Responding to simulated pandemic influenza in San Antonio, Texas

George Miller, Stephen Randolph, Jan E. Patterson

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


OBJECTIVE. To describe the results of a simulation study of the spread of pandemic influenza, the effects of public health measures on the simulated pandemic, and the resultant adequacy of the surge capacity of the hospital infrastructure and to investigate the adequacy of key elements of the national pandemic influenza plan to reduce the overall attack rate so that surge capacity would not be overwhelmed. DESIGN. We used 2 discrete-event simulation models: the first model simulates the contact and disease transmission process, as affected by public health interventions, to produce a stream of arriving patients, and the second model simulates the diagnosis and treatment process and determines patient outcomes. SETTING. Hypothetical scenarios were based on the response plans, infrastructure, and demographic data of the population of San Antonio, Texas. RESULTS. Use of a mix of strategies, including social distancing, antiviral medications, and targeted vaccination, may limit the overall attack rate so that demand for care would not exceed the capacity of the infrastructure. Additional simulations to assess social distancing as a sole mitigation strategy suggest that a reduction of infectious community contacts to half of normal levels would have to occur within approximately 7 days. CONCLUSIONS. Under ideal conditions, the mix of strategies may limit demand, which can then be met by community surge capacity. Given inadequate supplies of vaccines and antiviral medications, aggressive social distancing alone might allow for the control of a local epidemic without reliance on outside support.

Original languageEnglish (US)
Pages (from-to)320-326
Number of pages7
JournalInfection Control and Hospital Epidemiology
Issue number4
StatePublished - Apr 2008

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases
  • Epidemiology


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