The Role of Vaccination in the Control of SARS
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Department of Mathematics, Harvey Mudd College, 340 E. Foothill Blvd. Claremont, CA 91711
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Mathematics department, Clarion University of Pennsylvania, Clarion, Pennsylvania 16214
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Theoretical Division (MS B284), Los Alamos National Laboratory, Los Alamos, NM 87545
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BSCB, Cornell University, Ithaca, NY 14853
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College of Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332
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Department of Mathematics & Statistics, Arizona State University, Tempe, AZ 85287-1804
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Received:
01 June 2005
Accepted:
29 June 2018
Published:
01 October 2005
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MSC :
92D30.
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We assess pre-outbreak and during-outbreak vaccination as control strategies for SARS epidemics using a mathematical model that includes susceptible, latent (traced and untraced), infectious, isolated and recovered individuals. Scenarios focusing on policies that include contact tracing and levels of self-isolation among untraced infected individuals are explored. Bounds on the proportion of pre-outbreak successfully vaccinated individuals are provided using the the basic reproductive number. Uncertainty and sensitivity analyses on the reproductive number are carried out. The final epidemic size under different vaccination scenarios is computed.
Citation: Julijana Gjorgjieva, Kelly Smith, Gerardo Chowell, Fabio Sánchez, Jessica Snyder, Carlos Castillo-Chavez. The Role of Vaccination in the Control of SARS[J]. Mathematical Biosciences and Engineering, 2005, 2(4): 753-769. doi: 10.3934/mbe.2005.2.753
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Abstract
We assess pre-outbreak and during-outbreak vaccination as control strategies for SARS epidemics using a mathematical model that includes susceptible, latent (traced and untraced), infectious, isolated and recovered individuals. Scenarios focusing on policies that include contact tracing and levels of self-isolation among untraced infected individuals are explored. Bounds on the proportion of pre-outbreak successfully vaccinated individuals are provided using the the basic reproductive number. Uncertainty and sensitivity analyses on the reproductive number are carried out. The final epidemic size under different vaccination scenarios is computed.
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