Arti M K, Wilinski Antoni
NSUT East Campus (AIACTR), New Delhi, India.
WSB University in Gdansk, Gdansk, Poland.
Stoch Environ Res Risk Assess. 2022;36(9):2495-2501. doi: 10.1007/s00477-021-02119-5. Epub 2021 Nov 26.
We investigate the problem of mathematical modeling of new corona virus (COVID-19) in Poland and tries to predict the upcoming wave. A Gaussian mixture model is proposed to characterize the COVID-19 disease and to predict a new / future wave of COVID-19. This prediction is very much needed to prepare for medical setup and continue with the upcoming program. Specifically, data related to the new confirmed cases of COVID-19 per day are considered, and then we attempt to predict the data and statistical activity. A close match between actual data and analytical data by using the Gaussian mixture model shows that it is a suitable model to present new cases of COVID-19. In addition, it is thought that there are N waves of COVID-19 and that information for each future wave is also present in current and previous waves as well. Using this concept, predictions of a future wave can be made.
我们研究了波兰新型冠状病毒(COVID-19)的数学建模问题,并试图预测即将到来的疫情高峰。提出了一种高斯混合模型来表征COVID-19疾病,并预测新的/未来的COVID-19疫情高峰。为医疗准备工作和后续计划的推进,这种预测非常必要。具体而言,我们考虑了与每日新增COVID-19确诊病例相关的数据,然后尝试预测这些数据和统计活动。通过使用高斯混合模型,实际数据与分析数据之间的紧密匹配表明,它是呈现COVID-19新病例的合适模型。此外,人们认为COVID-19会出现N波疫情,并且每一波未来疫情的信息也存在于当前和之前的疫情中。利用这一概念,可以对未来的疫情高峰进行预测。