{"title":"A spline-based time-varying reproduction number for modelling epidemiological outbreaks","authors":"Eugen Pircalabelu","doi":"10.1093/jrsssc/qlad027","DOIUrl":null,"url":null,"abstract":"\n We develop in this manuscript a method for performing estimation and inference for the reproduction number of an epidemiological outbreak, focusing on the COVID-19 epidemic. The estimator is time-dependent and uses spline modelling to adapt to changes in the outbreak. This is accomplished by directly modelling the series of new infections as a function of time and subsequently using the derivative of the function to define a time-varying reproduction number, which is then used to assess the evolution of the epidemic for several countries.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"26 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Statistical Society Series C-Applied Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/jrsssc/qlad027","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 2
Abstract
We develop in this manuscript a method for performing estimation and inference for the reproduction number of an epidemiological outbreak, focusing on the COVID-19 epidemic. The estimator is time-dependent and uses spline modelling to adapt to changes in the outbreak. This is accomplished by directly modelling the series of new infections as a function of time and subsequently using the derivative of the function to define a time-varying reproduction number, which is then used to assess the evolution of the epidemic for several countries.
期刊介绍：
The Journal of the Royal Statistical Society, Series C (Applied Statistics) is a journal of international repute for statisticians both inside and outside the academic world. The journal is concerned with papers which deal with novel solutions to real life statistical problems by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to them. At their heart therefore the papers in the journal are motivated by examples and statistical data of all kinds. The subject-matter covers the whole range of inter-disciplinary fields, e.g. applications in agriculture, genetics, industry, medicine and the physical sciences, and papers on design issues (e.g. in relation to experiments, surveys or observational studies).
A deep understanding of statistical methodology is not necessary to appreciate the content. Although papers describing developments in statistical computing driven by practical examples are within its scope, the journal is not concerned with simply numerical illustrations or simulation studies. The emphasis of Series C is on case-studies of statistical analyses in practice.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
