Optimal Design of Serosurveys for Disease Burden Estimation

Abstract: The first state-wide COVID-19 serosurvey in Karnataka, a state in India with a population of about 70 million, was done in September 2020 when the infection was near a peak. For accurate total disease-burden estimation at such times, one needs to estimate the active infection in the population along with the seroprevalence of antibodies to the virus. This entails the use of multiple tests for the detection of antigens, viral RNA, and antibodies. Given a family of such tests, their sensitivities, specificities, and costs, what are good survey designs? In this talk, we will discuss a model for disease prevalence, the so-called c-optimal design criterion, and its solution. We will also discuss other criteria and their use in Karnataka's second statewide serosurvey which concluded only recently. The talk is based on joint work with collaborators from the Indian Institute of Public Health, Indian Statistical Institute, Strand Life Sciences, and the Indian Institute of Science.

Bio: Rajesh Sundaresan is a Professor at the Indian Institute of Science. He is currently on sabbatical leave visiting Strand Life Science and the Indian Statistical Institute. His research interests are in communication, computation, and control over networks. For recent COVID-19 modeling and epidemiological work, please visit his webpage: https://ece.iisc.ac.in/~rajeshs.