Siva Athreya, Giridhara R Babu, Aniruddha Iyer, Mohammed Minhaas B S, Nihesh Rathod, Sharad Shriram, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan
{"title":"COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation.","authors":"Siva Athreya, Giridhara R Babu, Aniruddha Iyer, Mohammed Minhaas B S, Nihesh Rathod, Sharad Shriram, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan","doi":"10.1007/s13571-021-00267-w","DOIUrl":null,"url":null,"abstract":"<p><p>We provide a methodology by which an epidemiologist may arrive at an optimal design for a survey whose goal is to estimate the disease burden in a population. For serosurveys with a given budget of <i>C</i> rupees, a specified set of tests with costs, sensitivities, and specificities, we show the existence of optimal designs in four different contexts, including the well known c-optimal design. Usefulness of the results are illustrated via numerical examples. Our results are applicable to a wide range of epidemiological surveys under the assumptions that the estimate's Fisher-information matrix satisfies a uniform positive definite criterion.</p>","PeriodicalId":74754,"journal":{"name":"Sankhya. Series B (2008)","volume":"84 2","pages":"472-494"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524406/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sankhya. Series B (2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13571-021-00267-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/10/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We provide a methodology by which an epidemiologist may arrive at an optimal design for a survey whose goal is to estimate the disease burden in a population. For serosurveys with a given budget of C rupees, a specified set of tests with costs, sensitivities, and specificities, we show the existence of optimal designs in four different contexts, including the well known c-optimal design. Usefulness of the results are illustrated via numerical examples. Our results are applicable to a wide range of epidemiological surveys under the assumptions that the estimate's Fisher-information matrix satisfies a uniform positive definite criterion.