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Estimates of US influenza-associated deaths made using four different methods
William W Thompson1, Eric Weintraub, Praveen Dhankhar
1Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
Influenza and Other Respiratory Viruses
|May 21, 2009
Summary
Estimating influenza deaths using four models showed similar results, with Poisson regression and rate-difference models providing comparable annual figures. These findings aid in understanding influenza
Area of Science:
- Epidemiology and Biostatistics
- Infectious Disease Modeling
Background:
- Estimating influenza-associated mortality is crucial for public health, yet various methods exist.
- Direct comparative analyses of different influenza death estimation models using US data were lacking.
Purpose of the Study:
- To compare influenza-associated death estimates from four distinct statistical models in the US.
- To summarize the strengths and weaknesses of each influenza mortality estimation model.
Main Methods:
- Utilized US mortality data (1972-2003) and WHO influenza surveillance data.
- Employed four models: rate-difference (peri-season/summer-season), Serfling least squares, Serfling-Poisson regression, and autoregressive integrated moving average (ARIMA).
Main Results:
- Annual influenza death estimates were generally similar and correlated across models.
- Summer-season rate-difference models produced consistently higher estimates.
- Poisson regression models estimated an average of 25,470 annual deaths; peri-season rate-difference models estimated 22,454.
Conclusions:
- Influenza-associated mortality estimates were of comparable magnitudes across models.
- Poisson regression models are suitable for estimating deaths from influenza A and B but need strong surveillance data.
- Simple peri-season rate-difference models are valuable for regions with limited surveillance or complex influenza patterns.
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