论文标题
模拟延迟在与基于混合代理和基于方程的模型的Covid-19引起的中风治疗中的延迟
Simulating Delay in Seeking Treatment for Stroke due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model
论文作者
论文摘要
Covid-19对全球医疗保健系统造成了巨大压力。同时，人口内部对这种压力的关注以及被感染的机会可能降低了人们为其他健康事件寻求医疗治疗的可能性。中风是一种医疗紧急情况，迅速治疗可以对患者预后产生很大的影响。了解对Covid-19的大流行的关注可能会影响中风后寻求治疗的时间延迟，这对于理解长期成本的影响以及如何在另一种大流行情景中瞄准个人的时间很重要，以提醒他们立即寻求治疗的重要性。我们提出了一个基于混合代理和方程式的模型，以模拟由于对COVID-19的担忧而引起的中风治疗的延迟，并表明行为的少量变化也会影响为人群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支持他们的未来医疗保健费用。我们发现，与一个大峰的情况相比，引入控制措施并具有大流行的多个较小峰会导致寻求治疗的延迟。
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.
