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Cited by 662

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Modeling targeted layered containment of an influenza pandemic in the United States

Open access
Halloran, M. Elizabeth, Ferguson, Neil M., Eubank, Stephen, Longini, Ira M., Cummings, Derek A. T., Lewis, Bryan, Xu, Shufu, Fraser, Christophe, Vullikanti, Anil, Germann, Timothy C., Wagener, Diane, Beckman, Richard, Kadau, Kai, Barrett, Chris, Macken, Catherine A., Burke, Donald S., Cooley, Philip·2008·Proceedings of the National Academy of Sciences

Abstract

Planning a response to an outbreak of a pandemic strain of influenza is a high public health priority. Three research groups using different individual-based, stochastic simulation models have examined the consequences of intervention strategies chosen in consultation with U.S. public health workers. The first goal is to simulate the effectiveness of a set of potentially feasible intervention strategies. Combinations called targeted layered containment (TLC) of influenza antiviral treatment and prophylaxis and nonpharmaceutical interventions of quarantine, isolation, school closure, community social distancing, and workplace social distancing are considered. The second goal is to examine the robustness of the results to model assumptions. The comparisons focus on a pandemic outbreak in a population similar to that of Chicago, with ≈8.6 million people. The simulations suggest that at the expected transmissibility of a pandemic strain, timely implementation of a combination of targeted household antiviral prophylaxis, and social distancing measures could substantially lower the illness attack rate before a highly efficacious vaccine could become available. Timely initiation of measures and school closure play important roles. Because of the current lack of data on which to base such models, further field research is recommended to learn more about the sources of transmission and the effectiveness of social distancing measures in reducing influenza transmission.

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Metadata

Authors
Halloran, M. E., Ferguson, N. M., Eubank, S., Longini, I. M., Cummings, D. A. T., Lewis, B., Xu, S., Fraser, C., Vullikanti, A., Germann, T. C., Wagener, D., Beckman, R., Kadau, K., Barrett, C., Macken, C. A., Burke, D. S., & Cooley, P.
Venue
Proceedings of the National Academy of Sciences
Published
2008-03-25
Volume
105
Issue
12
Pages
4639-4644
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2107324390
Cited by
662
References
2
FWCI
44.02
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Modeling targeted layered containment of an influenza pandemic in the United States. https://app.cochat.ai/papers/10.1073/pnas.0706849105
The paper
Halloran, M. E., Ferguson, N. M., Eubank, S., Longini, I. M., Cummings, D. A. T., Lewis, B., Xu, S., Fraser, C., Vullikanti, A., Germann, T. C., Wagener, D., Beckman, R., Kadau, K., Barrett, C., Macken, C. A., Burke, D. S., & Cooley, P. (2008). Modeling targeted layered containment of an influenza pandemic in the United States. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0706849105

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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.