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.
https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence
Dataset from Ministry of Health. For more information, visit https://data.gov.sg/datasets/d_37c77bafba57a15da0da74326d6cc077/view
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Singapore recorded 1722 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Singapore reported 2414394 Coronavirus Cases. This dataset includes a chart with historical data for Singapore Coronavirus Deaths.
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.
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.
JHU Coronavirus COVID-19 Global Cases, by country
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
Included Data Sources are:
%3C!-- --%3E
**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.
**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:
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.
The table covid19_jhu_csse_summary is part of the dataset Coronavirus COVID-19 Global Cases, available at https://redivis.com/datasets/rxta-4v35cgyzf. It contains 390476 rows across 13 variables.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This repository collects Singapore and Malaysia COVID-19 data from multiple data sources such as zaobao.sg and the Ministry of Health (MOH). The repository is updated multiple times per day. From June 1, 2020, Zaobao stopped updating the data so only Singapore MOH data are still daily updated. This database contains, updated until June 1st: detailed information about each case (demography data, date of onset, hospitalization, date of report, travel information, date of discharge or death), important action taken by the Singapore government, records of activities and status of each case, aggregated data by day, the daily numbers of suspect cases, close contacts, number of cases, deaths and their status. The repository contains also : the daily press release from MOH (until end of March 2023), the daily press release from the MOH of Malaysia, and the WHO situation reports. The repository contains information in multiple language.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The purpose of this project is to write a large and in sync dataset focused patient characteristics for identify the Risk groups and characteristics human-level that impact on infection, Complication and Death as a result of the disease
https://docs.google.com/spreadsheets/d/1awEY-04UK8wibkbZ1qfV6a-Q9YKScfP7qiAtWDsp9Jw/edit?usp=sharing
4535323 rows
A version that includes cleaning the data and engineering new features for more detail : https://docs.google.com/spreadsheets/d/1awEY-04UK8wibkbZ1qfV6a-Q9YKScfP7qiAtWDsp9Jw/edit?usp=sharing
Machine-ready version of machine learning model Consists only of INT and FLOAT for more detail : https://docs.google.com/spreadsheets/d/1awEY-04UK8wibkbZ1qfV6a-Q9YKScfP7qiAtWDsp9Jw/edit?usp=sharing
There may be duplicate cases (which come from different data systems) Focusing on countries: France, Korea, Indonesia, Tunisia, Japan, canada, new_zealand, singapore, guatemala, philippines, india, vietnam, hong kong , Toronto, Mexico.
I did not check the credibility of the sources
Concerns of the credibility of the Mexican government's data
Concerns about the credibility of the data of the Chinese government
india_wiki https://www.kaggle.com/karthikcs1/covid19-coronavirus-patient-list-karnataka-india
philippines https://www.kaggle.com/sundiver/covid19-philippines-edges
france https://www.kaggle.com/lperez/coronavirus-france-dataset
korea https://www.kaggle.com/kimjihoo/coronavirusdataset
indonesia https://www.kaggle.com/ardisragen/indonesia-coronavirus-cases
tunisia https://www.kaggle.com/ghassen1302/coronavirus-tunisia
japan https://www.kaggle.com/tsubasatwi/close-contact-status-of-corona-in-japan
world https://github.com/beoutbreakprepared/nCoV2019/tree/master/latest_data
canada https://www.kaggle.com/ryanxjhan/coronaviruscovid19-canada
new_zealand https://www.kaggle.com/madhavkru/covid19-nz
singapore https://www.kaggle.com/rhodiumbeng/singapores-covid19-cases
guatemala https://www.kaggle.com/ncovgt2020/covid19-guatemala
colombia https://www.kaggle.com/sebaxtian/covid19co
mexico https://www.kaggle.com/lalish99/covid19-mx
india_data https://www.kaggle.com/samacker77k/covid19india
vietnam https://www.kaggle.com/nh
kerla https://www.kaggle.com/baburajr/covid19inkerala
hong_kong https://www.kaggle.com/teddyteddywu/covid-19-hong-kong-cases
toronto https://www.kaggle.com/divyansh22/toronto-covid19-cases
Determining the severity illness according to WHO: https://www.who.int/publications/i/item/clinical-management-of-covid-19
*Thanks to all sources
*If you have any helpful information or suggestions for improvement, write
netbook PART A - cleaning and conact the data: https://www.kaggle.com/shirmani/characteristics-of-corona-patient-ds-v4
netbook PART B- features Engineering: https://www.kaggle.com/shirmani/build-characteristics-corona-patients-part-b/edit
part C data QA https://www.kaggle.com/shirmani/qa-characteristics-corona-patients-part-c
netbook PART D - format the data to int and float cols (model preparation): https://www.kaggle.com/shirmani/build-characteristics-corona-patients-part-d
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence
Dataset from Ministry of Health. For more information, visit https://data.gov.sg/datasets/d_11e68bba3b3c76733475a72d09759eeb/view
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
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.
On June 25, 2020, a total of 36,604 patients with COVID-19 in Singapore have recovered. As of that date, around 42.7 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 300 Singapore dollars on the spot.
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.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This is the data repository 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).
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.
As of April 2020, entering the third week of circuit breaker measures to restrain the spread of COVID-19 in Singapore, 20 percent of the respondents stated that the state of their mental health had gotten worse. In response to the growing number of new cases, Singapore announced on April 3 a set of preventive "circuit breaker" measures, to be applied from April 7 to May 4, with an extension to June 1 announced on April 21.
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.
As of March 25, 2020, the largest age group among Singaporeans confirmed to have COVID-19 were those between 20 to 29 years old, with 141 such cases. These were mostly Singaporeans who had returned from their studies or travels overseas, especially Europe and North America. At the time of writing, Singapore is experiencing a second wave of novel coronavirus infections. This was mostly brought into the country from returning Singapore citizens and residents.
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.