kazakhstan : 1671, Paraguay : 2080, Ecuador : 53320 Countries may have Spreading trend with under 21 days in new cases curve tail: (name : # of active cases)61 Countries have Epidemic trend with over 21 days in new cases curve tail: (name : # of active cases)Liechtenstein : 48, San Marino : 111, Mauritius : 742, Estonia : 761, Trinidad and Tobago : 1296, Montenegro : 1486, Luxembourg : 1540, Qatar : 1541, Philippines : 1915, Ireland : 1946, Brunei : 2010, United Arab Emirates : 2013, Denmark : 2111, Sweden : 2149, Finland : 2154, Hungary : 2169, Lebanon : 2208, Bolivia : 2838, Colombia : 3250, Switzerland : 3321, Peru : 3328, Slovakia : 3556, Malaysia : 3608, Indonesia : 3793, Portugal : 4049, Cyprus : 4279, Argentina : 5050, Iran : 5135, Lithuania : 5323, Guatemala : 5516, Slovenia : 5689, South Africa : 6604, Georgia : 7938, Moldova : 8082, Israel : 8746, Bahrain : 8932, Netherlands : 9710, Romania : 12375, Costa Rica : 12625, Singapore : 13816, Serbia : 14093, Czechia : 14897, Spain : 17399, Ukraine : 19568, Canada : 24913, New Zealand : 25136, Belgium : 30599, Poland : 38894, Chile : 41055, Australia : 50192, Mexico : 65453, United Kingdom : 65697, France : 68318, Italy : 70391, Austria : 90483, Brazil : 134279, Korea - South : 209145, Russia : 214935, Germany : 257248, Japan : 361884, US : 6440500 Countries may have Epidemic trend with under 21 days in new cases curve tail: (name : # of active cases) 54 Countries have Controlled trend: (name : # of active cases)Palau : 3, Saint Kitts and Nevis : 4, Guinea-Bissau : 7, Cabo Verde : 8, Mongolia : 8, Benin : 9, Maldives : 10, Comoros : 10, Gambia : 12, Bhutan : 14, Cambodia : 14, Syria : 14, Seychelles : 15, Senegal : 16, Libya : 16, Laos : 17, Sri Lanka : 19, Congo (Brazzaville) : 19, Tonga : 21, Liberia : 24, Chad : 25, Fiji : 26, Nepal : 27, Togo : 30, Nicaragua : 32, Madagascar : 37, Sudan : 38, Papua New Guinea : 38, Belize : 59, Egypt : 60, Algeria : 64, Burma : 65, Ghana : 72, Haiti : 74, Eswatini : 75, Guyana : 79, Rwanda : 83, Uganda : 88, Kenya : 92, Burundi : 94, Angola : 98, Congo (Kinshasa) : 125, Morocco : 125, Bangladesh : 127, Tanzania : 128, Nigeria : 135, Malawi : 148, Ethiopia : 248, Vietnam : 269, Namibia : 422, Cameroon : 462, Pakistan : 660, India : 4290 41 Countries have End Stage trend: (name : # of active cases)Sao Tome and Principe : 1, Saint Vincent and the Grenadines : 2, Somalia : 2, Timor-Leste : 2, Kiribati : 8, Mauritania : 12, Oman : 14, Equatorial Guinea : 20, Guinea : 28, Burkina Faso : 32, North Macedonia : 351, Nauru : 479, Samoa : 554, China : 2897, Taiwan* : 249634 -- SPIKING OF NEW CASE COUNTS --20 countries are currently experiencing spikes in new confirmed cases:Armenia, Barbados, Belgium, Brunei, Chile, Costa Rica, Georgia, India, Indonesia, Ireland, Israel, Kuwait, Luxembourg, Malaysia, Mauritius, Portugal, Sweden, Ukraine, United Kingdom, Uzbekistan 20 countries experienced a spike in new confirmed cases 3 to 5 days ago: Argentina, Bulgaria, Croatia, Czechia, Denmark, Estonia, France, Korea - South, Lithuania, Mozambique, New Zealand, Panama, Poland, Qatar, Romania, Slovakia, Slovenia, Switzerland, Trinidad and Tobago, United Arab Emirates 47 countries experienced a spike in new confirmed cases 5 to 14 days ago: Australia, Austria, Bahrain, Bolivia, Brazil, Canada, Colombia, Congo (Kinshasa), Cyprus, Dominican Republic, Ecuador, Finland, Germany, Guatemala, Honduras, Hungary, Iran, Italy, Jamaica, Japan, Kazakhstan, Lebanon, Malta, Mexico, Micronesia, Moldova, Montenegro, Netherlands, Nigeria, Pakistan, Paraguay, Peru, Philippines, Russia, Saint Lucia, Saudi Arabia, Serbia, Singapore, South Africa, Spain, Suriname, Thailand, Tunisia, US, Uruguay, Zambia, Zimbabwe 194 countries experienced a spike in new confirmed cases over 14 days ago: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea - South, Kosovo, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Taiwan*, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, US, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza, Yemen, Zambia, Zimbabwe Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.

  20. e

    COVID-19 pandemic: global statistics as at 31 March 2023

    • data.europa.eu
    csv
    Updated Mar 31, 2023
    + more versions
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    Stad Brussel (2023). COVID-19 pandemic: global statistics as at 31 March 2023 [Dataset]. https://data.europa.eu/data/datasets/pandemie-covid-19-statistiques-mondiales-arretees-au-31-mars-2023?locale=en
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    csvAvailable download formats
    Dataset updated
    Mar 31, 2023
    Dataset authored and provided by
    Stad Brussel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data from the 2019 Novel Coronavirus Visual Dashboard, managed by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). It is also supported by the team "ESRI Living Atlas" and "Johns Hopkins University Applied Physics Lab" (JHU APL).Data Sources:World Health Organization (WHO): https://www.who.int/ DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia. BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html Macau Government: https://www.ssm.gov.mo/portal/ Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-casesMinistry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

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Statista (2020). Total cases of COVID-19 infections Singapore 2020-2022 [Dataset]. https://www.statista.com/statistics/1098985/singapore-covid-19-total-cases/
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Total cases of COVID-19 infections Singapore 2020-2022

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 9, 2020
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Jan 23, 2020 - Apr 7, 2022
Area covered
Singapore
Description

As of April 7, 2022, the total number of COVID-19 cases in Singapore amounted to around 1.1 million. There has been a decrease in daily cases in Singapore this week, though the number is still expected to rise largely due to the highly-contagious Omicron variant.

Overcoming the COVID-19 pandemic Singapore was one of the few countries worldwide that had managed to successfully control the spread of COVID-19. This was done through imposing a strict lockdown period during the beginning of the pandemic in 2020, introducing and enforcing hygiene and social-distancing rules, and effective contact tracing, among others. The measures in place had the intended impact, as the number of daily recorded cases have decreased to manageable levels. Furthermore, community transmission has been reduced to just several cases a week; the majority of the daily new cases of COVID-19 recorded were from overseas arrivals.

Recovering from the economic impact of COVID-19 The closure of businesses, compounded by the global restrictions on movement, had had an adverse effect on its economy. Singapore went through its worse recession on record, while the resident unemployment rate increased. However, with restrictions in the country easing, economists have raised their forecasts for economic growth in Singapore for 2021.

Singapore is currently one out of more than 200 countries and territories battling the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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