EpiCURB: Learning to Derive Epidemic Control Policies-Reference-Cited by-同舟云学术

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EpiCURB: Learning to Derive Epidemic Control Policies

Published:2024-01 Issue:1 Volume:23 Page:57-62
ISSN:1536-1268
Container-title:IEEE Pervasive Computing
language:
Short-container-title:IEEE Pervasive Comput.

Author:

Rusu Andrei C.¹^ORCID,Farrahi Katayoun¹^ORCID,Niranjan Mahesan¹^ORCID

Affiliation:

1. University of Southampton, Southampton, U.K.

Funder

Engineering and Physical Sciences Research Council

University of Southampton

Artificial and Augmented Intelligence for Automated Scientific Discovery

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7756/10546482/10546494.pdf?arnumber=10546494

Reference23 articles.

1. Country level analysis of COVID-19 policies

2. Did lockdowns work? The verdict on Covid restrictions;Herby,Jun. 5, 2023

3. Flattening the Curve Through Reinforcement Learning Driven Test and Trace Policies

4. Modelling digital and manual contact tracing for COVID-19. Are low uptakes and missed contacts deal-breakers?

5. Epidemic Contact Tracing via Communication Traces

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