Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe

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Abstract

Background

As of 16 May 2020, more than 4.5 million cases and more than 300,000 deaths from disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported. Reliable estimates of mortality from SARS-CoV-2 infection are essential for understanding clinical prognosis, planning healthcare capacity, and epidemic forecasting. The case–fatality ratio (CFR), calculated from total numbers of reported cases and reported deaths, is the most commonly reported metric, but it can be a misleading measure of overall mortality. The objectives of this study were to (1) simulate the transmission dynamics of SARS-CoV-2 using publicly available surveillance data and (2) infer estimates of SARS-CoV-2 mortality adjusted for biases and examine the CFR, the symptomatic case–fatality ratio (sCFR), and the infection–fatality ratio (IFR) in different geographic locations.

Method and findings

We developed an age-stratified susceptible-exposed-infected-removed (SEIR) compartmental model describing the dynamics of transmission and mortality during the SARS-CoV-2 epidemic. Our model accounts for two biases: preferential ascertainment of severe cases and right-censoring of mortality. We fitted the transmission model to surveillance data from Hubei Province, China, and applied the same model to six regions in Europe: Austria, Bavaria (Germany), Baden-Württemberg (Germany), Lombardy (Italy), Spain, and Switzerland. In Hubei, the baseline estimates were as follows: CFR 2.4% (95% credible interval [CrI] 2.1%–2.8%), sCFR 3.7% (3.2%–4.2%), and IFR 2.9% (2.4%–3.5%). Estimated measures of mortality changed over time. Across the six locations in Europe, estimates of CFR varied widely. Estimates of sCFR and IFR, adjusted for bias, were more similar to each other but still showed some degree of heterogeneity. Estimates of IFR ranged from 0.5% (95% CrI 0.4%–0.6%) in Switzerland to 1.4% (1.1%–1.6%) in Lombardy, Italy. In all locations, mortality increased with age. Among individuals 80 years or older, estimates of the IFR suggest that the proportion of all those infected with SARS-CoV-2 who will die ranges from 20% (95% CrI 16%–26%) in Switzerland to 34% (95% CrI 28%–40%) in Spain. A limitation of the model is that count data by date of onset are required, and these are not available in all countries.

Conclusions

We propose a comprehensive solution to the estimation of SARS-Cov-2 mortality from surveillance data during outbreaks. The CFR is not a good predictor of overall mortality from SARS-CoV-2 and should not be used for evaluation of policy or comparison across settings. Geographic differences in IFR suggest that a single IFR should not be applied to all settings to estimate the total size of the SARS-CoV-2 epidemic in different countries. The sCFR and IFR, adjusted for right-censoring and preferential ascertainment of severe cases, are measures that can be used to improve and monitor clinical and public health strategies to reduce the deaths from SARS-CoV-2 infection.

Author summary

Why was this study done?

Reliable estimates of measures of mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are needed to understand clinical prognosis, to plan healthcare capacity, and for epidemic forecasting.
The case–fatality ratio (CFR), the number of reported deaths divided by the number of reported cases at a specific time point, is the most commonly used metric, but it is a biased measure of mortality from SARS-CoV-2 infection.
The symptomatic case–fatality ratio (sCFR) and overall infection–fatality ratio (IFR) are alternative measures of mortality with clinical and public health relevance, which should be investigated further in different geographic locations.

What did the researchers do and find?

We developed a mathematical model that describes infection transmission and death during a SARS-CoV-2 epidemic. The model takes into account the delay between infection and death and preferential ascertainment of disease in people with severe symptoms, both of which affect the assessment of mortality.
We applied the model to data from Hubei Province in China, which was the first place affected by SARS-CoV-2, and to six locations in Europe—Austria, Bavaria (Germany), Baden-Württemberg (Germany), Lombardy (Italy), Spain, and Switzerland—to estimate the CFR, the sCFR, and the IFR.
Estimates of sCFR and IFR, adjusted for bias, were similar to each other and varied less geographically than the CFR. IFR was lowest in Switzerland (0.5%) and highest in Hubei Province (2.9%). The IFR increased with age; among those 80 years or older, estimates ranged from 20% in Switzerland to 34% in Spain.

What do these findings mean?

The CFR does not predict overall mortality from SARS-CoV-2 infection well and should not be used for the evaluation of policy or for making comparisons between geographic locations.
There are geographic differences in the IFR of SARS-CoV-2, which could result from differences in factors including emergency preparedness and response and health service capacity.
SARS-CoV-2 infection results in substantial mortality. Further studies should investigate ways to reduce death from SARS-CoV-2 in older people and to understand the causes of the differences between countries.

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Most cited references 19

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A novel coronavirus outbreak of global health concern

Chen Wang, Peter W Horby, Frederick G. Hayden … (2020)

In December, 2019, Wuhan, Hubei province, China, became the centre of an outbreak of pneumonia of unknown cause, which raised intense attention not only within China but internationally. Chinese health authorities did an immediate investigation to characterise and control the disease, including isolation of people suspected to have the disease, close monitoring of contacts, epidemiological and clinical data collection from patients, and development of diagnostic and treatment procedures. By Jan 7, 2020, Chinese scientists had isolated a novel coronavirus (CoV) from patients in Wuhan. The genetic sequence of the 2019 novel coronavirus (2019-nCoV) enabled the rapid development of point-of-care real-time RT-PCR diagnostic tests specific for 2019-nCoV (based on full genome sequence data on the Global Initiative on Sharing All Influenza Data [GISAID] platform). Cases of 2019-nCoV are no longer limited to Wuhan. Nine exported cases of 2019-nCoV infection have been reported in Thailand, Japan, Korea, the USA, Vietnam, and Singapore to date, and further dissemination through air travel is likely.1, 2, 3, 4, 5 As of Jan 23, 2020, confirmed cases were consecutively reported in 32 provinces, municipalities, and special administrative regions in China, including Hong Kong, Macau, and Taiwan. 3 These cases detected outside Wuhan, together with the detection of infection in at least one household cluster—reported by Jasper Fuk-Woo Chan and colleagues 6 in The Lancet—and the recently documented infections in health-care workers caring for patients with 2019-nCoV indicate human-to-human transmission and thus the risk of much wider spread of the disease. As of Jan 23, 2020, a total of 835 cases with laboratory-confirmed 2019-nCoV infection have been detected in China, of whom 25 have died and 93% remain in hospital (figure ). 3 Figure Timeline of early stages of 2019-nCoV outbreak 2019-nCoV=2019 novel coronavirus. In The Lancet, Chaolin Huang and colleagues 7 report clinical features of the first 41 patients admitted to the designated hospital in Wuhan who were confirmed to be infected with 2019-nCoV by Jan 2, 2020. The study findings provide first-hand data about severity of the emerging 2019-nCoV infection. Symptoms resulting from 2019-nCoV infection at the prodromal phase, including fever, dry cough, and malaise, are non-specific. Unlike human coronavirus infections, upper respiratory symptoms are notably infrequent. Intestinal presentations observed with SARS also appear to be uncommon, although two of six cases reported by Chan and colleagues had diarrhoea. 6 Common laboratory findings on admission to hospital include lymphopenia and bilateral ground-glass opacity or consolidation in chest CT scans. These clinical presentations confounded early detection of infected cases, especially against a background of ongoing influenza and circulation of other respiratory viruses. Exposure history to the Huanan Seafood Wholesale market served as an important clue at the early stage, yet its value has decreased as more secondary and tertiary cases have appeared. Of the 41 patients in this cohort, 22 (55%) developed severe dyspnoea and 13 (32%) required admission to an intensive care unit, and six died. 7 Hence, the case-fatality proportion in this cohort is approximately 14·6%, and the overall case fatality proportion appears to be closer to 3% (table ). However, both of these estimates should be treated with great caution because not all patients have concluded their illness (ie, recovered or died) and the true number of infections and full disease spectrum are unknown. Importantly, in emerging viral infection outbreaks the case-fatality ratio is often overestimated in the early stages because case detection is highly biased towards the more severe cases. As further data on the spectrum of mild or asymptomatic infection becomes available, one case of which was documented by Chan and colleagues, 6 the case-fatality ratio is likely to decrease. Nevertheless, the 1918 influenza pandemic is estimated to have had a case-fatality ratio of less than 5% 13 but had an enormous impact due to widespread transmission, so there is no room for complacency. Table Characteristics of patients who have been infected with 2019-nCoV, MERS-CoV, and SARS-CoV7, 8, 10, 11, 12 2019-nCoV * MERS-CoV SARS-CoV Demographic Date December, 2019 June, 2012 November, 2002 Location of first detection Wuhan, China Jeddah, Saudi Arabia Guangdong, China Age, years (range) 49 (21–76) 56 (14–94) 39·9 (1–91) Male:female sex ratio 2·7:1 3·3:1 1:1·25 Confirmed cases 835† 2494 8096 Mortality 25† (2·9%) 858 (37%) 744 (10%) Health-care workers 16‡ 9·8% 23·1% Symptoms Fever 40 (98%) 98% 99–100% Dry cough 31 (76%) 47% 29–75% Dyspnoea 22 (55%) 72% 40–42% Diarrhoea 1 (3%) 26% 20–25% Sore throat 0 21% 13–25% Ventilatory support 9·8% 80% 14–20% Data are n, age (range), or n (%) unless otherwise stated. 2019-nCoV=2019 novel coronavirus. MERS-CoV=Middle East respiratory syndrome coronavirus. SARS-CoV=severe acute respiratory syndrome coronavirus. * Demographics and symptoms for 2019-nCoV infection are based on data from the first 41 patients reported by Chaolin Huang and colleagues (admitted before Jan 2, 2020). 8 Case numbers and mortalities are updated up to Jan 21, 2020) as disclosed by the Chinese Health Commission. † Data as of Jan 23, 2020. ‡ Data as of Jan 21, 2020. 9 As an RNA virus, 2019-nCoV still has the inherent feature of a high mutation rate, although like other coronaviruses the mutation rate might be somewhat lower than other RNA viruses because of its genome-encoded exonuclease. This aspect provides the possibility for this newly introduced zoonotic viral pathogen to adapt to become more efficiently transmitted from person to person and possibly become more virulent. Two previous coronavirus outbreaks had been reported in the 21st century. The clinical features of 2019-nCoV, in comparison with SARS-CoV and Middle East respiratory syndrome (MERS)-CoV, are summarised in the table. The ongoing 2019-nCoV outbreak has undoubtedly caused the memories of the SARS-CoV outbreak starting 17 years ago to resurface in many people. In November, 2002, clusters of pneumonia of unknown cause were reported in Guangdong province, China, now known as the SARS-CoV outbreak. The number of cases of SARS increased substantially in the next year in China and later spread globally, 14 infecting at least 8096 people and causing 774 deaths. 12 The international spread of SARS-CoV in 2003 was attributed to its strong transmission ability under specific circumstances and the insufficient preparedness and implementation of infection control practices. Chinese public health and scientific capabilities have been greatly transformed since 2003. An efficient system is ready for monitoring and responding to infectious disease outbreaks and the 2019-nCoV pneumonia has been quickly added to the Notifiable Communicable Disease List and given the highest priority by Chinese health authorities. The increasing number of cases and widening geographical spread of the disease raise grave concerns about the future trajectory of the outbreak, especially with the Chinese Lunar New Year quickly approaching. Under normal circumstances, an estimated 3 billion trips would be made in the Spring Festival travel rush this year, with 15 million trips happening in Wuhan. The virus might further spread to other places during this festival period and cause epidemics, especially if it has acquired the ability to efficiently transmit from person to person. Consequently, the 2019-nCoV outbreak has led to implementation of extraordinary public health measures to reduce further spread of the virus within China and elsewhere. Although WHO has not recommended any international travelling restrictions so far, 15 the local government in Wuhan announced on Jan 23, 2020, the suspension of public transportation, with closure of airports, railway stations, and highways in the city, to prevent further disease transmission. 16 Further efforts in travel restriction might follow. Active surveillance for new cases and close monitoring of their contacts are being implemented. To improve detection efficiency, front-line clinics, apart from local centres for disease control and prevention, should be armed with validated point-of-care diagnostic kits. Rapid information disclosure is a top priority for disease control and prevention. A daily press release system has been established in China to ensure effective and efficient disclosure of epidemic information. Education campaigns should be launched to promote precautions for travellers, including frequent hand-washing, cough etiquette, and use of personal protection equipment (eg, masks) when visiting public places. Also, the general public should be motivated to report fever and other risk factors for coronavirus infection, including travel history to affected area and close contacts with confirmed or suspected cases. Considering that substantial numbers of patients with SARS and MERS were infected in health-care settings, precautions need to be taken to prevent nosocomial spread of the virus. Unfortunately, 16 health-care workers, some of whom were working in the same ward, have been confirmed to be infected with 2019-nCoV to date, although the routes of transmission and the possible role of so-called super-spreaders remain to be clarified. 9 Epidemiological studies need to be done to assess risk factors for infection in health-care personnel and quantify potential subclinical or asymptomatic infections. Notably, the transmission of SARS-CoV was eventually halted by public health measures including elimination of nosocomial infections. We need to be wary of the current outbreak turning into a sustained epidemic or even a pandemic. The availability of the virus' genetic sequence and initial data on the epidemiology and clinical consequences of the 2019-nCoV infections are only the first steps to understanding the threat posed by this pathogen. Many important questions remain unanswered, including its origin, extent, and duration of transmission in humans, ability to infect other animal hosts, and the spectrum and pathogenesis of human infections. Characterising viral isolates from successive generations of human infections will be key to updating diagnostics and assessing viral evolution. Beyond supportive care, 17 no specific coronavirus antivirals or vaccines of proven efficacy in humans exist, although clinical trials of both are ongoing for MERS-CoV and one controlled trial of ritonavir-boosted lopinavir monotherapy has been launched for 2019-nCoV (ChiCTR2000029308). Future animal model and clinical studies should focus on assessing the effectiveness and safety of promising antiviral drugs, monoclonal and polyclonal neutralising antibody products, and therapeutics directed against immunopathologic host responses. We have to be aware of the challenge and concerns brought by 2019-nCoV to our community. Every effort should be given to understand and control the disease, and the time to act is now. This online publication has been corrected. The corrected version first appeared at thelancet.com on January 29, 2020

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Estimates of the severity of coronavirus disease 2019: a model-based analysis

Robert Verity, Lucy C Okell, Ilaria Dorigatti … (2020)

Summary Background In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. Methods We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. Findings Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9–19·2) and to hospital discharge to be 24·7 days (22·9–28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56–3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23–1·53), with substantially higher ratios in older age groups (0·32% [0·27–0·38] in those aged <60 years vs 6·4% [5·7–7·2] in those aged ≥60 years), up to 13·4% (11·2–15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4–3·5] in those aged <60 years [n=360] and 4·5% [1·8–11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39–1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0–7·6) in those aged 80 years or older. Interpretation These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. Funding UK Medical Research Council.

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Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020

Kenji Mizumoto, Katsushi Kagaya, Alexander Zarebski … (2020)

On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking. As at 20 February, 634 persons on board tested positive for the causative virus. We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5–20.2%). Most infections occurred before the quarantine start.

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Author and article information

Contributors

Anthony Hauser:

ORCID: http://orcid.org/0000-0002-7221-1929

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: SoftwareRole: Writing – original draftRole: Writing – review & editing

Michel J. Counotte:

ORCID: http://orcid.org/0000-0003-1039-6873

Role: Data curationRole: Formal analysisRole: Writing – review & editing

Charles C. Margossian:

ORCID: http://orcid.org/0000-0002-3274-5619

Role: SoftwareRole: Writing – review & editing

Garyfallos Konstantinoudis:

ORCID: http://orcid.org/0000-0001-7493-9334

Role: Formal analysisRole: Writing – review & editing

Nicola Low:

ORCID: http://orcid.org/0000-0003-4817-8986

Role: ValidationRole: Writing – review & editing

Christian L. Althaus: Role: ValidationRole: Writing – review & editing

Julien Riou:

ORCID: http://orcid.org/0000-0002-3808-2852

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing

Yuming Guo: Role: Academic Editor

Journal

Journal ID (nlm-ta): PLoS Med

Journal ID (iso-abbrev): PLoS Med

Journal ID (publisher-id): plos

Journal ID (pmc): plosmed

Title: PLoS Medicine

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Print): 1549-1277

ISSN (Electronic): 1549-1676

Publication date (Electronic): 28 July 2020

Publication date Collection: July 2020

Volume: 17

Issue: 7

Electronic Location Identifier: e1003189

Affiliations

[1 ] Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland

[2 ] Department of Statistics, Columbia University, New York, New York, United States of America

[3 ] MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom

[4 ] Division of infectious diseases, Federal Office of Public Health, Bern, Switzerland

Monash University, Australia

Author notes

I have read the journal's policy and the authors of this manuscript have the following competing interests: NL is a member of the editorial board of PLOS Medicine.

* E-mail: julien.riou@ 123456ispm.unibe.ch

Author information

Anthony Hauser http://orcid.org/0000-0002-7221-1929

Michel J. Counotte http://orcid.org/0000-0003-1039-6873

Charles C. Margossian http://orcid.org/0000-0002-3274-5619

Garyfallos Konstantinoudis http://orcid.org/0000-0001-7493-9334

Nicola Low http://orcid.org/0000-0003-4817-8986

Julien Riou http://orcid.org/0000-0002-3808-2852

Article

Publisher ID: PMEDICINE-D-20-00987

DOI: 10.1371/journal.pmed.1003189

PMC ID: 7386608

PubMed ID: 32722715

SO-VID: 746d6d04-1ce1-4f43-93f6-b05d14858c1b

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 22 March 2020

Date accepted : 23 June 2020

Page count

Figures: 4, Tables: 1, Pages: 17

Funding

Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH)

Award ID: 174281

Award Recipient :

ORCID: http://orcid.org/0000-0002-3808-2852

Julien Riou

Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH)

Award ID: 176233

Award Recipient :

ORCID: http://orcid.org/0000-0003-1039-6873

Michel J. Counotte

Funded by: funder-id http://dx.doi.org/10.13039/501100007601, Horizon 2020;

Award ID: 101003688

Award Recipient : Christian L. Althaus

JR is funded by the Swiss National Science Foundation (grant 174281). MJC is funded by the Swiss National Science Foundation (grant 176233). This project has received funding from the European Union's Horizon 2020 research and innovation programme - project EpiPose (No 101003688). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Data Availability All code and data are available from https://github.com/jriou/covid_adjusted_cfr.

Outbreaks COVID-19

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ScienceOpen disciplines: Medicine

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Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe

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Novel Coronavirus Disease COVID-19

Most cited references 19

A novel coronavirus outbreak of global health concern

Estimates of the severity of coronavirus disease 2019: a model-based analysis

Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020

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