Distributed and Decentralized State Estimation Applied to Complex Epidemic Networks

  • Anny Verly Department of Electrical Engineering, Universidade Federal de Ouro Preto, Rua 36 n 115, 35931-008, João Monlevade, MG
  • Bruno Otávio Soares Teixeira Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG
Keywords: State Estimation, Distributed Kalman Filter, Large-Scale Systems, Epidemics on Dynamical Networks, Complex Systems


In epidemic models, the traditional approaches assume that each individual has an equal chance, per unit of time, to communicate with each other. In this regard, the use of complex networks can be considered a more realistic approach. Indeed, in epidemic complex networks the contact patterns are taken into account in the study of an epidemic spreading. However, due to the high dimensionality of the state and observation equations, the use of a classical centralized strategy for state estimation is a challenge. For this reason, as a preliminary study, we propose the use of distributed and decentralized information filter in order to overcome this issue. In a numerical example, for a susceptible-infected network, we show that the distributed and decentralized information filter is effective in state estimation as the centralized approach.