Using Laboratory Data to Aid Early Warning in Prospective Influenza Mortality Surveillance
PDF

How to Cite

Moa, A. M., Muscatello, D. J., Turner, R., & MacIntyre, C. R. (2016). Using Laboratory Data to Aid Early Warning in Prospective Influenza Mortality Surveillance. Online Journal of Public Health Informatics, 8(1). https://doi.org/10.5210/ojphi.v8i1.6557

Abstract

Many countries prospectively monitor influenza-attributable mortality using a variation of the Serfling seasonal time series model. Our aim is to demonstrate use of routine laboratory-confirmed influenza surveillance data to forecast predicted influenza-attributable deaths during the current influenza season. The two models provided a reasonable forecast for 2012. The model forecasts of weekly deaths during 2012 were compared against observed deaths using root mean squared error (RMSE). The results shown that the model including influenza type A and B provided a better fit. Here, we demonstrated a time series model for influenza-attributable mortality surveillance based on laboratory surveillance information.

https://doi.org/10.5210/ojphi.v8i1.6557
PDF
Authors own copyright of their articles appearing in the Online Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes. Share-alike: when posting copies or adaptations of the work, release the work under the same license as the original. For any other use of articles, please contact the copyright owner. The journal/publisher is not responsible for subsequent uses of the work, including uses infringing the above license. It is the author's responsibility to bring an infringement action if so desired by the author.