The effective reproductive number: Modeling and prediction with application to the multi-wave Covid-19 pandemic

IF 3 3区 医学 Q2 INFECTIOUS DISEASES
Razvan G. Romanescu , Songdi Hu , Douglas Nanton , Mahmoud Torabi , Olivier Tremblay-Savard , Md Ashiqul Haque
{"title":"The effective reproductive number: Modeling and prediction with application to the multi-wave Covid-19 pandemic","authors":"Razvan G. Romanescu ,&nbsp;Songdi Hu ,&nbsp;Douglas Nanton ,&nbsp;Mahmoud Torabi ,&nbsp;Olivier Tremblay-Savard ,&nbsp;Md Ashiqul Haque","doi":"10.1016/j.epidem.2023.100708","DOIUrl":null,"url":null,"abstract":"<div><p>Classical compartmental models of infectious disease assume that spread occurs through a homogeneous population. This produces poor fits to real data, because individuals vary in their number of epidemiologically-relevant contacts, and hence in their ability to transmit disease. In particular, network theory suggests that super-spreading events tend to happen more often at the beginning of an epidemic, which is inconsistent with the homogeneity assumption. In this paper we argue that a flexible decay shape for the effective reproductive number (<span><math><msub><mrow><mi>R</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span>) indexed by the susceptible fraction (<span><math><msub><mrow><mi>S</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span>) is a theory-informed modeling choice, which better captures the progression of disease incidence over human populations. This, in turn, produces better retrospective fits, as well as more accurate prospective predictions of observed epidemic curves. We extend this framework to fit multi-wave epidemics, and to accommodate public health restrictions on mobility. We demonstrate the performance of this model by doing a prediction study over two years of the SARS-CoV2 pandemic.</p></div>","PeriodicalId":49206,"journal":{"name":"Epidemics","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1755436523000440","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0

Abstract

Classical compartmental models of infectious disease assume that spread occurs through a homogeneous population. This produces poor fits to real data, because individuals vary in their number of epidemiologically-relevant contacts, and hence in their ability to transmit disease. In particular, network theory suggests that super-spreading events tend to happen more often at the beginning of an epidemic, which is inconsistent with the homogeneity assumption. In this paper we argue that a flexible decay shape for the effective reproductive number (Rt) indexed by the susceptible fraction (St) is a theory-informed modeling choice, which better captures the progression of disease incidence over human populations. This, in turn, produces better retrospective fits, as well as more accurate prospective predictions of observed epidemic curves. We extend this framework to fit multi-wave epidemics, and to accommodate public health restrictions on mobility. We demonstrate the performance of this model by doing a prediction study over two years of the SARS-CoV2 pandemic.

有效繁殖数量:建模和预测,并应用于多波新冠肺炎大流行。
传染病的经典分区模型假设传播是通过同质人群发生的。这产生了与真实数据的不匹配,因为个体的流行病学相关接触者数量不同,因此传播疾病的能力也不同。特别是,网络理论表明,超级传播事件往往更频繁地发生在流行病开始时,这与同质性假设不一致。在本文中,我们认为,由易感分数(St)索引的有效繁殖数(Rt)的灵活衰变形状是一种基于理论的建模选择,它可以更好地捕捉疾病发病率在人类群体中的进展。这反过来又产生了更好的回顾性拟合,以及对观察到的流行病曲线的更准确的前瞻性预测。我们扩展了这一框架,以适应多波流行病,并适应公共卫生对流动性的限制。我们通过对严重急性呼吸系统综合征冠状病毒2型疫情两年的预测研究来证明该模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Epidemics
Epidemics INFECTIOUS DISEASES-
CiteScore
6.00
自引率
7.90%
发文量
92
审稿时长
140 days
期刊介绍: Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信