俄罗斯联邦下诺夫哥罗德地区 COVID-19 六次流行潮的多中心代理模型

A. V. Hilov, N. Saperkin, O. Kovalishena, N. A. Sadykova, V. V. Perekatova, N. V. Perekhozheva, D. Kurakina, M. Kirillin
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摘要

相关性。为了研究 COVID-19 的流行特征并及时采取有效措施,需要建立能够预测各种限制性措施或疾病本身特征对 COVID-19 传播动态影响的模型。采用基于代理的模型很有吸引力,因为这些模型考虑到了不同的人口特征(如年龄分布和社会活动)、限制性措施、实验室检测等,以及在传统的 SIR 类动态模型修改中通常会忽略的随机因素。目标改进之前提出的基于代理的模型[23,24],以模拟 COVID-19 在俄罗斯联邦各地区的传播。在现阶段,考虑到限制性措施和人口接种疫苗的情况,对 COVID-19 在下诺夫哥罗德地区作为一个整体及其各个城市的六波传播进行了建模。材料与方法。在本文中,我们扩展了最近提出的基于代理的模型,用于对 COVID-19 的传播进行基于蒙特卡罗的数值模拟,并考虑了检测和疫苗接种策略。分析在 MATLAB/ GNU Octave 中进行。结果所开发的多中心模型可以更准确地模拟一个区域内的流行动态,当零号病人通常到达一个区域中心后,由于钟摆迁移,分布链会捕捉到该区域的外围。此外,我们还展示了所开发模型在俄罗斯联邦下诺夫哥罗德地区疫情传播分析中的应用。模拟的每日新发现病例和 COVID-19 相关死亡的动态与整个地区和不同周边城市的官方统计数据非常吻合。结论利用开发的模型得出的结果表明,COVID-19 病例的实际数量可能是报告病例数量的 1.5-3.0 倍。开发的模型还考虑了疫苗接种的影响。结果表明,在模型参数不变但不接种疫苗的情况下,流行病的第三波和第四波将合二为一,其特点是发病率大幅上升,出现自然个体免疫,不再出现进一步的大流行。然而,死亡人数将比实际死亡人数高出约 9-10 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multicentral Agent-Based Model of Six Epidemic Waves of COVID-19 in the Nizhny Novgorod Region of Russian Federation
Relevance. To investigate the characteristics of the COVID-19 pandemic and introduce timely and effective measures, there is a need for models that can predict the impact of various restrictive actions or characteristics of disease itself on COVID-19 spread dynamics. Employing agent-based models can be attractive because they take into consideration different population characteristics (e.g., age distribution and social activity) and restrictive measures, laboratory testing, etc., as well as random factors that are usually omitted in traditional modifications of the SIR-like dynamic models. Aim. Improvement of the previously proposed agent-based model [23,24] for modeling the spread of COVID-19 in various regions of the Russian Federation. At this stage, six waves of the spread of COVID-19 have been modeled in the Nizhny Novgorod region as a whole region, as well as in its individual cities, taking into account restrictive measures and vaccination of the population. Materials and Methods. In this paper we extend a recently proposed agent-based model for Monte Carlo-based numerical simulation of the spread of COVID-19 with consideration of testing and vaccination strategies. Analysis is performed in MATLAB/ GNU Octave. Results. Developed multicentral model allows for more accurate simulation of the epidemic dynamics within one region, when a patient zero usually arrives at a regional center, after which the distribution chains capture the periphery of the region due to pendulum migration. Furthermore, we demonstrate the application of the developed model to analyze the epidemic spread in the Nizhny Novgorod region of Russian Federation. The simulated dynamics of the daily newly detected cases and COVID-19-related deaths was in good agreement with the official statistical data both for the region as whole and different periphery cities. Conclusions. The results obtained with developed model suggest that the actual number of COVID-19 cases might be 1.5–3.0 times higher than the number of reported cases. The developed model also took into account the effect of vaccination. It is shown that with the same modeling parameters, but without vaccination, the third and fourth waves of the epidemic would be united into one characterized by a huge rise in the morbidity rates and the occurrence of natural individual immunity with the absence of further pandemic waves. Nonetheless, the number of deaths would exceed the real one by about 9–10 times.
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