Impact of population movement on the spread of 2019-nCoV in China.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang C
PROVIDER: S-EPMC7269026 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Publications
Impact of population movement on the spread of 2019-nCoV in China.
Zhang Chi C Chen Cai C Shen Wei W Tang Feng F Lei Hao H Xie Yu Y Cao Zicheng Z Tang Kang K Bai Junbo J Xiao Lehan L Xu Yutian Y Song Yanxin Y Chen Jiwei J Guo Zhihui Z Guo Yichen Y Wang Xiao X Xu Modi M Zou Huachun H Shu Yuelong Y Du Xiangjun X
Emerging microbes & infections 20201201 1
Since Dec 2019, China has experienced an outbreak caused by a novel coronavirus, 2019-nCoV. A travel ban was implemented for Wuhan, Hubei on Jan 23 to slow down the outbreak. We found a significant positive correlation between population influx from Wuhan and confirmed cases in other cities across China (R<sup>2</sup> = 0.85, <i>P</i> < 0.001), especially cities in Hubei (R<sup>2</sup> = 0.88, <i>P</i> < 0.001). Removing the travel restriction would have increased 118% (91%-172%) of the overall ...[more]
Similar Datasets
Project description:We quantify the causal impact of human mobility restrictions, particularly the lockdown of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. The lockdown of Wuhan reduced inflows to Wuhan by 76.98%, outflows from Wuhan by 56.31%, and within-Wuhan movements by 55.91%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities - the epicenter of the 2019-nCoV outbreak - on the destination cities' new infection cases. We also provide evidence that the enhanced social distancing policies in the 98 Chinese cities outside Hubei province were effective in reducing the impact of the population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV in the destination cities. We find that in the counterfactual world in which Wuhan were not locked down on January 23, 2020, the COVID-19 cases would be 105.27% higher in the 347 Chinese cities outside Hubei province. Our findings are relevant in the global efforts in pandemic containment.
| S-EPMC7833277 | biostudies-literature
Project description:The global spread of the 2019-nCoV is continuing and is fast moving, as indicated by the WHO raising the risk assessment to high. In this article, we provide a preliminary phylodynamic and phylogeographic analysis of this new virus. A Maximum Clade Credibility tree has been built using the 29 available whole genome sequences of 2019-nCoV and two whole genome sequences that are highly similar sequences from Bat SARS-like Coronavirus available in GeneBank. We are able to clarify the mechanism of transmission among the countries which have provided the 2019-nCoV sequence isolates from their patients. The Bayesian phylogeographic reconstruction shows that the 2019-2020 nCoV most probably originated from the Bat SARS-like Coronavirus circulating in the Rhinolophus bat family. In agreement with epidemiological observations, the most likely geographic origin of the new outbreak was the city of Wuhan, China, where 2019-nCoV time of the most recent common ancestor emerged, according to molecular clock analysis, around November 25th, 2019. These results, together with previously recorded epidemics, suggest a recurring pattern of periodical epizootic outbreaks due to Betacoronavirus. Moreover, our study describes the same population genetic dynamic underlying the SARS 2003 epidemic, and suggests the urgent need for the development of effective molecular surveillance strategies of Betacoronavirus among animals and Rhinolophus of the bat family.
| S-EPMC7099638 | biostudies-literature
Project description:Traveller screening is being used to limit further global spread of 2019 novel coronavirus (nCoV) following its recent emergence. Here, we project the impact of different travel screening programs given remaining uncertainty around the values of key nCoV life history and epidemiological parameters. Even under best-case assumptions, we estimate that screening will miss more than half of infected travellers. Breaking down the factors leading to screening successes and failures, we find that most cases missed by screening are fundamentally undetectable, because they have not yet developed symptoms and are unaware they were exposed. These findings emphasize the need for measures to track travellers who become ill after being missed by a travel screening program. We make our model available for interactive use so stakeholders can explore scenarios of interest using the most up-to-date information. We hope these findings contribute to evidence-based policy to combat the spread of nCoV, and to prospective planning to mitigate future emerging pathogens.
| S-EPMC7216848 | biostudies-literature
Project description:Motivated by the rapid spread of a novel coronavirus (2019-nCoV) in Mainland China, we use a global metapopulation disease transmission model to project the impact of both domestic and international travel limitations on the national and international spread of the epidemic. The model is calibrated on the evidence of internationally imported cases before the implementation of the travel quarantine of Wuhan. By assuming a generation time of 7.5 days, the reproduction number is estimated to be 2.4 [90% CI 2.2-2.6]. The median estimate for number of cases before the travel ban implementation on January 23, 2020 is 58,956 [90% CI 40,759 - 87,471] in Wuhan and 3,491 [90% CI 1,924 - 7,360] in other locations in Mainland China. The model shows that as of January 23, most Chinese cities had already received a considerable number of infected cases, and the travel quarantine delays the overall epidemic progression by only 3 to 5 days. The travel quarantine has a more marked effect at the international scale, where we estimate the number of case importations to be reduced by 80% until the end of February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
| S-EPMC7216908 | biostudies-literature
Project description:BackgroundSince 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.MethodsWe 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).FindingsIn 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.InterpretationGiven 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.FundingHealth and Medical Research Fund (Hong Kong, China).
| S-EPMC7159271 | biostudies-literature
Project description: Not available
| S-EPMC7174828 | biostudies-literature
Project description:The 2019 novel coronavirus (2019-nCov) has caused increasing number of infected cases globally. This study was performed to analyze information regarding the transmission route and presence of viral nucleic acids on several clinical samples. Confirmed 2019-nCov-infected cases were identified in Dongyang and were treated according to guidelines for the diagnosis of 2019-nCov infection released by the National Health Commission. Information regarding the contacts that the infected people had was collected to determine whether it caused clustered cases. A series of successive nucleic acid examination of feces, oropharyngeal swabs, and sputum was also performed, and the results were analyzed. A total of 19 confirmed cases of 2019-nCov infection were identified in Dongyang, Zhejiang Province, China. Five cases showed severe symptoms, and the remaining ones showed mild manifestations. Ten cases infected from two asymptomatic individuals were clustered into two groups. Among 14 cases with consecutive nucleic acid test results, four patients showed positive results in feces after their negative conversion in oropharyngeal swabs. Asymptomatic individuals with the virus could cause 2019-nCov clustered cases, and the clustered cases may differ from sporadic cases on age and length of hospitalization. In addition, nucleic acids in feces last longer than those in oropharyngeal swabs.
| S-EPMC7324955 | biostudies-literature
Project description:The recent pandemic caused by the 2019 outbreak of novel coronavirus (2019-nCoV or COVID-19) has affected more than 3.0 million people resulting ~?212,000 deaths across 215 countries/territories as on 28th April 2020. The importation of the cases owing to enormous international travels from the affected countries is the foremost reason for local cycle of transmission. For a country like India, the second most populous country in the world with ~?1.35 billion population, the management and control of 2019-nCoV domestic spread heavily relied on effective screening and strict quarantine of passengers arriving at various international airports in India from affected countries. Here, by extracting the data from FLIRT, an online airline database for more than 800 airlines, and scanning more than 180,000 flights and 39.9 million corresponding passenger seats during 4th - 25th March, we show that India experienced the highest risk index of importing the passengers from middle eastern airports. Contrary to perception, travelers from China imposed lowest risk of importing the infected cases in India. This is clearly evident form the fact that while the number of infected cases were on the peak in China India was one of the least affected countries. The number of cases in India started exhibiting a sharp increase in the infected cases only after the European countries and USA recorded large number of infected cases. We further argue that while the number of cases in middle eastern countries may still be very low, the airports in middle eastern countries, particularly Dubai, being one of the largest transit hubs for international passengers, including arriving in India, might have posed a higher risk of getting infected with 2019-nCoV. We suggest that any future travel related disease infection screening at the airports should critically assess the passengers from major transit hubs in addition to affected country of origin.
| S-EPMC7216130 | biostudies-literature
Project description:An in-depth annotation of the newly discovered coronavirus (2019-nCoV) genome has revealed differences between 2019-nCoV and severe acute respiratory syndrome (SARS) or SARS-like coronaviruses. A systematic comparison identified 380 amino acid substitutions between these coronaviruses, which may have caused functional and pathogenic divergence of 2019-nCoV.
| S-EPMC7154514 | biostudies-literature
Project description:A novel coronavirus (2019-nCoV) is causing an outbreak of viral pneumonia that started in Wuhan, China. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan in the early outbreak phase, we estimate the mean incubation period to be 6.4 days (95% credible interval: 5.6-7.7), ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values should help inform 2019-nCoV case definitions and appropriate quarantine durations.
| S-EPMC7014672 | biostudies-literature