» Articles » PMID: 32014114

Nowcasting and Forecasting the Potential Domestic and International Spread of the 2019-nCoV Outbreak Originating in Wuhan, China: a Modelling Study

Overview
Journal Lancet
Publisher Elsevier
Specialty General Medicine
Date 2020 Feb 5
PMID 32014114
Citations 1880
Authors
Affiliations
Soon will be listed here.
Abstract

Background: 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.

Methods: 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).

Findings: 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.

Interpretation: 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.

Funding: Health and Medical Research Fund (Hong Kong, China).

Citing Articles

Terminating pandemics with smartwatches.

Vesinurm M, Ndeffo-Mbah M, Yamin D, Brandeau M PNAS Nexus. 2025; 4(3):pgaf044.

PMID: 40045996 PMC: 11879515. DOI: 10.1093/pnasnexus/pgaf044.


Dynamical analysis and numerical assessment of the 2019-nCoV virus transmission with optimal control.

Li S, Khan T, Al-Mdallal Q, Awwad F, Zaman G Sci Rep. 2025; 15(1):7587.

PMID: 40038386 PMC: 11880544. DOI: 10.1038/s41598-025-90915-2.


Embedding risk monitoring in infectious disease surveillance for timely and effective outbreak prevention and control.

Ingelbeen B, van Kleef E, Mbala P, Danis K, Macicame I, Hens N BMJ Glob Health. 2025; 10(2).

PMID: 39961690 PMC: 11836831. DOI: 10.1136/bmjgh-2024-016870.


Prediction of COVID-19 cases by multifactor driven long short-term memory (LSTM) model.

Shao Y, Wan T, Katie Chan K Sci Rep. 2025; 15(1):4935.

PMID: 39929873 PMC: 11811167. DOI: 10.1038/s41598-025-86698-1.


Ultra-Sensitive Aptamer-Based Diagnostic Systems for Rapid Detection of All SARS-CoV-2 Variants.

Kim S, Han M, Rahman M, Kim H, Noh J, Lee M Int J Mol Sci. 2025; 26(2.

PMID: 39859459 PMC: 11766214. DOI: 10.3390/ijms26020745.


References
1.
Leung G, Lim W, Ho L, Lam T, Ghani A, Donnelly C . Seroprevalence of IgG antibodies to SARS-coronavirus in asymptomatic or subclinical population groups. Epidemiol Infect. 2006; 134(2):211-21. PMC: 2870380. DOI: 10.1017/S0950268805004826. View

2.
Cowling B, Park M, Fang V, Wu P, Leung G, Wu J . Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015. Euro Surveill. 2015; 20(25):7-13. PMC: 4535930. DOI: 10.2807/1560-7917.es2015.20.25.21163. View

3.
Al Kahlout R, Nasrallah G, Farag E, Wang L, Lattwein E, Muller M . Comparative Serological Study for the Prevalence of Anti-MERS Coronavirus Antibodies in High- and Low-Risk Groups in Qatar. J Immunol Res. 2019; 2019:1386740. PMC: 6398027. DOI: 10.1155/2019/1386740. View

4.
Oh M, Beom Park W, Park S, Choe P, Bang J, Song K . Middle East respiratory syndrome: what we learned from the 2015 outbreak in the Republic of Korea. Korean J Intern Med. 2018; 33(2):233-246. PMC: 5840604. DOI: 10.3904/kjim.2018.031. View

5.
Chowell G, Abdirizak F, Lee S, Lee J, Jung E, Nishiura H . Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study. BMC Med. 2015; 13:210. PMC: 4558759. DOI: 10.1186/s12916-015-0450-0. View