基于代理和方程的混合模型模拟COVID-19引起的脑卒中患者就诊延迟
Simulating Delay in Seeking Treatment for Stroke due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model
摘要：
COVID-19给全球医疗系统造成了巨大压力。与此同时，人们对这种毒株和感染机会的担忧可能会减少人们因其他健康事件寻求治疗的可能性。中风是一种医疗紧急情况，迅速治疗可以使患者的结果有很大的不同。了解对COVID-19大流行的担忧如何影响中风后寻求治疗的时间延迟，对于了解长期成本影响以及如何在另一种大流行情况下针对个人提醒他们立即寻求治疗的重要性非常重要。我们提出了一个基于代理和基于方程的混合模型，以模拟由于对COVID-19的担忧而导致的寻求中风治疗的延迟，并表明即使是微小的行为变化也会影响人口寻求治疗的平均延迟。这种延迟可能会影响中风患者的结果和未来支持他们的医疗费用。我们发现，引入控制措施，并有多个较小的流行病的高峰导致更少的延误寻求治疗相比，一个大的高峰的情况。
英文摘要：
COVID-19 has caused tremendous strain on healthcare systems worldwide. At the same time, concern within the population over this strain and the chances of becoming infected has potentially reduced the likelihood of people seeking medical treatment for other health events. Stroke is a medical emergency and swift treatment can make a large difference in patient outcomes. Understanding how concern over the COVID-19 pandemic might impact the time delay in seeking treatment after a stroke can be important in understanding both the long term cost implications and how to target individuals during another pandemic scenario to remind them of the importance of seeking treatment immediately. We present a hybrid agent-based and equation-based model to simulate the delay in seeking treatment for stroke due to concerns over COVID-19 and show that even small changes in behaviour impact the average delay in seeking treatment for the population. This delay could potentially impact the outcomes for stroke patients and future healthcare costs to support them. We find that introducing control measures and having multiple smaller peaks of the pandemic results in less delay in seeking treatment compared to a scenario with one large peak.
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