tetano
Editor, Senior Moderator
BMC Public Health. 2014 Apr 17;14(1):376. [Epub ahead of print]
Modelling the effects of media during an influenza epidemic.
Collinson S, Heffernan JM.
Abstract
BACKGROUND:
Mass media is used to inform individuals regarding diseases within a population. The effects ofmass media during disease outbreaks have been studied in the mathematical modelling literature, byincluding '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 toinform public health may be affected.
METHODS:
We present a survey of the disease modelling literature with the effects of mass media. We present acomparison of the functions employed and compare epidemic results parameterized for an influenzaoutbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemicmeasurements, and a sensitivity analysis is completed in order to gain insight into which modelparameters have the largest influence on epidemic outcomes.
RESULTS:
Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemicoutcomes are different for each media function.
CONCLUSION:
Different functions used to represent the effects of media during an epidemic will affect the outcomesof a disease model, including the variability in key epidemic measurements. Thus, media functionsmay not best represent the effects of media during an epidemic. A new method for modelling theeffects of media needs to be considered.
PMID:
24742139
[PubMed - as supplied by publisher]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24742139
Modelling the effects of media during an influenza epidemic.
Collinson S, Heffernan JM.
Abstract
BACKGROUND:
Mass media is used to inform individuals regarding diseases within a population. The effects ofmass media during disease outbreaks have been studied in the mathematical modelling literature, byincluding '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 toinform public health may be affected.
METHODS:
We present a survey of the disease modelling literature with the effects of mass media. We present acomparison of the functions employed and compare epidemic results parameterized for an influenzaoutbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemicmeasurements, and a sensitivity analysis is completed in order to gain insight into which modelparameters have the largest influence on epidemic outcomes.
RESULTS:
Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemicoutcomes are different for each media function.
CONCLUSION:
Different functions used to represent the effects of media during an epidemic will affect the outcomesof a disease model, including the variability in key epidemic measurements. Thus, media functionsmay not best represent the effects of media during an epidemic. A new method for modelling theeffects of media needs to be considered.
PMID:
24742139
[PubMed - as supplied by publisher]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24742139