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.
@article{arxiv.2012.12135,
title = {COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation},
author = {Siva Athreya and Giridhara R. Babu and Aniruddha Iyer and Mohammed Minhaas B. S. and Nihesh Rathod and Sharad Shriram and Rajesh Sundaresan and Nidhin Koshy Vaidhiyan and Sarath Yasodharan},
journal= {arXiv preprint arXiv:2012.12135},
year = {2020}
}