Get the News Out Loudly and Quickly: The Influence of the Media on Limiting Emerging Infectious Disease Outbreaks

Abstract

During outbreaks of infectious diseases with high morbidity and mortality, individuals closely follow media reports of the outbreak. Many will attempt to minimize contacts with other individuals in order to protect themselves from infection and possibly death. This process is called social distancing. Social distancing strategies include restricting socializing and travel, and using barrier protections. We use modeling to show that for short-term outbreaks, social distancing can have a large influence on reducing outbreak morbidity and mortality. In particular, public health agencies working together with the media can significantly reduce the severity of an outbreak by providing timely accounts of new infections and deaths. Our models show that the most effective strategy to reduce infections is to provide this information as early as possible, though providing it well into the course of the outbreak can still have a significant effect. However, our models for long-term outbreaks indicate that reporting historic infection data can result in more infections than with no reporting at all. We examine three types of media influence and we illustrate the media influence with a simulated outbreak of a generic emerging infectious disease in a small city. Social distancing can never be complete; however, for a spectrum of outbreaks, we show that leaving isolation (stopping applying social distancing measures) for up to 4 hours each day has modest effect on the overall morbidity and mortality.

Dynamics of an Infectious Disease Where Media Coverage Influences Transmission

“…Vigorous media reporting can have a substantial effect on reducing the impact of an outbreak as public health agencies constant updating of the media about the number of infections as they immediately pass on the information to the general population could result is a dramatic decrease in the severity of the outbreak, see Figure 4. This agrees with the conclusion in [31].…”

“…First, note that other functional types may also be considered for the transition to the Hclass such as an integral operator of the form h(I) = T 0 K(t − u)İ(u)du to capture the delay effects leading to a neutral functional differential system, however, we will not consider it further. One contribution in the direction of studying this area is [31]. The right choice of the kernel K could approximate I or forİ which in the simplest case might just be the source-term τI, which leads us back to the current model.…”

“…Joshi et al [30] model the effect of information campaigns on the HIV epidemic in Uganda and explicitly include a class reflecting the amount of educational information. Mummert and Weiss [31] examined the situation when the media holds back news of an outbreak and only after some time begins to report the disease morbidity and mortality with two types of delays. A model with pulse vaccination has shown that the media can trigger a vaccinating panic if the vaccine is imperfect and simplified messages may result in the vaccinated mixing with infected individuals without regard to disease risk [32].…”

Behavioural change models for infectious disease transmission: a systematic review (2010–2015)

“…[44], Karimi et al [45]—Social DistancingPoletti et al . [46], Mummert & Weiss [47], Zhong et al [48]Larson & Nigmatulina [49], Wang [50], Greer [51], Morin et al . [52], Liu et al .…”

“…[71,77], Kassa & Ouhinou [81], Zhang et al . [44], Mummert & Weiss [47], Zhong et al . [48], Wang [50], Greer [51], Morin et al .…”