  Infectious diseases are a significant threat to human society which was over
sighted before the incidence of COVID-19, although according to the report of
the World Health Organisation (WHO) about 4.2 million people die annually due
to infectious disease. Due to recent COVID-19 pandemic, more than 2 million
people died during 2020 and 96.2 million people got affected by this
devastating disease. Recent research shows that applying individual
interactions and movements data could help managing the pandemic though
modelling the spread of infectious diseases on social contact networks.
Infectious disease spreading can be explained with the theories and methods of
diffusion processes where a dynamic phenomena evolves on networked systems. In
the modelling of diffusion process, it is assumed that contagious items spread
out in the networked system through the inter-node interactions. This resembles
spreading of infectious virus, e.g. spread of COVID-19, within a population
through individual social interactions. The evolution behaviours of the
diffusion process are strongly influenced by the characteristics of the
underlying system and the mechanism of the diffusion process itself. Thus,
spreading of infectious disease can be explained how people interact with each
other and by the characteristics of the disease itself. This paper presenters
the relevant theories and methodologies of diffusion process that can be used
to model the spread of infectious diseases.
