Stockpiling Ventilators for Influenza Pandemics
, Ozgur M. Araz, David P. Morton, Gregory P. Johnson, Paul Damien, Bruce Clements, and Lauren Ancel Meyers
Author affiliations: The University of Texas at Austin, Austin, Texas, USA (H.-C. Huang, G.P. Johnson, P. Damien, L.A. Meyers); University of Nebraska, Lincoln, Nebraska, USA (O.M. Araz); University of Nebraska Medical Center, Omaha, Nebraska, USA (O.M. Araz); Northwestern University, Evanston, Illinois, USA (D.P. Morton); Department of State Health Services, Austin (B. Clements); Santa Fe Institute, Santa Fe, New Mexico, USA (L.A. Meyers)
Figure 1. Overview of methods for projecting the need to stockpile ventilators for an influenza pandemic, Texas, USA. First, a forecasting model was used to estimate weekly hospitalizations at each site on the basis of historical ILI hospitalization data and CDC ILINet reports. Second, 3 additional factors, along with a spatial correlation coefficient, were used to form a probability distribution for peak-week ventilator demand at each site. Third, an optimization model was solved to determine local and central stockpile allocations and generate trade-off curves between the expected unmet demand and total stockpile and between the probability of unmet demand and total stockpile. CDC, Centers for Disease Control and Prevention; HSR, health service region; ICU, intensive care unit; ILI, influenza-like illness.
Page created: May 30, 2017
Page updated: May 30, 2017
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