Alexei Gvishiani, A. Odintsova, E. Rovenskaya, Grigory Boyarshinov, I. Belov, M. Dobrovolsky
{"title":"2019冠状病毒病大流行课程2020-2022:用数理统计和离散数学分析方法进行描述","authors":"Alexei Gvishiani, A. Odintsova, E. Rovenskaya, Grigory Boyarshinov, I. Belov, M. Dobrovolsky","doi":"10.2205/2023es000839","DOIUrl":null,"url":null,"abstract":"The paper describes the course of the COVID-19 pandemic using a combination of mathematical statistics and discrete mathematical analysis (DMA) methods. The method of regression derivatives and FCARS algorithm as components of DMA will be for the first time tested outside of geophysics problems. The algorithm is applied to time series of the number of new cases of COVID-19 infections per day for some regions of Russia and the Republic of Austria. This allowed to assess the nature and anomalies of pandemic spread as well as restrictive measures and decisions taken in terms of the administration of countries and territories. It was shown that these methods can be used to identify time intervals of change in the nature of the incidence rate and areas with the most severe course of the epidemic. This made it possible to identify the most significant restrictive measures that allowed to reduce the growth of the disease.","PeriodicalId":44680,"journal":{"name":"Russian Journal of Earth Sciences","volume":"4 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"COVID-19 pandemic course 2020-2022: description by methods of mathematical statistics and discrete mathematical analysis\",\"authors\":\"Alexei Gvishiani, A. Odintsova, E. Rovenskaya, Grigory Boyarshinov, I. Belov, M. Dobrovolsky\",\"doi\":\"10.2205/2023es000839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes the course of the COVID-19 pandemic using a combination of mathematical statistics and discrete mathematical analysis (DMA) methods. The method of regression derivatives and FCARS algorithm as components of DMA will be for the first time tested outside of geophysics problems. The algorithm is applied to time series of the number of new cases of COVID-19 infections per day for some regions of Russia and the Republic of Austria. This allowed to assess the nature and anomalies of pandemic spread as well as restrictive measures and decisions taken in terms of the administration of countries and territories. It was shown that these methods can be used to identify time intervals of change in the nature of the incidence rate and areas with the most severe course of the epidemic. This made it possible to identify the most significant restrictive measures that allowed to reduce the growth of the disease.\",\"PeriodicalId\":44680,\"journal\":{\"name\":\"Russian Journal of Earth Sciences\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Journal of Earth Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2205/2023es000839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Earth Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2205/2023es000839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
COVID-19 pandemic course 2020-2022: description by methods of mathematical statistics and discrete mathematical analysis
The paper describes the course of the COVID-19 pandemic using a combination of mathematical statistics and discrete mathematical analysis (DMA) methods. The method of regression derivatives and FCARS algorithm as components of DMA will be for the first time tested outside of geophysics problems. The algorithm is applied to time series of the number of new cases of COVID-19 infections per day for some regions of Russia and the Republic of Austria. This allowed to assess the nature and anomalies of pandemic spread as well as restrictive measures and decisions taken in terms of the administration of countries and territories. It was shown that these methods can be used to identify time intervals of change in the nature of the incidence rate and areas with the most severe course of the epidemic. This made it possible to identify the most significant restrictive measures that allowed to reduce the growth of the disease.