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OR Spectrum

, Volume 33, Issue 3, pp 751–786 | Cite as

A predictive decision-aid methodology for dynamic mitigation of influenza pandemics

  • Andrés Uribe-Sánchez
  • Alex Savachkin
  • Alfredo Santana
  • Diana Prieto-Santa
  • Tapas K. Das
Regular Article

Abstract

In a recent report, the Institute of Medicine has stressed the need for dynamic mitigation strategies for pandemic influenza. In response to the need, we have developed a simulation-based optimization methodology for generating dynamic predictive mitigation strategies for pandemic outbreaks affecting several regions. Our methodology can accommodate varying virus and population dynamics. It progressively allocates a limited budget to procure vaccines and antivirals, capacities for their administration, and resources required to enforce social distancing. The methodology uses measures of morbidity, mortality, and social distancing, which are translated into the costs of lost productivity and medical services. The simulation model was calibrated using historic pandemic data. We illustrate the use of our methodology on a mock outbreak involving over four million people residing in four major population centers in Florida, USA. A sensitivity analysis is presented to estimate the impact of changes in the budget availability and variability of some of the critical parameters of mitigation strategies. The methodology is intended to assist public health policy makers.

Keywords

Pandemic influenza Mitigation Dynamic Vaccination Antiviral Social distancing 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Andrés Uribe-Sánchez
    • 1
  • Alex Savachkin
    • 1
  • Alfredo Santana
    • 1
  • Diana Prieto-Santa
    • 1
  • Tapas K. Das
    • 1
  1. 1.Department of Industrial and Management Systems EngineeringUniversity of South FloridaTampaUSA

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