Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study
Identifieur interne : 000164 ( Pmc/Checkpoint ); précédent : 000163; suivant : 000165Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study
Auteurs : Joseph T. Wu [République populaire de Chine] ; Kathy Leung [République populaire de Chine] ; Gabriel M. Leung [République populaire de Chine]Source :
- Lancet (London, England) [ 0140-6736 ] ; 2020.
Abstract
Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions.
We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23–24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI).
In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47–2·86) and that 75 815 individuals (95% CrI 37 304–130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8–7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227–805), 113 (57–193), 98 (49–168), 111 (56–191), and 80 (40–139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1–2 weeks.
Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally.
Health and Medical Research Fund (Hong Kong, China).
Url:
DOI: 10.1016/S0140-6736(20)30260-9
PubMed: 32014114
PubMed Central: 7159271
Affiliations:
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<series><title level="j">Lancet (London, England)</title>
<idno type="ISSN">0140-6736</idno>
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<front><div type="abstract" xml:lang="en"><title>Summary</title>
<sec><title>Background</title>
<p>Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions.</p>
</sec>
<sec><title>Methods</title>
<p>We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23–24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI).</p>
</sec>
<sec><title>Findings</title>
<p>In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47–2·86) and that 75 815 individuals (95% CrI 37 304–130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8–7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227–805), 113 (57–193), 98 (49–168), 111 (56–191), and 80 (40–139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1–2 weeks.</p>
</sec>
<sec><title>Interpretation</title>
<p>Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally.</p>
</sec>
<sec><title>Funding</title>
<p>Health and Medical Research Fund (Hong Kong, China).</p>
</sec>
</div>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Lancet</journal-id>
<journal-id journal-id-type="iso-abbrev">Lancet</journal-id>
<journal-title-group><journal-title>Lancet (London, England)</journal-title>
</journal-title-group>
<issn pub-type="ppub">0140-6736</issn>
<issn pub-type="epub">1474-547X</issn>
<publisher><publisher-name>Elsevier Ltd.</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">32014114</article-id>
<article-id pub-id-type="pmc">7159271</article-id>
<article-id pub-id-type="publisher-id">S0140-6736(20)30260-9</article-id>
<article-id pub-id-type="doi">10.1016/S0140-6736(20)30260-9</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" id="au10"><name><surname>Wu</surname>
<given-names>Joseph T</given-names>
</name>
<degrees>Prof</degrees>
<degrees>PhD</degrees>
<email>joewu@hku.hk</email>
<xref rid="aff1" ref-type="aff">a</xref>
<xref rid="cor1" ref-type="corresp">*</xref>
<xref rid="fn1" ref-type="fn">*</xref>
</contrib>
<contrib contrib-type="author" id="au20"><name><surname>Leung</surname>
<given-names>Kathy</given-names>
</name>
<degrees>PhD</degrees>
<xref rid="aff1" ref-type="aff">a</xref>
<xref rid="fn1" ref-type="fn">*</xref>
</contrib>
<contrib contrib-type="author" id="au30"><name><surname>Leung</surname>
<given-names>Gabriel M</given-names>
</name>
<degrees>Prof</degrees>
<degrees>MD</degrees>
<xref rid="aff1" ref-type="aff">a</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>a</label>
WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China</aff>
<author-notes><corresp id="cor1"><label>*</label>
Correspondence to: Prof Joseph T Wu, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China <email>joewu@hku.hk</email>
</corresp>
<fn id="fn1"><label>*</label>
<p id="cenpara20">Contributed equally</p>
</fn>
</author-notes>
<pub-date pub-type="pmc-release"><day>31</day>
<month>1</month>
<year>2020</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub" iso-8601-date="2020-03-06"><season>29 February-6 March</season>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub"><day>31</day>
<month>1</month>
<year>2020</year>
</pub-date>
<volume>395</volume>
<issue>10225</issue>
<fpage>689</fpage>
<lpage>697</lpage>
<permissions><copyright-statement>© 2020 Elsevier Ltd. All rights reserved.</copyright-statement>
<copyright-year>2020</copyright-year>
<copyright-holder>Elsevier Ltd</copyright-holder>
<license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p>
</license>
</permissions>
<abstract id="ceab10"><title>Summary</title>
<sec><title>Background</title>
<p>Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions.</p>
</sec>
<sec><title>Methods</title>
<p>We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23–24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI).</p>
</sec>
<sec><title>Findings</title>
<p>In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47–2·86) and that 75 815 individuals (95% CrI 37 304–130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8–7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227–805), 113 (57–193), 98 (49–168), 111 (56–191), and 80 (40–139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1–2 weeks.</p>
</sec>
<sec><title>Interpretation</title>
<p>Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally.</p>
</sec>
<sec><title>Funding</title>
<p>Health and Medical Research Fund (Hong Kong, China).</p>
</sec>
</abstract>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>République populaire de Chine</li>
</country>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Wu, Joseph T" sort="Wu, Joseph T" uniqKey="Wu J" first="Joseph T" last="Wu">Joseph T. Wu</name>
</noRegion>
<name sortKey="Leung, Gabriel M" sort="Leung, Gabriel M" uniqKey="Leung G" first="Gabriel M" last="Leung">Gabriel M. Leung</name>
<name sortKey="Leung, Kathy" sort="Leung, Kathy" uniqKey="Leung K" first="Kathy" last="Leung">Kathy Leung</name>
</country>
</tree>
</affiliations>
</record>
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