AI for Covid-19: Conduits for Public Health Surveillance

C. Unnithan, J. Hardy, N. Lilley

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The spread of SARS-Covid-19 virus has impacted the world as it continues to raise questions on the long-term impacts. With the absence of historic/big data sets, digital public health surveillance measures are informed via modelling using real-time data, which is collected and validated by public health agencies; and also aggregated/merged with self/open reported data by the public, via mobile apps and social media channels. This chapter informs on such conduits (using two case studies: Australia and Canada) that enabled AI-based solutions for informing public health strategies. Blue tooth technology used in contact tracing apps seems to allay privacy concerns to an extent, in both countries. Real-time streamed data collection to train predictive models and combining AI methods with active learning seems to be the way forward.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
EditorsK.C. Santosh , Amit Joshi
Place of PublicationSingapore
PublisherSpringer Science and Business Media Deutschland GmbH
Chapter2
Pages9-17
Number of pages9
Edition1
ISBN (Electronic)978-981-15-9682-7
ISBN (Print)978-981-15-9681-0
DOIs
Publication statusPublished - 12 Dec 2020

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume60
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

Keywords

  • Artificial intelligence
  • Australia
  • Canada
  • Covid-19
  • Nowcasting
  • Public health

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