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The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
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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.
In the citing paper
“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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Karataş, M., Erişkin, L., & Bozkaya, E. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3166724 · Cited by 24
Dynamics of information-awareness-epidemic-activity coevolution in multiplex networks
Chen, J., Hu, M.-B., & Cao, J. (2023) · Physical Review Research · doi:10.1103/physrevresearch.5.033065 · Cited by 24
Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots
Muylaert, R. L., Wilkinson, D. A., Kingston, T., D’Odorico, P., Rulli, M. C., Galli, N., John, R. S., Alviola, P., & Hayman, D. T. S. (2023) · Nature Communications · doi:10.1038/s41467-023-42627-2 · Cited by 20
Núñez, M. T. D. V., Ancillo, A. D. L., Gavrila, S. G., & Gandía, J. A. G. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123168 · Cited by 24
Liu, G., Wang, X., Yu, J., & Ding, B. (2024) · Separation and Purification Technology · doi:10.1016/j.seppur.2024.126575 · Cited by 25
Bird, J. J., Barnes, C. M., Premebida, C., Ekárt, A., & Faria, D. R. (2020) · PLoS ONE · doi:10.1371/journal.pone.0241332 · Cited by 24
Pomponi, F., Li, M., Sun, Y., Malik, A., Manfred Lenzen, A., Fountas, G., D’Amico, B., Akizu‐Gardoki, O., & Anguita, M. L. (2020) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.0c00764 · Cited by 24
Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study
Großmann, G., Backenköhler, M., & Wolf, V. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59854-9_16 · Cited by 24
Zheng, W., Kämpfen, F., & Huang, Z. (2021) · Scientific Reports · doi:10.1038/s41598-021-96888-2 · Cited by 24
Making decisions to mitigate COVID-19 with limited knowledge
Zhang, W., & Qian, B.-Y. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30280-2 · Cited by 24
Definitions and psychological impacts of quarantine and strategies to reduce it: A review paper
Sadeghmoghadam, L., Khoshkhoo, M., & Saadati, N. (2020) · Iranian Journal of Psychiatry and Behavioral Sciences · doi:10.5812/ijpbs.103501 · Cited by 1
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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