Abstract
Dengue is an arbovirus that has spread throughout different, especially tropical and subtropical, regions of the world. This disease affects humans through mosquito bites. The occurrence of dengue epidemics has increased alarmingly over the last three decades. To detect a pattern regarding the dispersal process of dengue, this research presents a computational model based on three pillars: complex networks, time-varying graphing (TVG), and time-series synchronisation. To establish the synchronisation networks, the Motif-Synchronisation method with TVG was applied to a time series analysis of georeferenced dengue incidence data from the municipalities of Bahia from 2001 to 2016. After applying the model presented in this work, the dispersal behaviour patterns of these epidemics were found amongst the municipalities within Bahia, when synchronised, in epidemic moments. The results indicate that the incidence of dengue is not directly related to the distance between municipalities; rather, a time relation exists regarding the development of the vector and its capacity to transmit disease. The purpose of this model is to contribute to public disease interventions by providing early information.
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