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Modelling the effects of media during an influenza epidemic
Shannon Collinson and Jane M Heffernan
Author Affiliations
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BMC Public Health 2014, 14:376 doi:10.1186/1471-2458-14-376
Published: 17 April 2014
Abstract (provisional)
Background
Mass media is used to inform individuals regarding diseases within a population. The effects of mass media during disease outbreaks have been studied in the mathematical modelling literature, by including 'media functions' that affect transmission rates in mathematical epidemiological models. The choice of function to employ, however, varies, and thus, epidemic outcomes that are important to inform public health may be affected.
Methods
We present a survey of the disease modelling literature with the effects of mass media. We present a comparison of the functions employed and compare epidemic results parameterized for an influenza outbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemic measurements, and a sensitivity analysis is completed in order to gain insight into which model parameters have the largest influence on epidemic outcomes.
Results
Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemic outcomes are different for each media function.
Conclusion
Different functions used to represent the effects of media during an epidemic will affect the outcomes of a disease model, including the variability in key epidemic measurements. Thus, media functions may not best represent the effects of media during an epidemic. A new method for modelling the effects of media needs to be considered.
full article
http://www.biomedcentral.com/content/pdf/1471-2458-14-376.pdf
Shannon Collinson and Jane M Heffernan
Author Affiliations
For all author emails, please log on.
BMC Public Health 2014, 14:376 doi:10.1186/1471-2458-14-376
Published: 17 April 2014
Abstract (provisional)
Background
Mass media is used to inform individuals regarding diseases within a population. The effects of mass media during disease outbreaks have been studied in the mathematical modelling literature, by including 'media functions' that affect transmission rates in mathematical epidemiological models. The choice of function to employ, however, varies, and thus, epidemic outcomes that are important to inform public health may be affected.
Methods
We present a survey of the disease modelling literature with the effects of mass media. We present a comparison of the functions employed and compare epidemic results parameterized for an influenza outbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemic measurements, and a sensitivity analysis is completed in order to gain insight into which model parameters have the largest influence on epidemic outcomes.
Results
Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemic outcomes are different for each media function.
Conclusion
Different functions used to represent the effects of media during an epidemic will affect the outcomes of a disease model, including the variability in key epidemic measurements. Thus, media functions may not best represent the effects of media during an epidemic. A new method for modelling the effects of media needs to be considered.
full article
http://www.biomedcentral.com/content/pdf/1471-2458-14-376.pdf