{"title":"New Opportunities Model for Monitoring, Analyzing and Forecasting the Official Statistics on Coronavirus Disease Pandemic","authors":"S. Abramov, S. Travin, G. Duca","doi":"10.59277/romjist.2023.1.04","DOIUrl":null,"url":null,"abstract":"At the beginning of 2020, it became obvious that the coronavirus disease 2019 (COVID-19) pandemic will have a fairly significant scale and duration. There was an unmet need for the analysis and forecast of the development of events. The forecast was needed to make the managerial decisions in terms of knowledge on the dynamics of the pandemic, considering and analyzing the incoming official statistics about the pandemic, modeling and predicting the behavior of this statistics. Due to the objective and subjective factors, the available statistics is far from the unknown true data regarding the pandemic. Therefore, strictly speaking, it was necessary to model and predict not the dynamics of the pandemic, but the dynamics of the official (i.e. government) statistics on the pandemic. This paper proposes a new model, referred to as the new opportunities model, to monitor, analyze and forecast the government statistics on COVID-19 pandemic. A modeling approach is offered in this regard. The modeling approach is important as it answers simple questions on what awaits us in the near future, which is the current phase of the pandemic and when all this will be over. The new opportunities model is applied to three different countries in terms of area, economy and population, namely Russia, Romania and Moldova, plus the Campania region in Italy, and proves to be efficient over other similar models including the classical Susceptible-Infected (SI) model.","PeriodicalId":54448,"journal":{"name":"Romanian Journal of Information Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Romanian Journal of Information Science and Technology","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.59277/romjist.2023.1.04","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1
Abstract
At the beginning of 2020, it became obvious that the coronavirus disease 2019 (COVID-19) pandemic will have a fairly significant scale and duration. There was an unmet need for the analysis and forecast of the development of events. The forecast was needed to make the managerial decisions in terms of knowledge on the dynamics of the pandemic, considering and analyzing the incoming official statistics about the pandemic, modeling and predicting the behavior of this statistics. Due to the objective and subjective factors, the available statistics is far from the unknown true data regarding the pandemic. Therefore, strictly speaking, it was necessary to model and predict not the dynamics of the pandemic, but the dynamics of the official (i.e. government) statistics on the pandemic. This paper proposes a new model, referred to as the new opportunities model, to monitor, analyze and forecast the government statistics on COVID-19 pandemic. A modeling approach is offered in this regard. The modeling approach is important as it answers simple questions on what awaits us in the near future, which is the current phase of the pandemic and when all this will be over. The new opportunities model is applied to three different countries in terms of area, economy and population, namely Russia, Romania and Moldova, plus the Campania region in Italy, and proves to be efficient over other similar models including the classical Susceptible-Infected (SI) model.
期刊介绍:
The primary objective of this journal is the publication of original results of research in information science and technology. There is no restriction on the addressed topics, the only acceptance criterion being the originality and quality of the articles, proved by independent reviewers. Contributions to recently emerging areas are encouraged.
Romanian Journal of Information Science and Technology (a publication of the Romanian Academy) is indexed and abstracted in the following Thomson Reuters products and information services:
• Science Citation Index Expanded (also known as SciSearch®),
• Journal Citation Reports/Science Edition.