| Paper ID | D2-S2-T3.3 |
| Paper Title |
An Entropy Reduction Approach to Continual Testing |
| Authors |
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 |
| Session |
D2-S2-T3: Sequential Detection |
| Chaired Session: |
Tuesday, 13 July, 22:20 - 22:40 |
| Engagement Session: |
Tuesday, 13 July, 22:40 - 23:00 |
| Abstract |
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.
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