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<p>Pandemics pose significant challenges, particularly in the early stages when vertical resupply chains are overwhelmed. To mitigate the impact of medical resource shortages, we develop a multi-period optimization model incorporating lateral transshipment and hospital admission to minimize the total number of infected individuals by strategically allocating regional resources in the face of complex dynamics, including endogenous hospital admission rates and pandemic spread. To capture the temporal-spatial nature of pandemics, we extend the Susceptible-Exposed-Infected-Hospitalized-Recovered (SEIHR) model by accounting for population migration. Additionally, we derive threshold-type structures for optimal resource transfers, considering factors such as pandemic dynamics, patient length of stay, and budget constraints. We also demonstrate the effectiveness of our models via numerical experiments. Our research identifies three main findings: 1) Pooling medical resources effectively reduces infections and alleviates shortages in outbreak areas. This strategy is particularly beneficial during pandemics due to self-reinforcing infection dynamics and surging demand. 2) Regions adjacent to the epicenter should exercise caution in contributing resources to avoid exacerbating infections through population migration. 3) While effective in localized outbreaks, widespread resource scarcity can limit the viability of pooling strategies, potentially leading to increased infections and fluctuating resource levels in transferring regions.</p>

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Joint decisions for hospital admissions and horizontal medical resource transfer against capacity shortage in the early stage of pandemics

  • 期刊论文

  • 发表日期：

    2025年11月28日

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  • Huiping Sun,
  • Jianghua Zhang

摘要

Pandemics pose significant challenges, particularly in the early stages when vertical resupply chains are overwhelmed. To mitigate the impact of medical resource shortages, we develop a multi-period optimization model incorporating lateral transshipment and hospital admission to minimize the total number of infected individuals by strategically allocating regional resources in the face of complex dynamics, including endogenous hospital admission rates and pandemic spread. To capture the temporal-spatial nature of pandemics, we extend the Susceptible-Exposed-Infected-Hospitalized-Recovered (SEIHR) model by accounting for population migration. Additionally, we derive threshold-type structures for optimal resource transfers, considering factors such as pandemic dynamics, patient length of stay, and budget constraints. We also demonstrate the effectiveness of our models via numerical experiments. Our research identifies three main findings: 1) Pooling medical resources effectively reduces infections and alleviates shortages in outbreak areas. This strategy is particularly beneficial during pandemics due to self-reinforcing infection dynamics and surging demand. 2) Regions adjacent to the epicenter should exercise caution in contributing resources to avoid exacerbating infections through population migration. 3) While effective in localized outbreaks, widespread resource scarcity can limit the viability of pooling strategies, potentially leading to increased infections and fluctuating resource levels in transferring regions.