COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation

Siva Athreya (), Giridhara R. Babu (), Aniruddha Iyer (), Mohammed Minhaas B. S. (), Nihesh Rathod (), Sharad Shriram (), Rajesh Sundaresan (), Nidhin Koshy Vaidhiyan () and Sarath Yasodharan ()
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Siva Athreya: Indian Statistical Institute
Giridhara R. Babu: Indian Institute of Public Health
Aniruddha Iyer: Indian Institute of Science
Mohammed Minhaas B. S.: Indian Institute of Science
Nihesh Rathod: Indian Institute of Science
Sharad Shriram: Indian Institute of Science
Rajesh Sundaresan: Indian Institute of Science
Nidhin Koshy Vaidhiyan: Indian Institute of Science
Sarath Yasodharan: Indian Institute of Science

Sankhya B: The Indian Journal of Statistics, 2022, vol. 84, issue 2, No 2, 472-494

Abstract: 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.

Keywords: c-optimal design; serosurvey; COVID-19; worst-case design; Fisher information; weighted estimate; adjusted estimate.; Primary 62K05; Secondary 62P10 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13571-021-00267-w

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