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Impact of misinformation in temporal network epidemiology

Published online by Cambridge University Press:  25 April 2019

Petter Holme Open the ORCID record for Petter Holme [Opens in a new window]  and
Luis E. C. Rocha
Petter Holme*
Affiliation:
Institute of Innovative Research, Tokyo Institute of Technology, Tokyo, Japan
Luis E. C. Rocha
Affiliation:
Centre for Business Network Analysis, Department of International Business and Economics, Business School University of Greenwich, London, United Kingdom (e-mail: luis.rocha@gre.ac.uk)
*
*Corresponding author. Email: holme@cns.pi.titech.ac.jp
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Abstract

We investigate the impact of misinformation about the contact structure on the ability to predict disease outbreaks. We base our study on 31 empirical temporal networks and tune the frequencies in errors in the node identities or time stamps of contacts. We find that for both these spreading scenarios, the maximal misprediction of both the outbreak size and time to extinction follows an stretched exponential convergence as a function of the error frequency. We furthermore determine the temporal-network structural factors influencing the parameters of this convergence.

Keywords

computational epidemiologynetwork sciencecomplex networks

Information

Type
Original Article
Information
Network Science , Volume 7 , Issue 1 , March 2019 , pp. 52 - 69
Copyright
© Cambridge University Press 2019 

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