{"title":"研究报告:新颖的沙利文法投影框架在长 COVID 中的应用。","authors":"Cayley Ryan-Claytor, Ashton Verdery","doi":"10.1215/00703370-11226858","DOIUrl":null,"url":null,"abstract":"<p><p>Originally developed for estimating healthy life expectancy, the traditional Sullivan method continues to be a popular tool for obtaining point-in-time estimates of the population impacts of a wide range of health and social conditions. However, except in rare data-intensive cases, the method is subject to stringent stationarity assumptions, which often do not align with real-world conditions and restrict its resulting estimates and applications. In this research note, we present an expansion of the original method to apply within a population projection framework. The Sullivan method projection framework produces estimates that offer new insights about future trends in population health and social arrangements under various demographic and epidemiologic scenarios, such as the percentage of life years that population members can expect to spend with a condition of interest in a time interval under different assumptions. We demonstrate the utility of this framework using the case of long COVID, illustrating both its operation and potential to reveal insights about emergent population health challenges under various theoretically informed scenarios. The traditional Sullivan method provides a summary measure of the present, while its incorporation into a projection framework enables preparation for a variety of potential futures.</p>","PeriodicalId":48394,"journal":{"name":"Demography","volume":" ","pages":"267-281"},"PeriodicalIF":3.6000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research Note: A Novel Sullivan Method Projection Framework With Application to Long COVID.\",\"authors\":\"Cayley Ryan-Claytor, Ashton Verdery\",\"doi\":\"10.1215/00703370-11226858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Originally developed for estimating healthy life expectancy, the traditional Sullivan method continues to be a popular tool for obtaining point-in-time estimates of the population impacts of a wide range of health and social conditions. However, except in rare data-intensive cases, the method is subject to stringent stationarity assumptions, which often do not align with real-world conditions and restrict its resulting estimates and applications. In this research note, we present an expansion of the original method to apply within a population projection framework. The Sullivan method projection framework produces estimates that offer new insights about future trends in population health and social arrangements under various demographic and epidemiologic scenarios, such as the percentage of life years that population members can expect to spend with a condition of interest in a time interval under different assumptions. We demonstrate the utility of this framework using the case of long COVID, illustrating both its operation and potential to reveal insights about emergent population health challenges under various theoretically informed scenarios. The traditional Sullivan method provides a summary measure of the present, while its incorporation into a projection framework enables preparation for a variety of potential futures.</p>\",\"PeriodicalId\":48394,\"journal\":{\"name\":\"Demography\",\"volume\":\" \",\"pages\":\"267-281\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Demography\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1215/00703370-11226858\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Demography","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1215/00703370-11226858","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Research Note: A Novel Sullivan Method Projection Framework With Application to Long COVID.
Originally developed for estimating healthy life expectancy, the traditional Sullivan method continues to be a popular tool for obtaining point-in-time estimates of the population impacts of a wide range of health and social conditions. However, except in rare data-intensive cases, the method is subject to stringent stationarity assumptions, which often do not align with real-world conditions and restrict its resulting estimates and applications. In this research note, we present an expansion of the original method to apply within a population projection framework. The Sullivan method projection framework produces estimates that offer new insights about future trends in population health and social arrangements under various demographic and epidemiologic scenarios, such as the percentage of life years that population members can expect to spend with a condition of interest in a time interval under different assumptions. We demonstrate the utility of this framework using the case of long COVID, illustrating both its operation and potential to reveal insights about emergent population health challenges under various theoretically informed scenarios. The traditional Sullivan method provides a summary measure of the present, while its incorporation into a projection framework enables preparation for a variety of potential futures.
期刊介绍:
Since its founding in 1964, the journal Demography has mirrored the vitality, diversity, high intellectual standard and wide impact of the field on which it reports. Demography presents the highest quality original research of scholars in a broad range of disciplines, including anthropology, biology, economics, geography, history, psychology, public health, sociology, and statistics. The journal encompasses a wide variety of methodological approaches to population research. Its geographic focus is global, with articles addressing demographic matters from around the planet. Its temporal scope is broad, as represented by research that explores demographic phenomena spanning the ages from the past to the present, and reaching toward the future. Authors whose work is published in Demography benefit from the wide audience of population scientists their research will reach. Also in 2011 Demography remains the most cited journal among population studies and demographic periodicals. Published bimonthly, Demography is the flagship journal of the Population Association of America, reaching the membership of one of the largest professional demographic associations in the world.