2019冠状病毒病再生产数R的数学计算:人口统计学家入门

Q3 Social Sciences

Vienna Yearbook of Population Research Pub Date : 2020-11-17 DOI:10.31235/osf.io/u6ey9

L. Rosero-Bixby, Tim Miller

{"title":"2019冠状病毒病再生产数R的数学计算:人口统计学家入门","authors":"L. Rosero-Bixby, Tim Miller","doi":"10.31235/osf.io/u6ey9","DOIUrl":null,"url":null,"abstract":"The reproduction number R is a key indicator to monitor the dynamics of Covid-19 and to assess the effect of control strategies that frequently have high social and economic costs. Despite having an analog in demography’s “net reproduction rate” that has been routinely computed for a century, demographers may not be familiar with the concept and measurement of R in the context of Covid-19. This article intends to be a primer for understanding and estimating R in demography. We show that R can be estimated as a ratio between the numbers of new cases today divided by the weighted average of cases in previous days. We present two alternative derivations for these weights based on how risks change over time: constant vs. exponential decay. We provide estimates of these weights and demonstrate their use in calculating R to trace the course of the first pandemic year in several countries.","PeriodicalId":34968,"journal":{"name":"Vienna Yearbook of Population Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The mathematics of the reproduction number R for Covid-19: A primer for demographers\",\"authors\":\"L. Rosero-Bixby, Tim Miller\",\"doi\":\"10.31235/osf.io/u6ey9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The reproduction number R is a key indicator to monitor the dynamics of Covid-19 and to assess the effect of control strategies that frequently have high social and economic costs. Despite having an analog in demography’s “net reproduction rate” that has been routinely computed for a century, demographers may not be familiar with the concept and measurement of R in the context of Covid-19. This article intends to be a primer for understanding and estimating R in demography. We show that R can be estimated as a ratio between the numbers of new cases today divided by the weighted average of cases in previous days. We present two alternative derivations for these weights based on how risks change over time: constant vs. exponential decay. We provide estimates of these weights and demonstrate their use in calculating R to trace the course of the first pandemic year in several countries.\",\"PeriodicalId\":34968,\"journal\":{\"name\":\"Vienna Yearbook of Population Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vienna Yearbook of Population Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31235/osf.io/u6ey9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vienna Yearbook of Population Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31235/osf.io/u6ey9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}

引用次数: 3

摘要

复制数R是监测Covid-19动态和评估控制战略效果的关键指标，这些战略往往具有高昂的社会和经济成本。尽管一个世纪以来，人口统计学家经常计算“净再生率”，但在Covid-19的背景下，人口统计学家可能不熟悉R的概念和测量方法。本文旨在成为理解和估计人口统计学中的R的入门读物。我们表明，R可以估计为今天的新病例数除以前几天病例的加权平均值之间的比率。基于风险随时间的变化，我们提出了两种不同的权重推导:常数衰减与指数衰减。我们提供了这些权重的估计值，并展示了它们在计算R以追踪几个国家大流行第一年的过程中的应用。

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

The mathematics of the reproduction number R for Covid-19: A primer for demographers

The reproduction number R is a key indicator to monitor the dynamics of Covid-19 and to assess the effect of control strategies that frequently have high social and economic costs. Despite having an analog in demography’s “net reproduction rate” that has been routinely computed for a century, demographers may not be familiar with the concept and measurement of R in the context of Covid-19. This article intends to be a primer for understanding and estimating R in demography. We show that R can be estimated as a ratio between the numbers of new cases today divided by the weighted average of cases in previous days. We present two alternative derivations for these weights based on how risks change over time: constant vs. exponential decay. We provide estimates of these weights and demonstrate their use in calculating R to trace the course of the first pandemic year in several countries.

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

Vienna Yearbook of Population Research Social Sciences-Demography

CiteScore

1.90

自引率

0.00%

发文量

期刊介绍： In Europe there is currently an increasing public awareness of the importance that demographic trends have in reshaping our societies. Concerns about possible negative consequences of population aging seem to be the major force behind this new interest in demographic research. Demographers have been pointing out the fundamental change in the age composition of European populations and its potentially serious implications for social security schemes for more than two decades but it is only now that the expected retirement of the baby boom generation has come close enough in time to appear on the radar screen of social security planners and political decision makers to be considered a real challenge and not just an academic exercise.