scholarly journals Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19)

2020 ◽  
Vol 9 (2) ◽  
pp. 580 ◽  
Author(s):  
Tetsuro Kobayashi ◽  
Sung-mok Jung ◽  
Natalie M. Linton ◽  
Ryo Kinoshita ◽  
Katsuma Hayashi ◽  
...  
Keyword(s):  
Virus Detection ◽  
Case Fatality ◽  
Cumulative Number ◽  
Diagnostic Laboratory ◽  
Illness Onset ◽  
Risk Of Death ◽  
Health Authorities ◽  
Novel Coronavirus ◽  
Case Fatality Risk ◽  
Diagnostic Laboratory Tests

To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death must be addressed. Second, the observed dataset of reported cases represents only a proportion of all infected individuals and there can be a substantial number of asymptomatic and mildly infected individuals who are never diagnosed. Third, ascertainment bias and risk of death among all those infected would be smaller when estimated using shorter virus detection windows and less sensitive diagnostic laboratory tests. In the ongoing COVID-19 epidemic, health authorities must cope with the uncertainty in the risk of death from COVID-19, and high-risk individuals should be identified using approaches that can address the abovementioned three problems. Although COVID-19 involves mostly mild infections among the majority of the general population, the risk of death among young adults is higher than that of seasonal influenza, and elderly with underlying comorbidities require additional care.

scholarly journals Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

2020 ◽  
Vol 9 (2) ◽  
pp. 538 ◽  
Author(s):  
Natalie Linton ◽  
Tetsuro Kobayashi ◽  
Yichi Yang ◽  
Katsuma Hayashi ◽  
Andrei Akhmetzhanov ◽  
...  
Keyword(s):  
Incubation Period ◽  
Case Fatality ◽  
Illness Onset ◽  
Event Date ◽  
History Of ◽  
Novel Coronavirus ◽  
Case Fatality Risk ◽  
Right Truncation ◽  
Epidemiological Characteristics ◽  
Mean Time

The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.

scholarly journals Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data

2020 ◽  
Author(s):  
Natalie M. Linton ◽  
Tetsuro Kobayashi ◽  
Yichi Yang ◽  
Katsuma Hayashi ◽  
Andrei R. Akhmetzhanov ◽  
...  
Keyword(s):  
Incubation Period ◽  
Case Fatality ◽  
Illness Onset ◽  
Event Date ◽  
History Of ◽  
Novel Coronavirus ◽  
Case Fatality Risk ◽  
Right Truncation ◽  
Epidemiological Characteristics ◽  
Mean Time

AbstractThe geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3–4 days without truncation and at 5–9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.

scholarly journals A Comparison of Case Fatality Risk of COVID-19 between Singapore and Japan

2020 ◽  
Vol 9 (10) ◽  
pp. 3326
Author(s):  
Taishi Kayano ◽  
Hiroshi Nishiura
Keyword(s):  
Age Distribution ◽  
Case Fatality ◽  
Standardized Mortality Ratio ◽  
Fatality Risk ◽  
Illness Onset ◽  
High Virulence ◽  
Mortality Ratio ◽  
The Many ◽  
Case Fatality Risk ◽  
Protection Against Infection

The crude case fatality risk (CFR) for coronavirus disease (COVID-19) in Singapore is remarkably small. We aimed to estimate the unbiased CFR by age for Singapore and Japan and compare these estimates by calculating the standardized mortality ratio (SMR). Age-specific CFRs for COVID-19 were estimated in real time, adjusting for the delay from illness onset to death. The SMR in Japan was estimated by using the age distribution of the Singapore population. Among cases aged 60–69 years and 70–79 years, the age-specific CFRs in Singapore were estimated as 1.84% (95% confidence interval: 0.46–4.72%) and 5.57% (1.41–13.97%), respectively, and those in Japan as 5.52% (4.55–6.62%) and 15.49% (13.81–17.27%), respectively. The SMR of COVID-19 in Japan, when compared with Singapore as the baseline, was estimated to be 1.46 (1.09–2.96). The overall CFR for Singapore is lower than that for Japan. It is possible that the circulating variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Singapore causes a milder clinical course of COVID-19 infection compared with other strains. If infection with a low-virulence SARS-CoV-2 variant provides protection against infection by high-virulence strains, the existence of such a strain is encouraging news for the many countries struggling to suppress this virus.

scholarly journals Situation analysis of novel Coronavirus (2019-nCoV) cases in Nepal

2020 ◽  
Vol 1 (1) ◽  
pp. 9-14
Author(s):  
Kiran Paudel ◽  
Prashamsa Bhandari ◽  
Yadav Prasad Joshi
Keyword(s):  
South Asian ◽  
Case Fatality ◽  
Cumulative Number ◽  
The Novel ◽  
Asian Countries ◽  
Primary Case ◽  
The Status ◽  
Exponential Trend ◽  
Using Data ◽  
Novel Coronavirus

The Novel Coronavirus (2019-nCoV) is currently a major threat to global health in an unprecedented manner. The global pandemic of COVID-19 has affected 215 countries and territories including Nepal. Until 1st June 2020, altogether 1,811 COVID-19 positive cases were diagnosed using RT-PCR. This study aimed to analyze the status of COVID-19 cases in Nepal and South Asian countries. A retrospective study from 23rd January to 1st June 2020 was conducted using data of the Ministry of Home Affairs, Nepal and Worldometer homepages. The primary case records during the pre and post lockdown periods were examined. Spatial distribution was observed. An exponential trend line was plotted and COVID-19 situation in South Asian countries was assessed. Of 1,811 COVID-19 cases, the highest number (38.3%) was reported in Province 2. Out of 77 districts, 59 were affected. In Fifty-eight districts, primary cases appeared during the lockdown period. The cumulative number of COVID-19 cases showed the exponential pattern of distribution in Nepal. In South Asian countries, India had the highest number of cases and case fatality rate (CFR). There were no cases of CFR in Bhutan. The Novel Coronavirus emergence in Nepal has become a serious challenge to the various sectors including public health. The emergence of primary cases even in the lockdown period needs a detailed study in the future.

scholarly journals Estimating the Risk of COVID-19 Death during the Course of the Outbreak in Korea, February–May 2020

2020 ◽  
Vol 9 (6) ◽  
pp. 1641 ◽  
Author(s):  
Eunha Shim ◽  
Kenji Mizumoto ◽  
Wongyeong Choi ◽  
Gerardo Chowell
Keyword(s):  
Time Delay ◽  
Early Stage ◽  
Case Fatality ◽  
Credible Interval ◽  
Adjusted Risk ◽  
Risk Of Death ◽  
Early Implementation ◽  
Daily Series ◽  
Case Fatality Risk ◽  
Reporting Delay

Background: In Korea, a total of 10,840 confirmed cases of COVID-19 including 256 deaths have been recorded as of May 9, 2020. The time-delay adjusted case fatality risk (CFR) of COVID-19 in Korea is yet to be estimated. Methods: We obtained the daily series of confirmed cases and deaths in Korea reported prior to May 9, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in Daegu, Gyeongsangbuk-do, other regions in Korea, as well as the entire country. Results: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do; this was partially due to the reporting delay. Our estimates of the risk of death in Gyeongsangbuk-do reached 25.9% (95% Credible Interval (CrI): 19.6%–33.6%), 20.8% (95% CrI: 18.1%–24.0%) in Daegu, and 1.7% (95% CrI: 1.1%–2.5%) in other regions, whereas the national estimate was 10.2% (95% CrI: 9.0%–11.5%). Conclusions: The latest estimates of CFR of COVID-19 in Korea are considerably high, even with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings. Geographic differences in the CFR are likely influenced by clusters tied to hospitals and nursing homes.

scholarly journals Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

2020 ◽  
Author(s):  
Sung-mok Jung ◽  
Andrei R. Akhmetzhanov ◽  
Katsuma Hayashi ◽  
Natalie M. Linton ◽  
Yichi Yang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Cumulative Incidence ◽  
Reproduction Number ◽  
Early Stage ◽  
Case Fatality ◽  
Primary Case ◽  
Risk Of Death ◽  
Novel Coronavirus ◽  
The Basic Reproduction Number

AbstractThe exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside of China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January, 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

scholarly journals Case fatality risk of novel coronavirus diseases 2019 in China

2020 ◽  
Author(s):  
Xiaowei Deng ◽  
Juan Yang ◽  
Wei Wang ◽  
Xiling Wang ◽  
Jiaxin Zhou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Risk ◽  
Influenza Pandemic ◽  
Mainland China ◽  
Case Fatality ◽  
Right Censoring ◽  
Fatality Risk ◽  
Critical Patients ◽  
Novel Coronavirus ◽  
Case Fatality Risk

ABSTRACTObjectiveThe outbreak of novel coronavirus disease 2019 (COVID-19) imposed a substantial health burden in mainland China and remains a global epidemic threat. Our objectives are to assess the case fatality risk (CFR) among COVID-19 patients detected in mainland China, stratified by clinical category and age group.MethodsWe collected individual information on laboratory-confirmed COVID-19 cases from publicly available official sources from December 29, 2019 to February 23, 2020. We explored the risk factors associated with mortality. We used methods accounting for right-censoring and survival analyses to estimate the CFR among detected cases.ResultsOf 12,863 cases reported outside Hubei, we obtained individual records for 9,651 cases, including 62 deaths and 1,449 discharged cases. The deceased were significantly older than discharged cases (median age: 77 vs 39 years, p<0.001). 58% (36/62) were male. Older age (OR 1.18 per year; 95%CI: 1.14 to 1.22), being male (OR 2.02; 95%CI: 1.02 to 4.03), and being treated in less developed economic regions (e.g., West and Northeast vs. East, OR 3.93; 95%CI: 1.74 to 8.85) were mortality risk factors. The estimated CFR was 0.89-1.24% among all cases. The fatality risk among critical patients was 2-fold higher than that among severe and critical patients, and 24-fold higher than that among moderate, severe and critical patients.ConclusionsOur estimates of CFR based on laboratory-confirmed cases ascertained outside of Hubei suggest that COVID-19 is not as severe as severe acute respiratory syndrome and Middle East respiratory syndrome, but more similar to the mortality risk of 2009 H1N1 influenza pandemic in hospitalized patients. The fatality risk of COVID-19 is higher in males and increases with age. Our study improves the severity assessment of the ongoing epidemic and can inform the COVID-19 outbreak response in China and beyond.

scholarly journals Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

2020 ◽  
Vol 9 (2) ◽  
pp. 523 ◽  
Author(s):  
Sung-mok Jung ◽  
Andrei R. Akhmetzhanov ◽  
Katsuma Hayashi ◽  
Natalie M. Linton ◽  
Yichi Yang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Cumulative Incidence ◽  
Reproduction Number ◽  
Early Stage ◽  
Case Fatality ◽  
Primary Case ◽  
Risk Of Death ◽  
Novel Coronavirus ◽  
The Basic Reproduction Number

The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

scholarly journals Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England

2021 ◽  
Author(s):  
Daniel J Grint ◽  
Kevin Wing ◽  
Elizabeth Williamson ◽  
Helen I McDonald ◽  
Krishnan Bhaskaran ◽  
...  
Keyword(s):  
Disease Severity ◽  
Absolute Risk ◽  
Case Fatality ◽  
Accurate Estimation ◽  
Fatality Risk ◽  
Risk Of Death ◽  
Increased Risk ◽  
Pandemic Planning ◽  
Case Fatality Risk

AbstractThe B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P<.0001)). Absolute risk of death by 28-days increased with age and comorbidities. VOC has potential to spread faster with higher mortality than the pandemic to date.

scholarly journals Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England, 16 November to 5 February

2021 ◽  
Vol 26 (11) ◽  
Author(s):  
Daniel J Grint ◽  
Kevin Wing ◽  
Elizabeth Williamson ◽  
Helen I McDonald ◽  
Krishnan Bhaskaran ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Disease Severity ◽  
Absolute Risk ◽  
Case Fatality ◽  
Accurate Estimation ◽  
Fatality Risk ◽  
Risk Of Death ◽  
Increased Risk ◽  
Pandemic Planning ◽  
Case Fatality Risk

The SARS-CoV-2 B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (hazard ratio: 1.67; 95% confidence interval: 1.34–2.09; p < 0.0001). Absolute risk of death by 28 days increased with age and comorbidities. This VOC has potential to spread faster with higher mortality than the pandemic to date.

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