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Dynamic redistribution of mitigation resources during influenza pandemics

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  • Savachkin, Alex
  • Uribe, Andrés

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.

Suggested Citation

  • Savachkin, Alex & Uribe, Andrés, 2012. "Dynamic redistribution of mitigation resources during influenza pandemics," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 33-45.
    • Handle: RePEc:eee:soceps:v:46:y:2012:i:1:p:33-45
    DOI: 10.1016/j.seps.2011.05.001
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    Cited by:

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    2. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    3. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    4. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    5. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    6. Manupati, Vijaya Kumar & Schoenherr, Tobias & Subramanian, Nachiappan & Ramkumar, M. & Soni, Bhanushree & Panigrahi, Suraj, 2021. "A multi-echelon dynamic cold chain for managing vaccine distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    7. Gong, Jiangyue & Gujjula, Krishna Reddy & Ntaimo, Lewis, 2023. "An integrated chance constraints approach for optimal vaccination strategies under uncertainty for COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

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