Adaptive Surveillance Testing for Efficient Infection Rate Estimation

Songtao Feng, Jing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we study a surveillance testing problem where the learner aims to monitor the infection rate in a community with large population. At each time t, the learner is able to collect samples from a randomly selected group of individuals in the community and perform group testing. The test result is equal to one if at least one individual in the selected group is infected and zero otherwise. Assume each individual is infected according to an independent and identically distributed Bernoulli random variable with parameter p. Our objective is to design an efficient testing procedure to decide the number of samples included in each step for group testing and obtain an accurate estimate of the infection rate p with high probability. We present a two-phase adaptive testing algorithm and show that it reduces the number of tests required to achieve the desired accuracy level compared with the single-sample testing approach. When p is sufficiently small, which is the regime of interest in practice, it leads to an order-of-magnitude improvement. Simulation corroborates theoretical results.

Original languageEnglish (US)
Title of host publication2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538682098
StatePublished - Jul 12 2021
Event2021 IEEE International Symposium on Information Theory, ISIT 2021 - Virtual, Melbourne, Australia
Duration: Jul 12 2021Jul 20 2021

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095


Conference2021 IEEE International Symposium on Information Theory, ISIT 2021
CityVirtual, Melbourne

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics


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