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Media impact switching surface during an infectious disease outbreak.

Xiao Y, Tang S, Wu J - Sci Rep (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, Xi'an Jiaotong University, Xi'an 710049, P. R. China.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Flow diagram to illustrate the infection dynamics during an outbreak.Integrated control measures include contact tracing, quarantine, isolation and vaccination. Media impact is modeled as a factor potentially reducing the transmission rate.
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f1: Flow diagram to illustrate the infection dynamics during an outbreak.Integrated control measures include contact tracing, quarantine, isolation and vaccination. Media impact is modeled as a factor potentially reducing the transmission rate.

Mentions: We investigate a general SIR(susceptible-infective-recovery)-type epidemiological model, which incorporates media impacts and other interventions such as quarantine, isolation, vaccination and treatment. We stratify the usual susceptible (S), infected (I), and recovered (R) compartments in the classical SIR model15, to include the quarantined susceptible (Sq) and isolated infected (Iq) compartments. With contact tracing, a proportion, q, of individuals exposed to the virus is quarantined. The quarantined individuals can either move to compartment Iq or Sq, depending on whether they are infected or not1617, while the remaining proportion, 1 − q, of individuals exposed to the virus, but missed from the contact tracing, move to the infectious compartment I (once infected) or stay in compartment S (if uninfected). Let the media-influenced transmission probability be β and the contact rate be a constant c. Then the quarantined individuals, if infected (or uninfected), move to the compartment Iq (or Sq) at a rate of βcq (or (1 − β)cq). Those who are not quarantined, if infected, will move to the compartment I at a rate of βc(1 − q). The infected individuals can be detected and then isolated at a rate of dI, and can also move to the compartment R due to recovery. The transmission dynamics is illustrated in Fig. 1.


Media impact switching surface during an infectious disease outbreak.

Xiao Y, Tang S, Wu J - Sci Rep (2015)

Flow diagram to illustrate the infection dynamics during an outbreak.Integrated control measures include contact tracing, quarantine, isolation and vaccination. Media impact is modeled as a factor potentially reducing the transmission rate.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4296304&req=5

f1: Flow diagram to illustrate the infection dynamics during an outbreak.Integrated control measures include contact tracing, quarantine, isolation and vaccination. Media impact is modeled as a factor potentially reducing the transmission rate.
Mentions: We investigate a general SIR(susceptible-infective-recovery)-type epidemiological model, which incorporates media impacts and other interventions such as quarantine, isolation, vaccination and treatment. We stratify the usual susceptible (S), infected (I), and recovered (R) compartments in the classical SIR model15, to include the quarantined susceptible (Sq) and isolated infected (Iq) compartments. With contact tracing, a proportion, q, of individuals exposed to the virus is quarantined. The quarantined individuals can either move to compartment Iq or Sq, depending on whether they are infected or not1617, while the remaining proportion, 1 − q, of individuals exposed to the virus, but missed from the contact tracing, move to the infectious compartment I (once infected) or stay in compartment S (if uninfected). Let the media-influenced transmission probability be β and the contact rate be a constant c. Then the quarantined individuals, if infected (or uninfected), move to the compartment Iq (or Sq) at a rate of βcq (or (1 − β)cq). Those who are not quarantined, if infected, will move to the compartment I at a rate of βc(1 − q). The infected individuals can be detected and then isolated at a rate of dI, and can also move to the compartment R due to recovery. The transmission dynamics is illustrated in Fig. 1.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, Xi'an Jiaotong University, Xi'an 710049, P. R. China.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus