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<p>Cardiovascular disease (CVD) is a leading contributor to rising mortality rates in the USA. This issue is exacerbated in areas prone to natural disasters, where a portion of the population seeks refuge in shelters with limited access to essential treatments. The unavailability of necessary medications in these situations significantly increases the mortality rate among individuals with CVD. Deploying mobile pharmacies has been identified as an effective intervention to ensure easy access to medications for CVD patients displaced during disasters. In this study, a mixed-integer programming model has been developed to optimize the allocation of mobile pharmacies. This model demonstrates a maximum demand coverage of 78% in affected areas or shelters by efficiently distributing the necessary quantity of mobile pharmacies. The study also includes a cost-effectiveness analysis, enabling policymakers to determine the maximum demand coverage percentage with the limited resources required to optimize disaster response efforts. By providing a robust framework for resource allocation, this model supports informed decision-making and improves disaster preparedness and response, ultimately reducing the health impacts on vulnerable populations.</p>

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Mixed Integer Programming Model for Planning Interventions to Care for Cardiovascular Patients After Natural Disasters

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月29日

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  • Faria Farzana,
  • Eduardo Perez

摘要

Cardiovascular disease (CVD) is a leading contributor to rising mortality rates in the USA. This issue is exacerbated in areas prone to natural disasters, where a portion of the population seeks refuge in shelters with limited access to essential treatments. The unavailability of necessary medications in these situations significantly increases the mortality rate among individuals with CVD. Deploying mobile pharmacies has been identified as an effective intervention to ensure easy access to medications for CVD patients displaced during disasters. In this study, a mixed-integer programming model has been developed to optimize the allocation of mobile pharmacies. This model demonstrates a maximum demand coverage of 78% in affected areas or shelters by efficiently distributing the necessary quantity of mobile pharmacies. The study also includes a cost-effectiveness analysis, enabling policymakers to determine the maximum demand coverage percentage with the limited resources required to optimize disaster response efforts. By providing a robust framework for resource allocation, this model supports informed decision-making and improves disaster preparedness and response, ultimately reducing the health impacts on vulnerable populations.