The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
Open accessPublished version of a preprint
Abstract
Motivated by the rapid spread of coronavirus disease 2019 (COVID-19) in mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated on the basis of internationally reported cases and shows that, at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-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.
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“Most of the studies reviewed acknowledged that quarantine is one of the first public health measures to control and prevent further spread of respirational infections caused by the coronavirus (3, 11, 14, 22).”
From Definitions and psychological impacts of quarantine and strategies to reduce it: A review paper (2020) · cites this paper as [14]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“These studies referred to travel restrictions as travel quarantine, which included the restriction or cancellation of overland air travel and public and private vehicles to areas of a high risk of the outbreak (14).”
From Definitions and psychological impacts of quarantine and strategies to reduce it: A review paper (2020) · cites this paper as [14]
Experimental — accuracy not yet measuredIn the citing paper
“Using disease simulation on aggregated inter-province movement counts in China as derived from Baidu location based services [101] has shown that the travel restrictions in Wuhan introduced on 23 January 2020 had reduced the number of cases exported internationally by 70–80% until mid February 2020.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [101]
In the citing paper
“Several studies across different countries have shown their effectiveness [101,102].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [101]
In the citing paper
“Affected travelers are required to undergo compulsory self-quarantine for 14 days (Chinazzi et al., 2020) before any test of swab is issued.”
From IoMT amid COVID-19 pandemic: Application, architecture, technology, and security (2021) · cites this paper as Chinazzi et al., 2020
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Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Correspondence - Tranexamic acid for traumatic brain injury
(2005) · London School of Economics and Political Science Theses Online (London School of Economics and Political Science) · doi:10.1016/s0140-6736 · Cited by 11,894
Wu, J. T., Leung, K., & Leung, G. M. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30260-9 · Cited by 4,389
Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., et al. (2020) · Science · doi:10.1126/science.abb6105 · Cited by 2,010
Zhao, S., Lin, Q., Ran, J., Musa, S. S., Yang, G., Wang, W., Lou, Y., Gao, D., Yang, L., He, D., et al. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.01.050 · Cited by 1,852
Backer, J. A., Klinkenberg, D., & Wallinga, J. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.5.2000062 · Cited by 1,546
Transmission Dynamics and Control of Severe Acute Respiratory Syndrome
Lipsitch, M., Cohen, T., Cooper, B. S., Robins, J. M., Ma, S., James, L., Gopalakrishna, G., Chew, S. K., Tan, C. C., Samore, M. H., et al. (2003) · Science · doi:10.1126/science.1086616 · Cited by 1,485
Riou, J., & Althaus, C. L. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.4.2000058 · Cited by 1,354
Multiscale mobility networks and the spatial spreading of infectious diseases
Balcan, D., Vittoria Colizza, A., Gonçalves, B., Hu, H., Ramasco, J. J., & Vespignani, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906910106 · Cited by 1,347
Self-citationRiley, S., Fraser, C., Donnelly, C. A., Ghani, A. C., Abu-Raddad, L. J., Hedley, A. J., Leung, G. M., Ho, L., Lam, T.-H., Thach, T., et al. (2003) · Science · doi:10.1126/science.1086478 · Cited by 1,152
Read, J. M., Bridgen, J. R. E., Cummings, D. A. T., Ho, A. Y. W., & Jewell, C. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0265 · Cited by 992
Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictionsPreprint
Read, J. M., Bridgen, J. R. E., Cummings, D. A. T., et al. (2020) · medRxiv · doi:10.1101/2020.01.23.20018549 · Cited by 951
Approximate Bayesian Computation
Sunnåker, M., Busetto, A. G., Numminen, E., Corander, J., Foll, M., & Dessimoz, C. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002803 · Cited by 636
Sun, K., Chen, J., & Viboud, C. G. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30026-1 · Cited by 523
Self-citationBalcan, D., Gonçalves, B., Hu, H., Ramasco, J., Colizza, V., & Vespignani, A. (2010) · Journal of Computer Science · doi:10.1016/j.jocs.2010.07.002 · Cited by 515
Self-citationRisk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China
Du, Z., Wang, L., Cauchemez, S., Xu, X.-K., Wang, X., Cowling, B. J., & Ancel, L. W. (2020) · Emerging infectious diseases · doi:10.3201/eid2605.200146 · Cited by 382
Spread of Zika virus in the Americas
Zhang, Q., Sun, K., Chinazzi, M., y Piontti, A. P., Dean, N. E., Rojas, D. P., Merler, S., Mistry, D., Poletti, P., Rossi, L. C., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620161114 · Cited by 335
Self-citationAssessing the International Spreading Risk Associated with the 2014 West African Ebola Outbreak
Gomes, M. F. D. C., y Piontti, A. P., Rossi, L. C., Chao, D. L., Longini, I. M., Halloran, M. E., & Vespignani, A. (2014) · PLoS Currents · doi:10.1371/currents.outbreaks.cd818f63d40e24aef769dda7df9e0da5 · Cited by 330
Self-citationBalcan, D., Hu, H., Goncalves, B., Bajardi, P., Poletto, C., Ramasco, J. J., Paolotti, D., Perra, N., Tizzoni, M., Van Den Broeck, W., et al. (2009) · PORTO Publications Open Repository TOrino (Politecnico di Torino) · Cited by 311
Self-citationBalcan, D., Hu, H., Gonçalves, B., Bajardi, P., Poletto, C., Ramasco, J. J., Paolotti, D., Perra, N., Tizzoni, M., den Broeck, W. V., et al. (2009) · BMC Medicine · doi:10.1186/1741-7015-7-45 · Cited by 303
Self-citationSalazar, P. M. D., Niehus, R., Taylor, A. R., Buckee, C. O., & Lipsitch, M. (2020) · Emerging infectious diseases · doi:10.3201/eid2607.200250 · Cited by 116
Tian, H., Liu, Y., Li, Y., et al. (2020) · medRxiv · doi:10.1101/2020.01.30.20019844 · Cited by 114
Niehus, R., Salazar, P. M. D., Taylor, A. R., & Lipsitch, M. (2020) · medRxiv · doi:10.1101/2020.02.13.20022707 · Cited by 91
Salazar, P. M. D., Niehus, R., Taylor, A. R., et al. (2020) · medRxiv · doi:10.1101/2020.02.04.20020495 · Cited by 83
Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study
Pinotti, F., Domenico, L. D., Ortega, E., Mancastroppa, M., Pullano, G., Valdano, E., Boëlle, P., Poletto, C., & Vittoria Colizza, A. (2020) · PLoS Medicine · doi:10.1371/journal.pmed.1003193 · Cited by 65
Drake, J. M., Chew, S. K., & Ma, S. (2006) · PLoS ONE · doi:10.1371/journal.pone.0000020 · Cited by 60
Pinotti, F., Domenico, L. D., Ortega, E., et al. (2020) · medRxiv · doi:10.1101/2020.02.24.20027326 · Cited by 29
Early epidemiological analysis of the 2019-nCoV outbreak based on a crowdsourced dataPreprint
Sun, K., Chen, J., & Viboud, C. G. (2020) · medRxiv · doi:10.1101/2020.01.31.20019935 · Cited by 22
Self-citationRisk of 2019 novel coronavirus importations throughout China prior to the Wuhan quarantinePreprint
Du, Z., Wang, L., Cauchemez, S., Xu, X.-K., Wang, X., Cowling, B. J., & Ancel, L. W. (2020) · medRxiv · doi:10.1101/2020.01.28.20019299 · Cited by 20
Genomic analysis of nCoV spread. Situation report 2020-01-23.
Bedford, T., Neher, R. A., Hadfield, J., Hodcroft, E. B., Ilcisin, M., & Müller, N. F. (2020) · ResearchWorks at the University of Washington (University of Washington) · Cited by 11
Cited by
Sorted by citations
Characteristics of SARS-CoV-2 and COVID-19
Hu, B., Guo, H., Zhou, P., & Shi, Z.-L. (2021) · Nature Reviews Microbiology · doi:10.1038/s41579-020-00459-7 · Cited by 5,291
Pan, A., Liu, L., Wang, C., Guo, H., Hao, X., Wang, Q., Huang, J., He, N., Yu, H., Lin, X., et al. (2020) · JAMA · doi:10.1001/jama.2020.6130 · Cited by 1,931
Self-citationHuman neutralizing antibodies elicited by SARS-CoV-2 infection
Ju, B., Zhang, Q., Ge, J., Wang, R., Sun, J., Ge, X., Yu, J., Shan, S., Zhou, B., Song, S., et al. (2020) · Nature · doi:10.1038/s41586-020-2380-z · Cited by 1,667
Mobility network models of COVID-19 explain inequities and inform reopening
Chang, S., Pierson, E., Koh, P. W., Gerardin, J., Redbird, B., Grusky, D., & Leskovec, J. (2021) · Nature · doi:10.1038/s41586-020-2923-3 · Cited by 1,533
Ranking the effectiveness of worldwide COVID-19 government interventions
Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars-Larrive, A., Loreto, V., Pinior, B., Thurner, S., & Klimek, P. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-01009-0 · Cited by 1,412
Metadata
- Authors
- Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., Viboud, C., Xiong, X., Yu, H., Halloran, M. E., Longini, I. M., & Vespignani, A.
- Affiliations
- Northeastern University (US)
- Fondazione Bruno Kessler (IT)
- Institute for Scientific Interchange (IT)
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
- National Institutes of Health (US)
- Fogarty International Center, NIH, Bethesda, MD, USA.
- Fudan University (CN)
- University of Washington (US)
- University of Florida Health (US)
- Corresponding author
- Longini, Ira M.
- Vespignani, Alessandro
- ORCID
- Venue
- Science
- Published
- 2020-04-24
- Volume
- 368
- Issue
- 6489
- Pages
- 395-400
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7164386
- OpenAlex
- W3010131837
- Cited by
- 3,694
- References
- 30
- Citations by year
- 2026: 87 · 2025: 173 · 2024: 244 · 2023: 405 · 2022: 644 · 2021: 1101 · 2020: 1036
- FWCI
- 127.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- U.S. Department of Health and Human Services
- National Institutes of Health (H2020, MIDAS-U54-GM111274)
- Horizon 2020 Framework Programme (EU‐H2020)
- National Institute of General Medical Sciences (U54GM111274)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Travel-related health issues
- Keywords
- COVID-19 pandemic, travel restrictions, metapopulation model, epidemic projection, international spread, quarantine, epidemic control
- MeSH terms
- Betacoronavirus, Communicable Diseases, Imported, COVID-19, SARS-CoV-2, China, Computer Simulation, Disease Outbreaks, Humans, Pneumonia, Viral, Quarantine, Travel, Models, Statistical, Incidence, Coronavirus Infections, Internationality, Pandemics
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