{"title":"史蒂文·莱利在2021年6月9日皇家统计学会2019冠状病毒病传播专题会议第一届会议上对论文的讨论贡献","authors":"Steven Riley","doi":"10.1111/rssa.12891","DOIUrl":null,"url":null,"abstract":"<p>I congratulate: Parag, Thompson, and Donnelly; Jewell and Lewnard; and Coffeng and de Vlas on their papers which highlight both the benefits and potential pitfalls associated with statistics such as the doubling time <math>\n <msub>\n <mi>T</mi>\n <mi>d</mi>\n </msub></math> and the basic reproductive number <math>\n <msub>\n <mi>R</mi>\n <mn>0</mn>\n </msub></math> during the COVID-19 pandemic. As is appropriate for a methodological meeting, these papers focus on the choice of statistics themselves rather than the specific data sets on which estimates are based. In this brief comment, I would like to also highlight opportunities for innovative study design and mention specifically the value of accurate measures of infection prevalence.</p><p>During a pandemic, when the value of epidemiological information is much higher than at other times, there is an opportunity to gather novel population data which would otherwise be deemed too expensive. In the UK, there are a number of examples of community surveys, including the Office for National Statistics Coronavirus Infection Survey (Pouwels et al., <span>2021</span>), Virus Watch (Hayward et al., <span>2020</span>) and the REal-time Assessment of Community Transmission (REACT) (Riley et al., <span>2020</span>). REACT is a program of studies separated into REACT-1 (Riley et al., <span>2021</span>) that collects self-administered nose and throat swabs (Riley et al., <span>2021</span>) and REACT-2 that collects self-administered lateral-flow antibody tests (Ward et al., <span>2021</span>).</p><p>Incidence and growth-rate estimates based on routine surveillance are subject to changes in the propensity of individuals to seek tests and in the ability of the system to supply those test (Omori et al., <span>2020</span>). Community surveys can help to overcome these issues. For example, in recruiting participants randomly from those registered for healthcare in England, the REACT-1 design attempts to reduce the impact of temporal variation when making growth rate estimates (Riley et al., <span>2021</span>).</p><p>In addition to growth rates, population surveys of infection provide estimates of prevalence at national and regional scales that can be easily understood as measures of individual risk: measured swab-positivity is easily translated into odds of infection. While doubling times and reproduction numbers are valuable as indicators of future changes in risk, it could be argued that their prominence in official UK government communications in the UK has led to their value in assessing current levels of risk being overestimated.</p>","PeriodicalId":49983,"journal":{"name":"Journal of the Royal Statistical Society Series A-Statistics in Society","volume":"185 S1","pages":"S53-S54"},"PeriodicalIF":1.5000,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssa.12891","citationCount":"0","resultStr":"{\"title\":\"Steven Riley’s discussion contribution to papers in Session 1 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 transmission: 9 June 2021\",\"authors\":\"Steven Riley\",\"doi\":\"10.1111/rssa.12891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>I congratulate: Parag, Thompson, and Donnelly; Jewell and Lewnard; and Coffeng and de Vlas on their papers which highlight both the benefits and potential pitfalls associated with statistics such as the doubling time <math>\\n <msub>\\n <mi>T</mi>\\n <mi>d</mi>\\n </msub></math> and the basic reproductive number <math>\\n <msub>\\n <mi>R</mi>\\n <mn>0</mn>\\n </msub></math> during the COVID-19 pandemic. As is appropriate for a methodological meeting, these papers focus on the choice of statistics themselves rather than the specific data sets on which estimates are based. In this brief comment, I would like to also highlight opportunities for innovative study design and mention specifically the value of accurate measures of infection prevalence.</p><p>During a pandemic, when the value of epidemiological information is much higher than at other times, there is an opportunity to gather novel population data which would otherwise be deemed too expensive. In the UK, there are a number of examples of community surveys, including the Office for National Statistics Coronavirus Infection Survey (Pouwels et al., <span>2021</span>), Virus Watch (Hayward et al., <span>2020</span>) and the REal-time Assessment of Community Transmission (REACT) (Riley et al., <span>2020</span>). REACT is a program of studies separated into REACT-1 (Riley et al., <span>2021</span>) that collects self-administered nose and throat swabs (Riley et al., <span>2021</span>) and REACT-2 that collects self-administered lateral-flow antibody tests (Ward et al., <span>2021</span>).</p><p>Incidence and growth-rate estimates based on routine surveillance are subject to changes in the propensity of individuals to seek tests and in the ability of the system to supply those test (Omori et al., <span>2020</span>). Community surveys can help to overcome these issues. For example, in recruiting participants randomly from those registered for healthcare in England, the REACT-1 design attempts to reduce the impact of temporal variation when making growth rate estimates (Riley et al., <span>2021</span>).</p><p>In addition to growth rates, population surveys of infection provide estimates of prevalence at national and regional scales that can be easily understood as measures of individual risk: measured swab-positivity is easily translated into odds of infection. While doubling times and reproduction numbers are valuable as indicators of future changes in risk, it could be argued that their prominence in official UK government communications in the UK has led to their value in assessing current levels of risk being overestimated.</p>\",\"PeriodicalId\":49983,\"journal\":{\"name\":\"Journal of the Royal Statistical Society Series A-Statistics in Society\",\"volume\":\"185 S1\",\"pages\":\"S53-S54\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/rssa.12891\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Royal Statistical Society Series A-Statistics in Society\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/rssa.12891\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Statistical Society Series A-Statistics in Society","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/rssa.12891","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
Steven Riley’s discussion contribution to papers in Session 1 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 transmission: 9 June 2021
I congratulate: Parag, Thompson, and Donnelly; Jewell and Lewnard; and Coffeng and de Vlas on their papers which highlight both the benefits and potential pitfalls associated with statistics such as the doubling time and the basic reproductive number during the COVID-19 pandemic. As is appropriate for a methodological meeting, these papers focus on the choice of statistics themselves rather than the specific data sets on which estimates are based. In this brief comment, I would like to also highlight opportunities for innovative study design and mention specifically the value of accurate measures of infection prevalence.
During a pandemic, when the value of epidemiological information is much higher than at other times, there is an opportunity to gather novel population data which would otherwise be deemed too expensive. In the UK, there are a number of examples of community surveys, including the Office for National Statistics Coronavirus Infection Survey (Pouwels et al., 2021), Virus Watch (Hayward et al., 2020) and the REal-time Assessment of Community Transmission (REACT) (Riley et al., 2020). REACT is a program of studies separated into REACT-1 (Riley et al., 2021) that collects self-administered nose and throat swabs (Riley et al., 2021) and REACT-2 that collects self-administered lateral-flow antibody tests (Ward et al., 2021).
Incidence and growth-rate estimates based on routine surveillance are subject to changes in the propensity of individuals to seek tests and in the ability of the system to supply those test (Omori et al., 2020). Community surveys can help to overcome these issues. For example, in recruiting participants randomly from those registered for healthcare in England, the REACT-1 design attempts to reduce the impact of temporal variation when making growth rate estimates (Riley et al., 2021).
In addition to growth rates, population surveys of infection provide estimates of prevalence at national and regional scales that can be easily understood as measures of individual risk: measured swab-positivity is easily translated into odds of infection. While doubling times and reproduction numbers are valuable as indicators of future changes in risk, it could be argued that their prominence in official UK government communications in the UK has led to their value in assessing current levels of risk being overestimated.
期刊介绍:
Series A (Statistics in Society) publishes high quality papers that demonstrate how statistical thinking, design and analyses play a vital role in all walks of life and benefit society in general. There is no restriction on subject-matter: any interesting, topical and revelatory applications of statistics are welcome. For example, important applications of statistical and related data science methodology in medicine, business and commerce, industry, economics and finance, education and teaching, physical and biomedical sciences, the environment, the law, government and politics, demography, psychology, sociology and sport all fall within the journal''s remit. The journal is therefore aimed at a wide statistical audience and at professional statisticians in particular. Its emphasis is on well-written and clearly reasoned quantitative approaches to problems in the real world rather than the exposition of technical detail. Thus, although the methodological basis of papers must be sound and adequately explained, methodology per se should not be the main focus of a Series A paper. Of particular interest are papers on topical or contentious statistical issues, papers which give reviews or exposés of current statistical concerns and papers which demonstrate how appropriate statistical thinking has contributed to our understanding of important substantive questions. Historical, professional and biographical contributions are also welcome, as are discussions of methods of data collection and of ethical issues, provided that all such papers have substantial statistical relevance.