Snowy Owl
Retired in 2010, In Memoriam
Proceedings of the National Academy of Sciences of the United States of America
Medical Sciences
Mitigation strategies for pandemic influenza in the United States
( antiviral agents | infectious diseases | simulation modeling | social network dynamics | vaccines )
Timothy C. Germann *{dagger}, Kai Kadau *, Ira M. Longini Jr. {ddagger}, and Catherine A. Macken *
*Los Alamos National Laboratory, Los Alamos, NM 87545; and {ddagger}Program of Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center and Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Seattle, WA 98109
Communicated by G. Balakrish Nair, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh, February 16, 2006 (received for review January 10, 2006)
Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R0 (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R0 < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R0, provided adequate contact tracing and distribution capacities exist. For higher R0, we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
Author contributions: T.C.G., K.K., I.M.L., and C.A.M. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper.
Conflict of interest statement: No conflicts declared.
http://www.pnas.org/cgi/content/abstract/0601266103v1
Medical Sciences
Mitigation strategies for pandemic influenza in the United States
( antiviral agents | infectious diseases | simulation modeling | social network dynamics | vaccines )
Timothy C. Germann *{dagger}, Kai Kadau *, Ira M. Longini Jr. {ddagger}, and Catherine A. Macken *
*Los Alamos National Laboratory, Los Alamos, NM 87545; and {ddagger}Program of Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center and Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Seattle, WA 98109
Communicated by G. Balakrish Nair, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh, February 16, 2006 (received for review January 10, 2006)
Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R0 (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R0 < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R0, provided adequate contact tracing and distribution capacities exist. For higher R0, we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
Author contributions: T.C.G., K.K., I.M.L., and C.A.M. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper.
Conflict of interest statement: No conflicts declared.
http://www.pnas.org/cgi/content/abstract/0601266103v1