tetano
Editor, Senior Moderator
Sci Rep. 2015 Jan 16;5:7838. doi: 10.1038/srep07838.
[h=1]Media impact switching surface during an infectious disease outbreak.[/h] Xiao Y[SUP]1[/SUP], Tang S[SUP]2[/SUP], Wu J[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] There are many challenges to quantifying and evaluating the media impact on the control of emerging infectious diseases. We modeled such media impacts using a piecewise smooth function depending on both the case number and its rate of change. The proposed model was then converted into a switching system, with the switching surface determined by a functional relationship between susceptible populations and different subgroups of infectives. By parameterizing the proposed model with the 2009 A/H1N1 influenza outbreak data in the Shaanxi province of China, we observed that media impact switched off almost as the epidemic peaked. Our analysis implies that media coverage significantly delayed the epidemic's peak and decreased the severity of the outbreak. Moreover, media impacts are not always effective in lowering the disease transmission during the entire outbreak, but switch on and off in a highly nonlinear fashion with the greatest effect during the early stage of the outbreak. The finding draws the attention to the important role of informing the public about 'the rate of change of case numbers' rather than 'the absolute number of cases' to alter behavioral changes, through a self-adaptive media impact switching on and off, for better control of disease transmission.
PMID: 25592757 [PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/25592757
[h=1]Media impact switching surface during an infectious disease outbreak.[/h] Xiao Y[SUP]1[/SUP], Tang S[SUP]2[/SUP], Wu J[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] There are many challenges to quantifying and evaluating the media impact on the control of emerging infectious diseases. We modeled such media impacts using a piecewise smooth function depending on both the case number and its rate of change. The proposed model was then converted into a switching system, with the switching surface determined by a functional relationship between susceptible populations and different subgroups of infectives. By parameterizing the proposed model with the 2009 A/H1N1 influenza outbreak data in the Shaanxi province of China, we observed that media impact switched off almost as the epidemic peaked. Our analysis implies that media coverage significantly delayed the epidemic's peak and decreased the severity of the outbreak. Moreover, media impacts are not always effective in lowering the disease transmission during the entire outbreak, but switch on and off in a highly nonlinear fashion with the greatest effect during the early stage of the outbreak. The finding draws the attention to the important role of informing the public about 'the rate of change of case numbers' rather than 'the absolute number of cases' to alter behavioral changes, through a self-adaptive media impact switching on and off, for better control of disease transmission.
PMID: 25592757 [PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/25592757