SIR模型在新冠肺炎疫情研究中的应用分析——以巴基斯坦为例

Ijaz Yusuf, Kishmala Ijaz, Hassan Qudrat Ullah
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摘要

本研究旨在利用系统动态模型检验COVID-19的指数传播率。新冠肺炎疫情于2020年2月26日在巴基斯坦首次得到证实。地方机关和执法部门采取了初步预防措施,将新冠病毒限制在特定地区,但都是徒劳的。大量的人感染了这种病毒,增加了全国的死亡率。受感染的人数令人震惊,人们认为有必要开发一个模型来计算现有的繁殖数量和传播率,并在未来几天强调其不同的值。必须探索对人民友好的措施和基于政府的政策来防治这一致命疾病。本文旨在利用仿真软件STELLA的系统动态框架建立流行病模型。此外,本研究的目的是通过系统动态模型进行实验,以复制传染病的发展过程,并探索以人为本和以政府为本的多种措施组合,以减少COVID-19大流行的传播。这些遏制措施有两种类型;直接影响COVID-19缓解情况的再现数量和感染增长率的以人为本和以政府为本的措施。公众和政府的共同努力可以抗击这一全球流行病。再现数/复发数减少和感染增长率是判断和评价防控措施有效性的关键指标。因此,这项研究指出,公共和政府导向的措施更全面地结合起来,对降低COVID-19不断上升的感染率至关重要。对模拟结果进行跟踪,以表格形式和图形形式复制四种密封措施组合的现实环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing the Application of SIR Model to Study the Outbreak of COVID-19: A Case Study in Pakistan
The current study aims to examine the exponential rate of the spread of COVID-19 by employing a system dynamic model. The outbreak of COVID-19 was first evidenced on Feb 26, 2020 in Pakistan. The local bodies and law enforcing agencies took the initial preventive measures to restrict COVID-19 to a particular locality but all in vain. A large number of people were infected by this virus which increased the death rate countrywide. The numbers of infected people were alarming and a need was felt to develop the model to calculate the existing reproduction number and transmission rate and highlight its varied values in the coming days. People-friendly measures and government-based policies must be explored to fight against this deadly disease. This paper aims to develop an epidemic model using the system dynamic framework of simulation software STELLA. Additionally, the current study’s purpose is to experiment with the system dynamic model to replicate the progression of the communicable disease and probe multiple combinations of people-based and government-based measures to reduce the spread of the COVID-19 pandemic. These containment measures are of two types; people-based measures and government-based measures which directly affect the reproduction number and infection growth rate of the mitigating circumstances due to COVID-19. Combined efforts of the public and government can combat this global pandemic. The reduced number of reproduction number/recurring cases and infection growth rate are the key metrics to judge and evaluate the effectiveness of containment/ control measures. Therefore, this research points to a more holistic combination of public and government-oriented measures that play a vital role in reducing the increasing infection rate of COVID-19. Simulation results were traced to replicate the real-life settings against four combinations of containmentmeasures in tabular form and graphical form.
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