Dataset from Ministry of Health. For more information, visit https://data.gov.sg/datasets/d_37c77bafba57a15da0da74326d6cc077/view

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, 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.

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.

On June 25, 2020, 305 patients with COVID-19 were discharged from Singapore hospitals and self-isolation facilities. As of that date, around 42.7 thousand people had been infected with the novel coronavirus in Singapore, and around 36.6 thousand people have recovered. The country has since introduced a stimulus package worth 48 billion Singapore dollars to help the Singapore economy, which had been badly hit by the pandemic.

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.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

A data set on COVID-19 pandemic in China, which covers daily statistics of confirmed cases (new and cumulative), recoveries (new and cumulative) and deaths (new and cumulative) at city/county level. All data are extracted from Chinese government reports.

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.

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.

As of July 13, 2022, 58 percent of Singaporean respondents stated that they had been avoiding public places during the COVID-19 outbreak, up from 44 percent on Feb 21, 2020. Singapore is experiencing a decrease in the number of confirmed daily cases, although the country is still expecting a rise in cases caused by the highly-contagious Omicron variant.

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

As of April 2020, entering the first week of circuit breaker measures to restrain the spread of COVID-19 in Singapore, 46 percent of the respondents stated they left their homes once during the previous day. 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 June 1.

In 2024, there were 13,655 reported cases of dengue fever and dengue hemorrhagic fever. This was an increase from the number of cases reported in the previous year. Largest outbreak in Singapore Dengue is one of Singapore’s most pressing endemic infectious disease. Since Singapore was declared malaria-free by the World Health Organization in 1982, the island-state has been focusing on fighting dengue and other infectious diseases such as HIV and tuberculosis. However, unlike malaria, Singapore has not been able to eradicate this mosquito-borne disease. The National Environment Agency (NEA) stated that Singapore saw one of the biggest dengue outbreaks in its history in 2020, reaching more than 35,000 cases. More dengue cases during Circuit Breaker period According to NEA, the increase in dengue infections were due to several factors: a change in the dominant dengue serotype, meaning fewer people would have immunity against it; the warmer months which allows mosquitoes to breed easily; and the impact of the ”circuit breaker” measures to control the COVID-19 pandemic in Singapore.During the two months of the “circuit breaker” period ending June 1, 2020, there were five times more cases of Aedes mosquito larvae detected in housing areas compared to the two months preceding it. As of May 1, 2020, 54 percent of Singaporean respondents stated that they had been avoiding going to work during the COVID-19 outbreak, up from 11 percent on Feb 21, 2020. With more people staying at home, and as the Aedes mosquitoes are active during the daytime, this period could have led to a higher number of dengue cases. To reduce the case numbers, since March 2020, the Inter-Agency Dengue Task Force (IADTF), including Town Councils, started to remove potential mosquito breeding grounds in public spaces and residences.