2019冠状病毒病在全球传播的累积病例数预测模型

Q3 Engineering

Engineering and Applied Science Research Pub Date : 2021-01-01 DOI:10.14456/easr.2021.46

R. Sunthornwat, Y. Areepong

{"title":"2019冠状病毒病在全球传播的累积病例数预测模型","authors":"R. Sunthornwat, Y. Areepong","doi":"10.14456/easr.2021.46","DOIUrl":null,"url":null,"abstract":"The coronavirus disease outbreak in 2019 (COVID-19) has caused major economic and healthcare problems worldwide. At this time, the worldwide outbreak has passed its peak, while the greatest number of cases has been in the USA, Brazil, and India. Measures and policies for controlling the outbreak have been developed by authorities to protect the population of each country, and forecasting the number of infectious people is an important factor for developing them. This research was conducted to identify a suitable forecasting model for estimating the cumulative daily number of infectious people worldwide. Sample countries with severe outbreaks were selected from each continent. Herein, forecasting models based on logistic, Richards, and Gompertz growth curves are derived and their suitability for forecasting the COVID-19 rates in each sample country and worldwide are analyzed. Moreover, estimating the growth curve parameters is based on the least-squares method. The results show that the Gompert growth curve is the most suitable for estimating the cumulative number of infectious people worldwide. © 2021, Paulus Editora. All rights reserved.","PeriodicalId":37310,"journal":{"name":"Engineering and Applied Science Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Predictive models for the number of cumulative cases for spreading coronavirus disease 2019 in the world\",\"authors\":\"R. Sunthornwat, Y. Areepong\",\"doi\":\"10.14456/easr.2021.46\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The coronavirus disease outbreak in 2019 (COVID-19) has caused major economic and healthcare problems worldwide. At this time, the worldwide outbreak has passed its peak, while the greatest number of cases has been in the USA, Brazil, and India. Measures and policies for controlling the outbreak have been developed by authorities to protect the population of each country, and forecasting the number of infectious people is an important factor for developing them. This research was conducted to identify a suitable forecasting model for estimating the cumulative daily number of infectious people worldwide. Sample countries with severe outbreaks were selected from each continent. Herein, forecasting models based on logistic, Richards, and Gompertz growth curves are derived and their suitability for forecasting the COVID-19 rates in each sample country and worldwide are analyzed. Moreover, estimating the growth curve parameters is based on the least-squares method. The results show that the Gompert growth curve is the most suitable for estimating the cumulative number of infectious people worldwide. © 2021, Paulus Editora. All rights reserved.\",\"PeriodicalId\":37310,\"journal\":{\"name\":\"Engineering and Applied Science Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering and Applied Science Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14456/easr.2021.46\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering and Applied Science Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14456/easr.2021.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 3

摘要

2019年冠状病毒病(COVID-19)的爆发在全球范围内造成了重大的经济和医疗问题。目前，全球疫情已经过了高峰，而病例最多的是美国、巴西和印度。各国当局已经制定了控制疫情的措施和政策，以保护每个国家的人口，预测感染人数是制定这些措施和政策的一个重要因素。进行这项研究是为了确定一个合适的预测模型，以估计全世界每天的累计感染人数。从各大洲选取了疫情严重的样本国家。在此基础上，推导了基于logistic、Richards和Gompertz增长曲线的预测模型，并分析了其在每个样本国家和全球范围内预测COVID-19发病率的适用性。此外，生长曲线参数的估计是基于最小二乘法。结果表明，Gompert生长曲线最适合估计世界范围内的累计感染人数。©2021,Paulus Editora。版权所有。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Predictive models for the number of cumulative cases for spreading coronavirus disease 2019 in the world

The coronavirus disease outbreak in 2019 (COVID-19) has caused major economic and healthcare problems worldwide. At this time, the worldwide outbreak has passed its peak, while the greatest number of cases has been in the USA, Brazil, and India. Measures and policies for controlling the outbreak have been developed by authorities to protect the population of each country, and forecasting the number of infectious people is an important factor for developing them. This research was conducted to identify a suitable forecasting model for estimating the cumulative daily number of infectious people worldwide. Sample countries with severe outbreaks were selected from each continent. Herein, forecasting models based on logistic, Richards, and Gompertz growth curves are derived and their suitability for forecasting the COVID-19 rates in each sample country and worldwide are analyzed. Moreover, estimating the growth curve parameters is based on the least-squares method. The results show that the Gompert growth curve is the most suitable for estimating the cumulative number of infectious people worldwide. © 2021, Paulus Editora. All rights reserved.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Engineering and Applied Science Research Engineering-Engineering (all)

CiteScore

2.10

自引率

0.00%

发文量

审稿时长

11 weeks

期刊介绍： Publication of the journal started in 1974. Its original name was “KKU Engineering Journal”. English and Thai manuscripts were accepted. The journal was originally aimed at publishing research that was conducted and implemented in the northeast of Thailand. It is regarded a national journal and has been indexed in the Thai-journal Citation Index (TCI) database since 2004. The journal now accepts only English language manuscripts and became open-access in 2015 to attract more international readers. It was renamed Engineering and Applied Science Research in 2017. The editorial team agreed to publish more international papers, therefore, the new journal title is more appropriate. The journal focuses on research in the field of engineering that not only presents highly original ideas and advanced technology, but also are practical applications of appropriate technology.