Page 118 - ITU Journal, Future and evolving technologies - Volume 1 (2020), Issue 1, Inaugural issue

ITU Journal on Future and Evolving Technologies, Volume 1 (2020), Issue 1

of detection and false alarms. The idea is to use possibly
disparate wireless data streams for data collection, then
1000
integrate this data to improve coverage, reduce probabil-
900
800 ities of errors and false alarms and create a susceptibility
graph that could be used for intelligent testing. Based
num of cumulative infections 600 on this susceptibility graph, we show how to develop
700
efficient sequential learning based algorithms in order
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to minimize the spread of the virus infection. Another
contribution is that we develop provably optimal algo-
400
300
observable Markov decision processes. In particular, we
policy 1
200 no tracing rithmic solutions that rely upon the theory of partially
policy 2 with p = 0.02
b show that current contact tracing plus testing strategies
100 policy 2 with p = 0.2
b
policy 2 with adaptive p that are aimed at identifying (and testing) individuals
b
0 50 100 150 with the highest probability of infection are inefficient.
days
Instead, we find that it is better to test those individuals
Fig. 2 – Simulation of the spreading of the virus under different whose expected impact on virus spread is the highest.
tracing policies. We formulate the testing problem as a Partially Observ-
which is approximately the entire population. Even able Markov Decision Process whose goal is to minimize
a simple contact tracing technique such as Policy 1, the expected spread of the virus subject to testing ca-
reduces the total infections to 617 (which is a 37% pacity constraints. We provide efficient algorithmic so-
reduction). Thus, it is worth the effort to establish lutions to this problem and show via numerical results
a system that can track the contacts of the people that our solution substantially reduces the spread of the
in order to better detect the infections. virus.
• Compared to Policy 1 that only considers the con- ACKNOWLEDGEMENT
tacts with confirmed infected people, Policy 2 also
takes contacts with untested (but probable to be This work was supported in part by NSF grants CNS-
infected) people into account, and hence it has a 1618520 and CNS-2028547.
better performance. This is clearly demonstrated
in its superior performance in all of the three ex- REFERENCES
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expected-to-shrink-by-3-this-year.
Policy 2 with adaptive values of is a good option

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• If we are to use only contact tracing and quarantine tracing protocol. https://github.com/ROBERT-
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6. CONCLUSION
[6] CDC. How to protect yourself & others. https:
In this paper, we have provided a detailed blueprint on //www.cdc.gov/coronavirus/2019-ncov/preven
how to contain the spread of a pandemic by integrating t-getting-sick/prevention.html.
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