Dynamic redistribution of mitigation resources during influenza pandemics

Abstract

The Institute of Medicine (IOM) has pointed out that the existing pandemic mitigation models lack the dynamic decision support capability. In this paper, we present a simulation optimization model to generate dynamic strategies for distribution of limited mitigation resources, such as vaccines and antivirals, over a network of regional outbreaks. The model has the capability to redistribute the resources remaining from previous allocations in response to changes in the pandemic progress. The model strives to minimize the impact of ongoing outbreaks and the expected impact of potential outbreaks, considering measures of morbidity, mortality, and social distancing, translated into the societal and economic costs of lost productivity and medical services. The model is implemented on a simulated H5N1 outbreak involving four counties in the state of Florida, U.S. with over four million inhabitants. The performance of our strategy is compared to that of a myopic distribution strategy. Sensitivity analysis is performed to assess the impact of variability of some critical factors on policy performance. The methodology is intended to support public health policy on effective distribution of limited mitigation resources.