The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Delaying the International Spread of Pandemic Influenza
Open accessAbstract
BACKGROUND: The recent emergence of hypervirulent subtypes of avian influenza has underlined the potentially devastating effects of pandemic influenza. Were such a virus to acquire the ability to spread efficiently between humans, control would almost certainly be hampered by limited vaccine supplies unless global spread could be substantially delayed. Moreover, the large increases that have occurred in international air travel might be expected to lead to more rapid global dissemination than in previous pandemics. METHODS AND FINDINGS: To evaluate the potential of local control measures and travel restrictions to impede global dissemination, we developed stochastic models of the international spread of influenza based on extensions of coupled epidemic transmission models. These models have been shown to be capable of accurately forecasting local and global spread of epidemic and pandemic influenza. We show that under most scenarios restrictions on air travel are likely to be of surprisingly little value in delaying epidemics, unless almost all travel ceases very soon after epidemics are detected. CONCLUSIONS: Interventions to reduce local transmission of influenza are likely to be more effective at reducing the rate of global spread and less vulnerable to implementation delays than air travel restrictions. Nevertheless, under the most plausible scenarios, achievable delays are small compared with the time needed to accumulate substantial vaccine stocks.
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Cites
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Cited by
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
Early dynamics of transmission and control of COVID-19: a mathematical modelling study
Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Eggo, R. M., Sun, F., Jit, M., Munday, J. D., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30144-4 · Cited by 2,671
Multiscale mobility networks and the spatial spreading of infectious diseases
Balcan, D., Colizza, V., Gonçalves, B., Hu, H., Ramasco, J. J., & Vespignani, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906910106 · Cited by 1,380
The Hidden Geometry of Complex, Network-Driven Contagion Phenomena
Brockmann, D., & Helbing, D. (2013) · Science · doi:10.1126/science.1245200 · Cited by 1,253
Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions
Colizza, V., Barrat, A., Barthelemy, M., Valleron, A.-J., & Vespignani, A. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040013 · Cited by 710
Metadata
- Authors
- Cooper, B. S., Pitman, R. J., Edmunds, W. J., & Gay, N. J.
- Venue
- PLoS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2006-05-02
- Volume
- 3
- Issue
- 6
- Pages
- e212
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- OpenAlex
- W2102842925
- Cited by
- 305
- References
- 28
- FWCI
- 16.38
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
