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.

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

Model inputs (parameters with * were included in the sensitivity analysis and varied ±25%).

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.

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.

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

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.