Statistics and Biostatistics seminar series
Patrick
Brown Room: M3 3127 |
Daily air pollution and mortality
Quantifying the relationship between daily changes in air pollution and short-term effects on mortality and hospitalisations is a complex task with many steps. Air pollution data contains missing values and outliers. Uncertainty in exposures should be reflected in uncertainty in effect sizes. Inference must account for the multitude of factors unrelated to air pollution that can influence mortality. Exposure-response effects are non-linear. Analyses across multiple cities and regions must take into account possible city-level variation in effects.
This talk will describe ongoing work undertaken in under contract from Health Canada to estimate health effects from pollution in 50 Canadian cities. A key feature of the project is the case-crossover model, a form of partial likelihood which adjusts for most changes in time using control days.