This paper is in the following e-collection/theme issue:

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481) Outbreak and Pandemic Preparedness and Management (1673) Infectious Diseases (non-STD/STI) (1478) Innovative Methods in Public Health and Surveillance (305) Surveillance Systems (427) JMIR Theme Issue: COVID-19 Special Issue (2388) Behavioural Surveillance for Public Health (204) Surveillance Reports (122)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39754, first published .
Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study

Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study

Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study

Authors of this article:

Michael F Rayo1 Author Orcid Image ;   Daria Faulkner2 Author Orcid Image ;   David Kline3 Author Orcid Image ;   Thomas Thornhill IV4 Author Orcid Image ;   Samuel Malloy5 Author Orcid Image ;   Dante Della Vella1 Author Orcid Image ;   Dane A Morey1 Author Orcid Image ;   Net Zhang5 Author Orcid Image ;   Gregg Gonsalves4 Author Orcid Image
Article Authors Cited by Tweetations (4) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.