An entropy reduction approach to continual testing

An entropy reduction approach to continual testing

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 pape...

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Bibliographic Details
Published in:2021 IEEE International Symposium on Information Theory (ISIT) pp. 611 - 616
Main Authors: Srinivasavaradhan, Sundara Rajan, Nikolopoulos, Pavlos, Fragouli, Christina, Diggavi, Suhas
Format: Conference Proceeding
Language:English
Published: IEEE 12-07-2021
Subjects:
Entropy
Epidemics
Sociology
State estimation
Statistics
Stochastic processes
Task analysis
Online Access:Get full text
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Summary: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.
DOI:10.1109/ISIT45174.2021.9518188