Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics

Raj Dandekar; Shane G Henderson; Hermanus M Jansen; Joshua McDonald; Sarat Moka; Yoni Nazarathy; Christopher Rackauckas; Peter G Taylor; Aapeli Vuorinen

Journal article

Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics

Raj Dandekar, Shane G Henderson, Hermanus M Jansen, Joshua McDonald, Sarat Moka, Yoni Nazarathy, Christopher Rackauckas, Peter G Taylor, Aapeli Vuorinen

PATTERNS | ELSEVIER | Published : 2021

DOI: 10.1016/j.patter.2021.100220

Download PDF

Abstract

Viral spread is a complicated function of biological properties, the environment, preventative measures such as sanitation and masks, and the rate at which individuals come within physical proximity. It is these last two elements that governments can control through social-distancing directives. However, infection measurements are almost always delayed, making real-time estimation nearly impossible. Safe Blues is one way of addressing the problem caused by this time lag via online measurements combined with machine learning methods that exploit the relationship between counts of multiple forms of the Safe Blues strands and the progress of the actual epidemic. The Safe Blues protocols and tec..

View full abstract

University of Melbourne Researchers

Peter Taylor Author Mathematics and Statistics

Grants

Awarded by Australian Research Council (ARC)

Awarded by ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)

Awarded by Army Research Office

Awarded by National Science Foundation

Funding Acknowledgements

We thank additional members of the Safe Blues team for fruitful discussion and preparations toward the campus experiment. These include Azam Asanjarani, Keng Chew, Kirsty Short, and Ilze Ziedins. We thank James McCaw, Tom Stace, Yoav Banin, and Yun William Yu for insights. We thank Toshali Banerjee for help with illustrations. We also thank two anonymous referees for helping improve the quality of this paper. H.M.J. and Y.N. are supported by the Australian Research Council (ARC) under grant no. DP180101602. S.M. and P.G.T. are supported by the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) under grant no. CE140100049. S.G.H. is supported by the Army Research Office under grant no. W911NF-17-1-0094 and the National Science Foundation under grant no. TRIPODS+X DMS-1839346.