To the Editor: Dr Thompson and colleagues developed a statistical model to estimate deaths attributable to influenza and respiratory syncytial virus (RSV). We are concerned that their model was inappropriate. When designing a model to attribute causality to deaths, a reasonable initial approach would be to assume that the number of deaths due to a specific virus in any given week was proportional to the number of laboratory reports of that virus in that week. The total number of deaths would be the sum of the contributions from each virus, plus the seasonal background of deaths due to other causes. Similar models have been used successfully to estimate the proportion of gastrointestinal disease attributable to rotavirus and the proportion of bronchiolitis and pneumonia attributable to RSV and other pathogens. Additional terms and factors could be included to account, for example, for improving sensitivity of surveillance over time, but the core of the model would remain linear and additive. An appropriate analysis could use linear regression, a generalized linear model (GLM) with a Poisson error distribution and an identity link, or maximum likelihood for a non-GLM. Instead, Thompson et al used a Poisson model in which the number of deaths increased exponentially with the number of laboratory reports and the effects of each virus (and the seasonal background) on the number of deaths were multiplicative rather than additive. We do not believe that there is plausible justification for fitting such a model to these data.
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