Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

The COVID-19 pandemic has resulted in a proliferation of conflicting opinions on physical
distancing across various media platforms, which has had a significant impact on human …

A reservoir computing based echo state network (ESN) is used here for the purpose of
predicting the spread of a disease. The current infection trends of a disease in some …

We investigate epidemic spreading in a deterministic susceptible-infected-susceptible
model on uncorrelated heterogeneous networks with higher-order interactions. We provide …

In this study, an epidemic model for spreading COVID-19 is presented. This model considers
the birth and death rates in the dynamics of spreading COVID-19. The birth and death rates …

Contact tracing is widely adopted to inhibit the epidemics in the global world, and has been
proved to be very effective in reducing infections. But it is rarely investigated whether contact …

Considering that people may change their face-to-face communication patterns with others
depending on the season, we propose an epidemic model that incorporates a time-varying …

We delve into the interplay between network's symmetry and functioning for a generic class
of dynamical systems. Primarily, we focus on a class of systems that characterize the …

The COVID-19 pandemic is the most significant global crisis since World War II that affected
almost all the countries of our planet. To control the COVID-19 pandemic outbreak, it is …

The epidemic threshold of a social system is the ratio of infection and recovery rate above
which a disease spreading in it becomes an epidemic. In the absence of pharmaceutical …