A. Angelopoulou, Sonipriya Paul
{"title":"Discrete event simulation of a drive-through COVID-19 mass vaccination model: senior population prioritization strategies","authors":"A. Angelopoulou, Sonipriya Paul","doi":"10.46354/i3m.2021.emss.036","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic has disrupted the normal operations of countries around the world, which applied different containment and mitigation policies, such as mask-wearing, social distancing, quarantine, and lockdowns, to limit the spread of the virus. More recent mitigation efforts include vaccination strategies, since various vaccines have been authorized for emergency use for the prevention of COVID-19. In fact, vaccination is one of the best proactive mitigation strategies against the virus spread. Mass vaccination strategies have been undertaken by multiple research and development teams in the past when the public needed to be vaccinated on a large scale due to a pandemic, such as the seasonal flu or H1N1. Drive through vaccination, in particular, is more convenient and safer than walk-in vaccinations in clinics due the nature of the contagious virus. In this paper, we present the implementation of a discrete event simulation model of a drive through clinic for mass vaccinations of patients, while prioritizing the senior population. The simulation output is examined in terms of average waiting time in the queue to get vaccinated, number of patients getting vaccinated per week, and utilization of the medical resources. The results are expected to provide insights into the allocation of medical resources across lanes and prioritization strategies for the senior population to achieve higher vaccination rates, while reducing the waiting time in queue. © 2021 The Authors.","PeriodicalId":322169,"journal":{"name":"Proceedings of the 33rd European Modeling & Simulation Symposium","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 33rd European Modeling & Simulation Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46354/i3m.2021.emss.036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
COVID-19免下车大规模疫苗接种模型的离散事件模拟:老年人群优先级策略
新冠肺炎大流行扰乱了世界各国的正常运作,各国采取了不同的防控政策,如戴口罩、保持社交距离、隔离、封锁等,以限制病毒的传播。最近的缓解努力包括疫苗接种战略,因为已授权紧急使用各种疫苗来预防COVID-19。事实上,疫苗接种是预防病毒传播的最佳主动缓解策略之一。过去,当季节性流感或H1N1等大流行导致公众需要大规模接种疫苗时,多个研究和开发团队采取了大规模疫苗接种战略。由于这种传染性病毒的性质,开车接种疫苗比在诊所接种疫苗更方便、更安全。在本文中,我们提出了一个离散事件模拟模型的实现,该模型通过诊所为患者大规模接种疫苗,同时优先考虑老年人。根据排队接种疫苗的平均等待时间、每周接种疫苗的患者数量和医疗资源的利用率来检查模拟输出。该结果有望为老年人提供跨车道医疗资源分配和优先级策略的见解,以实现更高的疫苗接种率,同时减少排队等待时间。©2021作者。
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