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Multiple Epidemic Wave Model of the COVID-19 Pandemic: Modeling Study

机译:Covid-19大流行病的多种流行性波模型:建模研究

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Background Intervention measures have been implemented around the world to mitigate the spread of the coronavirus disease (COVID-19) pandemic. Understanding the dynamics of the disease spread and the effectiveness of the interventions is essential in predicting its future evolution. Objective The aim of this study is to simulate the effect of different social distancing interventions and investigate whether their timing and stringency can lead to multiple waves (subepidemics), which can provide a better fit to the wavy behavior observed in the infected population curve in the majority of countries. Methods We have designed and run agent-based simulations and a multiple wave model to fit the infected population data for many countries. We have also developed a novel Pandemic Response Index to provide a quantitative and objective way of ranking countries according to their COVID-19 response performance. Results We have analyzed data from 18 countries based on the multiple wave (subepidemics) hypothesis and present the relevant parameters. Multiple waves have been identified and were found to describe the data better. The effectiveness of intervention measures can be inferred by the peak intensities of the waves. Countries imposing fast and stringent interventions exhibit multiple waves with declining peak intensities. This result strongly corroborated with agent-based simulations outcomes. We also provided an estimate of how much lower the number of infections could have been if early and strict intervention measures had been taken to stop the spread at the first wave, as actually happened for a handful of countries. A novel index, the Pandemic Response Index, was constructed, and based on the model’s results, an index value was assigned to each country, quantifying in an objective manner the country’s response to the pandemic. Conclusions Our results support the hypothesis that the COVID-19 pandemic can be successfully modeled as a series of epidemic waves (subepidemics) and that it is possible to infer to what extent the imposition of early intervention measures can slow the spread of the disease.
机译:背景干预措施已经在世界各地实施,以减轻冠状病毒疾病(Covid-19)大流行的传播。了解疾病的动态传播和干预措施的有效性对于预测其未来演变至关重要。目的这项研究的目的是模拟不同的社会偏移干预的效果,并调查他们的时序和严格性是否可以导致多波(潜水症),这可以提供更好地适应在感染的人口曲线中观察到的波浪行为大多数国家。方法我们设计了基于代理的模拟和多个波模型,以适应许多国家的受感染的人口数据。我们还开发了一种新的大流行反应指数,根据他们的Covid-19答复绩效提供排名国家的定量和客观方式。结果我们根据多波(潜水症)假设的18个国家分析了数据,并提出了相关参数。已经识别了多个波,并被发现更好地描述数据。波浪的峰值强度可以推断干预措施的有效性。强加快速和严格的干预的国家展现了多波峰,峰值强度下降。这一结果与基于代理的模拟结果强烈证实。我们还提供了估计,感染的数量较低,如果已经采取了早期和严格的干预措施,以阻止第一波的蔓延,正如少数各国所发生的那样。建立了一个新颖的指数,大流行反应指数,并根据模型的结果,指数值分配给每个国家,以客观方式量化该国对大流行的反应。结论我们的结果支持Covid-19流行病的假设可以成功地建模为一系列流行性波(潜水症),并且可以推断出早期干预措施的施加如何减缓疾病的传播。

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