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Impact of misinformation in temporal network epidemiology

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  • Holme, Petter
  • Rocha, Luis E. C.

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.

Suggested Citation

  • Holme, Petter & Rocha, Luis E. C., 2019. "Impact of misinformation in temporal network epidemiology," Network Science, Cambridge University Press, vol. 7(1), pages 52-69, March.
    • Handle: RePEc:cup:netsci:v:7:y:2019:i:01:p:52-69_00
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    Cited by:

    1. Zuluaga, Sandra & Oviedo, Sandra & Muñoz, Santiago & Vargas, Luisa, 2023. "Recomendación para una estrategia nacional de pago por resultados," Informes de Investigación 21028, Fedesarrollo.
    2. Nikolaj Horsevad & David Mateo & Robert E. Kooij & Alain Barrat & Roland Bouffanais, 2022. "Transition from simple to complex contagion in collective decision-making," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    3. Obermeier, Tim, 2022. "Individual Welfare Analysis: What's the Role of Intra-Family Preference Heterogeneity?," VfS Annual Conference 2022 (Basel): Big Data in Economics 264101, Verein für Socialpolitik / German Economic Association.

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