{"title":"需要隔离的人数——一种新的人口健康指标,用于量化传染病隔离干预措施减少传播的情况。","authors":"Aaron Prosser, Bartosz Helfer, David L Streiner","doi":"10.1186/s12963-024-00360-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>We have previously developed and reported on a procedure for estimating the purported benefits of immunity mandates using a novel variant of the number needed to treat (NNT) which we called the number needed to isolate (NNI). Here we demonstrate its broader properties as a useful population health metric.</p><p><strong>Main body: </strong>The NNI is analogous to the number needed to treat (NNT = 1/ARR), except the absolute risk reduction (ARR) is the absolute transmission risk in a specific population. The NNI is the number of susceptible hosts in a population who need to be isolated to prevent one transmission event from them. The properties and utility of the NNI were modeled using simulated data and its model predictions were validated using real world data. The properties of the NNI are described for three categories of data from a previous study on transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): (1) in different settings, (2) after a specific exposure and (3) depending on symptomaticity status of susceptible hosts.</p><p><strong>Conclusions: </strong>We provide a demonstration of the utility of the NNI as a valuable population health metric to quantify the transmission reductions from isolation interventions.</p>","PeriodicalId":51476,"journal":{"name":"Population Health Metrics","volume":"22 1","pages":"39"},"PeriodicalIF":3.2000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11668099/pdf/","citationCount":"0","resultStr":"{\"title\":\"Number needed to isolate - a new population health metric to quantify transmission reductions from isolation interventions for infectious diseases.\",\"authors\":\"Aaron Prosser, Bartosz Helfer, David L Streiner\",\"doi\":\"10.1186/s12963-024-00360-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>We have previously developed and reported on a procedure for estimating the purported benefits of immunity mandates using a novel variant of the number needed to treat (NNT) which we called the number needed to isolate (NNI). Here we demonstrate its broader properties as a useful population health metric.</p><p><strong>Main body: </strong>The NNI is analogous to the number needed to treat (NNT = 1/ARR), except the absolute risk reduction (ARR) is the absolute transmission risk in a specific population. The NNI is the number of susceptible hosts in a population who need to be isolated to prevent one transmission event from them. The properties and utility of the NNI were modeled using simulated data and its model predictions were validated using real world data. The properties of the NNI are described for three categories of data from a previous study on transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): (1) in different settings, (2) after a specific exposure and (3) depending on symptomaticity status of susceptible hosts.</p><p><strong>Conclusions: </strong>We provide a demonstration of the utility of the NNI as a valuable population health metric to quantify the transmission reductions from isolation interventions.</p>\",\"PeriodicalId\":51476,\"journal\":{\"name\":\"Population Health Metrics\",\"volume\":\"22 1\",\"pages\":\"39\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11668099/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Population Health Metrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12963-024-00360-y\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Population Health Metrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12963-024-00360-y","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Number needed to isolate - a new population health metric to quantify transmission reductions from isolation interventions for infectious diseases.
Background: We have previously developed and reported on a procedure for estimating the purported benefits of immunity mandates using a novel variant of the number needed to treat (NNT) which we called the number needed to isolate (NNI). Here we demonstrate its broader properties as a useful population health metric.
Main body: The NNI is analogous to the number needed to treat (NNT = 1/ARR), except the absolute risk reduction (ARR) is the absolute transmission risk in a specific population. The NNI is the number of susceptible hosts in a population who need to be isolated to prevent one transmission event from them. The properties and utility of the NNI were modeled using simulated data and its model predictions were validated using real world data. The properties of the NNI are described for three categories of data from a previous study on transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): (1) in different settings, (2) after a specific exposure and (3) depending on symptomaticity status of susceptible hosts.
Conclusions: We provide a demonstration of the utility of the NNI as a valuable population health metric to quantify the transmission reductions from isolation interventions.
期刊介绍:
Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.