Evidence map›Paper›PMID 32171059›Full record

ArticleThe Lancet. Infectious diseases2020

Early dynamics of transmission and control of COVID-19: a mathematical modelling study.

Adam J Kucharski, Timothy W Russell, Charlie Diamond, Yang Liu, John Edmunds, Sebastian Funk, Rosalind M Eggo, Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group

Erratum issuedOpen access · hybridAbstract 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. Cited by 1,129 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,129citing papers in PubMed, 3 pooled it
84.6field-weighted citation impact, top 1% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,129 citing papers in PubMed, 3 syntheses or guidelines pooled it, 2,643 citations in OpenAlex.

  1. Pooled it
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  6. Machine learning and probabilistic approaches for forecasting infectious disease transmission and cases.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2026
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  14. Real-time spatiotemporal tracking of infectious outbreaks in confined environments with a host-pathogen agent-based system.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  19. China's post-zero-COVID Omicron wave: A Bayesian analysis.Proceedings of the National Academy of Sciences of the United States of America · 2025
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1,069 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Adam J KucharskiCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: adam.kucharski@lshtm.ac.uk.
Timothy W RussellCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Charlie DiamondCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Yang LiuCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
John EdmundsCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Sebastian FunkCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Rosalind M EggoCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group
London School of Hygiene & Tropical Medicine · GB

Funding

Medical Research Council MR/S003975/1Wellcome Trust 206250/Z/17/ZWellcome Trust 208812/Z/17/Z
6 · The paper itself

Abstract

backgroundAn outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.

methodsWe combined a stochastic transmission model with data on cases of coronavirus disease 2019 (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020.

findingsWe estimated that the median daily reproduction number (R

interpretationOur results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually.

fundingWellcome Trust, Health Data Research UK, Bill & Melinda Gates Foundation, and National Institute for Health Research.

Indexed as

BetacoronavirusChinaCoronavirus InfectionsCOVID-19HumansModels, TheoreticalPandemicsPneumonia, ViralSARS-CoV-2Severe Acute Respiratory Syndrome

Identifiers

PMID32171059
PMCPMC7158569
OpenAlexW3009468976

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.