Abstract
Recurrent outbreaks of the influenza virus continue to pose a serious health threat all over the world. The role of mass media becomes increasingly important in modeling infectious disease transmission dynamics since it can provide public health information that influences risk perception and health behaviors. Motivated by the recent 2009 H1N1 influenza pandemic outbreak in South Korea, a mathematical model has been developed. In this work, a previous influenza transmission model is modified by incorporating two distinct media effect terms in the transmission rate function; (1) a theory-based media effect term is defined as a function of the number of infected people and its rage of change and (2) a data-based media effect term employs the real-world media coverage data during the same period of the 2009 influenza outbreak. The transmission rate and the media parameters are estimated through the least-squares fitting of the influenza model with two media effect terms to the 2009 H1N1 cumulative number of confirmed cases. The impacts of media effect terms are investigated in terms of incidence and cumulative incidence. Our results highlight that the theory-based and data-based media effect terms have almost the same influence on the influenza dynamics under the parameters obtained in this study. Numerical simulations suggest that the media can have a positive influence on influenza dynamics; more media coverage leads to a reduced peak size and final epidemic size of influenza.
Highlights
Biological and social aspects are critical factors in the transmission dynamics of human infectious diseases
Misra et al [7] utilized a simpler model, which divided the S class into being aware and unaware of a disease, based on the SIS model, and concluded that media campaigns are helpful in decreasing the spread of infectious diseases by ensuring that individuals are more cautious of making contact with those that are infected
We propose a mathematical model to investigate the media effects on the influenza transmission dynamics of H1N1 in South Korea, 2009
Summary
Biological and social aspects are critical factors in the transmission dynamics of human infectious diseases. Misra et al [7] utilized a simpler model, which divided the S class into being aware and unaware of a disease, based on the SIS model, and concluded that media campaigns are helpful in decreasing the spread of infectious diseases by ensuring that individuals are more cautious of making contact with those that are infected Another way of representing the media effect in a mathematical model is reducing the transmission rate. Xiao and Ruan [15] adopted a nonmonotonic incidence rate that rapidly decreases as the number of infected individuals increases They considered this as a psychological effect based on the assumption that people tend to reduce the contact rate when there are many infected people in the population. The relationship between media coverage and influenza dynamics is explored
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
