Evidence map›Paper›PMID 32240634›Full record

ArticleThe Lancet. Infectious diseases2020

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

Robert Verity, Lucy C Okell, Ilaria Dorigatti, Peter Winskill, Charles Whittaker, Natsuko Imai, Gina Cuomo-Dannenburg, Hayley Thompson, Patrick G T Walker, Han Fu and 23 more

Erratum issued 8 registry-linked trialsAbstract read
In one paragraph

Article in The Lancet. Infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to 8 registered trials, which are not on this map. Cited by 1,869 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,869citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04366739 phase3withdrawnnot on this map

Repurposing of Chlorpromazine in Covid-19 Treatment

TypeinterventionalSponsorCentre Hospitalier St AnneRan2020 to 2020Enrolled0ConditionsCOVID-19ArmsCHLORPROMAZINE (CPZ), Standard of Care (SOC)
NCT04369807 completednot on this map

Mapping Organ Health Following COVID-19 Disease Due to SARS-CoV-2 Infection

TypeobservationalSponsorPerspectumRan2020 to 2022Enrolled693ConditionsCOVID-19ArmsOutpatient MRI
NCT04397328 phase3withdrawnnot on this map

Safety and Efficacy of Post-exposure Prophylaxis With Hydroxychloroquine (HCQ) for the Prevention of COVID-19 in High-risk Older Individuals in Long-term and Specialized Care: A Double-blind Randomized Control Trial

TypeinterventionalSponsorLondon Health Sciences Centre Research Institute OR Lawson Research Institute of St. Joseph'sRan2020 to 2021Enrolled0ConditionsCOVID-19ArmsHydroxychloroquine, Placebo
NCT04492254 phase3terminatednot on this map

Early Thromboprophylaxis in COVID-19 (ETHIC Trial): an Open Label, Randomized Phase IIIb Trial of Community-based (LMWH) Versus Standard of Care (no Enoxaparin) in COVID-19 Positive Patients

TypeinterventionalSponsorThrombosis Research InstituteRan2020 to 2021Enrolled219ConditionsCOVID-19ArmsEnoxaparin
NCT04567979 completednot on this map

Prospective Determination of COVID-19 Infection Rate in Patients With Solid Tumors and Healthcare Workers of the Chemotherapy and Radiotherapy Unit at the Instituto Nacional de Ciencias Médicas y Nutrición Salvador.

TypeobservationalSponsorInstituto Nacional de Ciencias Medicas y Nutricion Salvador ZubiranRan2020 to 2020Enrolled149ConditionsCovid19, Cancer, Tumor
NCT04716985 naunknown statusnot on this mapstarted 2021, after this paper: background citation

Evaluation of the Daily Intake of 0.5 L of Water Saturated With Molecular Hydrogen for 21 Days in COVID-19 Patients Treated in Ambulatory Care. Double-blind, Randomized, Comparative Study

TypeinterventionalSponsorAGIR à DomRan2021 to 2023Enrolled700ConditionsSARS-CoV-2, Covid19, AMBULATORY CAREArmsMOLECULAR HYDROGEN, PLACEBO MAGNESIUM
NCT04780152 phase2 / phase3unknown statusnot on this mapstarted 2021, after this paper: background citation

Assessment of Efficacy and Safety of Anodal Transcranial Direct Current Stimulation (TDCS) in Pediatric and Teenage Patients With Major Depressive Disorder During COVID-19 Pandemics

TypeinterventionalSponsorEl Instituto Nacional de Neurologia y Neurocirugia Manuel Velasco SuarezRan2021 to 2022Enrolled172ConditionsMajor Depressive DisorderArmsTranscranial Direct Current Stimulation, Placebo-simulation of transcranial direct current stimulation, Fluoxetine Tablets
NCT05446961 phase2completednot on this mapstarted 2021, after this paper: background citation

Pilot Phase II Randomized, Placebo-Controlled Clinical Trial for the Prevention and Progression of SARS-CoV-2 Infection of Subjects and Patients Using a Supplement Treatment With Carnipure Tartrate ( LCLT)

TypeinterventionalSponsorSENAI CIMATECRan2021 to 2022Enrolled224ConditionsCOVID-19 Virus InfectionArmsLCLT : 68% elemental L-carnitine and 32 % Tartric acid, Placebo
3 · Its place in the literature

Who cites it

1,869 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Dynamic Cytokine and Coagulation Profiling in Patients With Severe COVID‑19 Evaluated for Pulmonary Embolism: A Prospective Cohort Study.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Observational
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1,809 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

33 authors.

Robert VerityMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Lucy C OkellMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Ilaria DorigattiMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Peter WinskillMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Charles WhittakerMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Natsuko ImaiMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Gina Cuomo-DannenburgMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Hayley ThompsonMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Patrick G T WalkerMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Han FuMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Amy DigheMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Jamie T GriffinSchool of Mathematical Sciences, Queen Mary University of London, London, UK.
Marc BaguelinMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Sangeeta BhatiaMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Adhiratha BoonyasiriMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Anne CoriMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Zulma CucunubáMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Rich FitzJohnMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Katy GaythorpeMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Will GreenMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Arran HamletMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Wes HinsleyMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Daniel LaydonMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Gemma Nedjati-GilaniMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Steven RileyMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Sabine van ElslandMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Erik VolzMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Haowei WangMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Yuanrong WangMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Xiaoyue XiMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Christl A DonnellyMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Department of Statistics, University of Oxford, Oxford, UK.
Azra C GhaniMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK. Electronic address: a.ghani@imperial.ac.uk.
Neil M FergusonMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK. Electronic address: neil.ferguson@imperial.ac.uk.

Funding

Medical Research Council MR/J008761/1Medical Research Council MR/R015600/1Wellcome Trust 200861/Z/16/Z
6 · The paper itself

Abstract

backgroundIn 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.

methodsWe 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.

findingsUsing 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% (11·0-37·6) in those aged 80 years or older.

interpretationThese 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.

fundingUK Medical Research Council.

Indexed as

AdolescentAdultAgedAged, 80 and overBetacoronavirusChildChild, PreschoolChinaCoronavirus InfectionsCOVID-19HospitalizationHumansIncidenceInfantInfant, NewbornMiddle Aged

Identifiers

PMID32240634
PMCPMC7158570

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.