• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Media coverage and hospital notifications: correlation analysis and optimal media impact duration to manage a pandemic

tetano

Editor, Senior Moderator
J Theor Biol. 2015 Nov 12. pii: S0022-5193(15)00536-6. doi: 10.1016/j.jtbi.2015.11.002. [Epub ahead of print]
[h=1]Media coverage and hospital notifications: correlation analysis and optimal media impact duration to manage a pandemic.[/h] Yan Q[SUP]1[/SUP], Tang S[SUP]1[/SUP], Gabriele S[SUP]2[/SUP], Wu J[SUP]3[/SUP].
[h=3]Author information[/h]

[h=3]Abstract[/h] News reporting has the potential to modify a community's knowledge of emerging infectious diseases and affect peoples' attitudes and behavior. Here we developed a quantitative approach to evaluate the effects of media on such behavior. Statistically significant correlations between the number of new hospital notifications, during the 2009 A/H1N1 influenza epidemic in the Shaanxi province of China, and the number of daily news items added to eight major websites were found from Pearson correlation and cross-correlation analyses. We also proposed a novel model to examine the implication for transmission dynamics of these correlations. The model incorporated the media impact function into the force of infection, and enhanced the traditional epidemic SEIR model with the addition of media dynamics. We used a nonlinear least squares estimation to identify the best-fit parameter values in the model from the observed data. We also carried out the uncertainty and sensitivity analyses to determine key parameters during early phase of the disease outbreak for the final outcome of the outbreak with media impact. The findings confirm the importance of responses by individuals to the media reports, with behavior changes having important consequence for the emerging infectious disease control. Therefore, for mitigating emerging infectious diseases, media publicity should be focused on how to guide people's behavioral changes, which are critical for limiting the spread of disease.
Copyright ? 2015. Published by Elsevier Ltd.


[h=4]KEYWORDS:[/h] A/H1N1; Basic reproduction number; Behaviour change; Correlation analysis; Media report; SEIR model

PMID: 26582723 [PubMed - as supplied by publisher]
 
Back
Top Bottom