Srinivasavaradhan, Sundara RajanNikolopoulos, PavlosFragouli, ChristinaDiggavi, Suhas2021-11-062021-11-062021-11-062021-01-0110.1109/ISIT45174.2021.9518188https://infoscience.epfl.ch/handle/20.500.14299/182810WOS:000701502200104SIR (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.Computer Science, Theory & MethodsEngineering, Electrical & ElectronicComputer ScienceEngineeringdefective memberstext::conference output::conference proceedings::conference paper