|| An Entropy Reduction Approach to Continual Testing
||Sundara Rajan Srinivasavaradhan, University of California, Los Angeles, United States; Pavlos Nikolopoulos, École polytechnique fédérale de Lausanne, Switzerland; Christina Fragouli, Suhas Diggavi, University of California, Los Angeles, United States|
||D2-S2-T3: Sequential Detection
||Tuesday, 13 July, 22:20 - 22:40
||Tuesday, 13 July, 22:40 - 23:00
SIR (Susceptible, Infected or Recovered) stochastic network models are commonly used to describe the progression of epidemics inside a network. A task of interest in epidemiology is to use these models to estimate the state evolution, both at an individual as well as a population level. In this paper, we propose using continual testing to improve the state estimation at the individual level. Our testing is inspired from entropy reduction principles and requires only a small number of tests.