ارائه مدلی برای شبیه‌سازی انتشار ویروس کووید-19 بر اساس زنجیره مارکوف گسسته زمان

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی کامپیوتر، دانشکده مهندسی برق و کامپیوتر، دانشگاه کاشان، کاشان، ایران

چکیده

شیوع بیماری‌های واگیردار در جامعه به عوامل مختلفی بستگی دارد که از آن جمله می‌توان به شدت واگیری بیماری، میزان رعایت پروتکل‌های بهداشتی و ارتباطی، سرعت واکسیناسیون، ضریب تاثیر و مدت اثربخشی آن بر ایمن‌سازی، میزان تاثیر پروتکل‌های درمانی و میانگین مدت درمان اشاره نمود. وجود مدلی که بتوان به وسیله آن رفتار بیماری را برحسب پارامترهای مختلف پیش‌بینی نمود، می‌تواند به مدیران جامعه برای مقابله با این نوع بیماری‌ها کمک نماید. در مطالعاتی که تاکنون در این زمینه انجام شده، تاثیر برخی عوامل مانند رعایت دستورالعمل‌های بهداشتی، دوره پنهان بیماری و ایمنی پس از بیماری همزمان با عوامل اصلی مانند ضریب انتشار و نرخ واکسیناسیون به طور کامل در نظر گرفته نشده است. در این مقاله مدلی جدید و جامع مبتنی بر نظریه مارکوف برای پیش‌بینی رفتار بیماری کووید-۱۹ ارائه می‌شود. این مدل می‌تواند با دریافت پارامترهای داده شده رفتار بیماری را در شرایط مختلف تقلید نماید. شبیه‌سازی‌های متعدد با مقادیر مختلف پارامترهای ورودی و تشابه آن با رفتار واقعی بیماری کووید-۱۹ نشان‌دهنده صحت عملکرد مدل ارائه شده است.

کلیدواژه‌ها


عنوان مقاله [English]

A simulation model for the propagation of Covid-19 virus based on the discrete-time Markov chain

نویسندگان [English]

  • Amirhosein Yadollahi
  • Hossein Sabaghian-Bidgoli
Department of Computer Engineering, Faculty of Electrical and Computer Engineering, Kashan University, Kashan, Iran
چکیده [English]

The prevalence of infectious diseases in the community depends on various factors, including the severity of the disease, compliance with health and communication protocols, vaccination rate, impact factor and duration of its effectiveness on immunization, and effectiveness of treatment protocols and average duration of treatment. Having a model based on which the behavior of the disease can be predicted according to various parameters, can help community leaders to deal with these types of diseases. In the studies conducted so far in this field, the impact of some factors such as compliance with health guidelines, the latent period of the disease and immunity after the disease at the same time as the main factors such as the prevalence rate and vaccination rate have not been fully considered. In this paper, a new and comprehensive model based on Markov theory is presented for predicting the behavior of the Covid-19 disease. This model can imitate the behavior of the disease in different conditions by receiving the given parameters. Numerous simulations with different values of input parameters and their similarity to the actual behavior of Covid-19 disease show the accuracy of the model.

کلیدواژه‌ها [English]

  • Modeling
  • Markov chain
  • Predicting epidemic behavior
  • Covid-19 virus spread
  • Human communication networks
  • Effectiveness of health communication protocol
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