{"title":"基于严格指数对E7国家COVID-19感染情况进行预测并提出相关政策建议。","authors":"İhsan Erdem Kayral, Sencer Buzrul","doi":"10.15586/jptcp.v27SP1.757","DOIUrl":null,"url":null,"abstract":"COVID-19 infection data of Emerging 7 (E7) countries, namely Brazil, China, India, Indonesia, Mexico, Russia, and Turkey were described by an empirical model or a special case of this empirical model. Near-future forecasts were also performed. Moreover, the causalities between the Stringency Index's indicators and total cases in E7 countries in COVID-19 period were examined. Countries were grouped as \"stationary,\" \"transition,\" and \"exponential\" based on the data and model fits. The proposed models produced good fits to the COVID-19 data of E7 countries and it was possible to predict the number of cases in the near future. Some policies to control total cases in E7 countries were also proposed in the final phase of this study based on the findings and forecasting in these countries.","PeriodicalId":73904,"journal":{"name":"Journal of population therapeutics and clinical pharmacology = Journal de la therapeutique des populations et de la pharmacologie clinique","volume":"27 S Pt 1","pages":"e76-e84"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Forecasting of COVID-19 infections in E7 countries and proposing some policies based on the Stringency Index.\",\"authors\":\"İhsan Erdem Kayral, Sencer Buzrul\",\"doi\":\"10.15586/jptcp.v27SP1.757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"COVID-19 infection data of Emerging 7 (E7) countries, namely Brazil, China, India, Indonesia, Mexico, Russia, and Turkey were described by an empirical model or a special case of this empirical model. Near-future forecasts were also performed. Moreover, the causalities between the Stringency Index's indicators and total cases in E7 countries in COVID-19 period were examined. Countries were grouped as \\\"stationary,\\\" \\\"transition,\\\" and \\\"exponential\\\" based on the data and model fits. The proposed models produced good fits to the COVID-19 data of E7 countries and it was possible to predict the number of cases in the near future. Some policies to control total cases in E7 countries were also proposed in the final phase of this study based on the findings and forecasting in these countries.\",\"PeriodicalId\":73904,\"journal\":{\"name\":\"Journal of population therapeutics and clinical pharmacology = Journal de la therapeutique des populations et de la pharmacologie clinique\",\"volume\":\"27 S Pt 1\",\"pages\":\"e76-e84\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of population therapeutics and clinical pharmacology = Journal de la therapeutique des populations et de la pharmacologie clinique\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15586/jptcp.v27SP1.757\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of population therapeutics and clinical pharmacology = Journal de la therapeutique des populations et de la pharmacologie clinique","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15586/jptcp.v27SP1.757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting of COVID-19 infections in E7 countries and proposing some policies based on the Stringency Index.
COVID-19 infection data of Emerging 7 (E7) countries, namely Brazil, China, India, Indonesia, Mexico, Russia, and Turkey were described by an empirical model or a special case of this empirical model. Near-future forecasts were also performed. Moreover, the causalities between the Stringency Index's indicators and total cases in E7 countries in COVID-19 period were examined. Countries were grouped as "stationary," "transition," and "exponential" based on the data and model fits. The proposed models produced good fits to the COVID-19 data of E7 countries and it was possible to predict the number of cases in the near future. Some policies to control total cases in E7 countries were also proposed in the final phase of this study based on the findings and forecasting in these countries.