Distributed clustering algorithm for adaptive pandemic control.
Keywords: 
Clustering algorithms.
COVID-19
Privacy.
Tools.
Pandemic
Laplace equations
Issue Date: 
2021
Publisher: 
IEEE
Project: 
info:eu-repo/grantAgreement/AEI/ Proyectos I+D/PID 2019-104958RB-C44/ES/AVANCES EN CODIFICACION Y PROCESADO DE SEÑAL PARA LA SOCIEDAD DIGITAL
ISSN: 
2169-3536
Editorial note: 
This work is licensed under a Creative Commons Attribution 4.0 License.
Citation: 
Insausti, X., Zárraga-Rodríguez, M., Nolasco-Ferencikova, C., & Gutierrez-Gutierrez, J. (2021). Distributed clustering algorithm for adaptive pandemic control. IEEE Access, 9, 160688-160696.
Abstract
The COVID-19 pandemic has had severe consequences on the global economy, mainly due to indiscriminate geographical lockdowns. Moreover, the digital tracking tools developed to survey the spread of the virus have generated serious privacy concerns. In this paper, we present an algorithm that adaptively groups individuals according to their social contacts and their risk level of severe illness from COVID-19, instead of geographical criteria. The algorithm is fully distributed and therefore, individuals do not know any information about the group they belong to. Thus, we present a distributed clustering algorithm for adaptive pandemic control.

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