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Responding to simulated pandemic influenza in San Antonio, Texas.
Infect Control Hosp Epidemiol. 2008 Apr; 29(4):320-6.IC

Abstract

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.

Authors+Show Affiliations

Altarum Institute, P.O. Box 134001, Ann Arbor, MI 48113-4001, USA. george.miller@altarum.orgNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, U.S. Gov't, P.H.S.

Language

eng

PubMed ID

18462144

Citation

Miller, George, et al. "Responding to Simulated Pandemic Influenza in San Antonio, Texas." Infection Control and Hospital Epidemiology, vol. 29, no. 4, 2008, pp. 320-6.
Miller G, Randolph S, Patterson JE. Responding to simulated pandemic influenza in San Antonio, Texas. Infect Control Hosp Epidemiol. 2008;29(4):320-6.
Miller, G., Randolph, S., & Patterson, J. E. (2008). Responding to simulated pandemic influenza in San Antonio, Texas. Infection Control and Hospital Epidemiology, 29(4), 320-6. https://doi.org/10.1086/529212
Miller G, Randolph S, Patterson JE. Responding to Simulated Pandemic Influenza in San Antonio, Texas. Infect Control Hosp Epidemiol. 2008;29(4):320-6. PubMed PMID: 18462144.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Responding to simulated pandemic influenza in San Antonio, Texas. AU - Miller,George, AU - Randolph,Stephen, AU - Patterson,Jan E, PY - 2008/5/9/pubmed PY - 2008/11/14/medline PY - 2008/5/9/entrez SP - 320 EP - 6 JF - Infection control and hospital epidemiology JO - Infect Control Hosp Epidemiol VL - 29 IS - 4 N2 - 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. SN - 0899-823X UR - https://www.unboundmedicine.com/medline/citation/18462144/Responding_to_simulated_pandemic_influenza_in_San_Antonio_Texas_ L2 - http://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=linkout&SEARCH=18462144.ui DB - PRIME DP - Unbound Medicine ER -