An SEI infection model incorporating media impact

Abstract

To study the impact of media coverage on spread and control of infectious diseases, we use a susceptible-exposed-infective (SEI) model, including individuals' behavior changes in their contacts due to the influences of media coverage, and fully investigate the model dynamics. We define the basic reproductive number ?0 for the model, and show that the modeled disease dies out regardless of initial infections when ?0< 1, and becomes uniformly persistently endemic if ?0>1. When the disease is endemic and the influence of the media coverage is less than or equal to a critical number, there exists a unique endemic equilibrium which is asymptotical stable provided ?0 is greater than and near one. However, if ?0 is larger than a critical number, the model can undergo Hopf bifurcation such that multiple endemic equilibria are bifurcated from the unique endemic equilibrium as the influence of the media coverage is increased to a threshold value. Using numerical simulations we obtain results on the effects of media coverage on the endemic that the media coverage may decrease the peak value of the infectives or the average number of the infectives in different cases. We show, however, that given larger ?0, the influence of the media coverage may as well result in increasing the average number of the infectives, which brings challenges to the control and prevention of infectious diseases.

Trending on Social Media: Integrating Social Media into Infectious Disease Dynamics

“…The behaviour modification induced by the media may be introduced as a reduction in the incidence function (via a so-called media function) with the underlying assumption that as the number of infections increases in a population and is reported by mass media, individuals who are susceptible will become more cautious and initiate protective measures which will then decrease their susceptibility. Hence, choices for the media functions are represented by decreasing functions of the number of infected, exposed or hospitalised people (Cui et al 2008;Xiao et al 2013;Sahu and Dhar 2015;Mitchell and Ross 2016;Lu et al 2017). Common choices for these functions are a saturated Holling type-II functional response and an exponentially decreasing functional response as shown in Table 1.…”

Global Stability of Pneumococcal Pneumonia with Awareness and Saturated Treatment

“…Mathematical models that describe the influence of media coverage to inform individuals regarding disease and control in a population have been generalized in the forms of SIS, SIRS, SEI, and SEIR [22][23][24][25]. Media coverage, private individual information, and appropriate treatment have proven to be among control measures undertaken by health institutions and the public to reduce the spread of most infectious diseases.…”

Stochastic dynamics in a delayed epidemic system with Markovian switching and media coverage

“…Finally, it is well known that there is a profound relationship between public health issues and mass media coverage. Media reports can affect individual behaviour during an infectious disease outbreak, thus affecting the transmission of the infectious disease [29][30][31][32][33] and the effects of intervention strategies that are also affected by individual behaviour [34][35][36]. Therefore, it is necessary to consider crucial effects of media coverage on epidemiology dynamics.…”

“…Recently, some delayed stochastic SIR systems have been used to investigate the combined dynamic effects of stochastic fluctuation and time delay on epidemiological dynamics [37][38][39][40][41][42]. Additionally, complex dynamical behaviours caused by media coverage have been investigated in stochastic epidemic systems in [29][30][31][32][33][34][35]43]. To the authors' best knowledge, combined dynamics of Markovian switching and media coverage on stochastic SIR epidemic system have not been investigated before.…”