tetano
Editor, Senior Moderator
Epidemiol Infect. 2011 Aug 31:1-5. [Epub ahead of print]
Time-series model to predict impact of H1N1 influenza on a children's hospital.
Spaeder MC, Stroud JR, Song X.
Source
Division of Critical Care Medicine, Children's National Medical Center, Washington, DC, USA.
Abstract
SUMMARYThe spring of 2009 witnessed the emergence of a novel influenza A(H1N1) virus resulting in the first influenza pandemic since 1968. In autumn of 2010, the 2009 novel H1N1 influenza strain re-emerged. We performed a retrospective time-series analysis of all patients with laboratory-confirmed H1N1 influenza who presented to our institution during 2009. Cases of influenza were assembled into 3-day aggregates and forecasting models of H1N1 influenza incidence were created. Forecasting estimates of H1N1 incidence for the 2010-2011 season were compared to actual values for our institution to assess model performance. Ninety-five percent confidence intervals calculated around our model's forecasts were accurate to ?3?6 cases per 3-day period for our institution. Our results suggest that time-series models may be useful tools in forecasting the incidence of H1N1 influenza, helping institutions to optimize distribution of resources based on the changing burden of illness.
PMID:
21878146
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/21878146
Time-series model to predict impact of H1N1 influenza on a children's hospital.
Spaeder MC, Stroud JR, Song X.
Source
Division of Critical Care Medicine, Children's National Medical Center, Washington, DC, USA.
Abstract
SUMMARYThe spring of 2009 witnessed the emergence of a novel influenza A(H1N1) virus resulting in the first influenza pandemic since 1968. In autumn of 2010, the 2009 novel H1N1 influenza strain re-emerged. We performed a retrospective time-series analysis of all patients with laboratory-confirmed H1N1 influenza who presented to our institution during 2009. Cases of influenza were assembled into 3-day aggregates and forecasting models of H1N1 influenza incidence were created. Forecasting estimates of H1N1 incidence for the 2010-2011 season were compared to actual values for our institution to assess model performance. Ninety-five percent confidence intervals calculated around our model's forecasts were accurate to ?3?6 cases per 3-day period for our institution. Our results suggest that time-series models may be useful tools in forecasting the incidence of H1N1 influenza, helping institutions to optimize distribution of resources based on the changing burden of illness.
PMID:
21878146
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/21878146