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

Authors

Siva Athreya, Indian Statistical Institute Bangalore
Giridhara R. Babu, Institute of Public Health
Aniruddha Iyer, Indian Institute of Science
Mohammed M.B. Minhaas, 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

Article Type

Research Article

Publication Title

Sankhya B

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.

First Page

472

Last Page

494

DOI

10.1007/s13571-021-00267-w

Publication Date

11-1-2022

Comments

Open Access, Hybrid Gold

Recommended Citation

Athreya, Siva; Babu, Giridhara R.; Iyer, Aniruddha; Minhaas, Mohammed M.B.; Rathod, Nihesh; Shriram, Sharad; Sundaresan, Rajesh; Vaidhiyan, Nidhin Koshy; and Yasodharan, Sarath, "COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation" (2022). Journal Articles. 2919.
https://digitalcommons.isical.ac.in/journal-articles/2919