Flexible Distributed Lag Models for Count Data Using mgcv.

In this tutorial we present the use of R package mgcv to implement Distributed Lag Non-Linear Models (DLNMs) in a flexible way. Interpretation of smoothing splines as random quantities enables approximate Bayesian inference, which in turn allows uncertainty quantification and comprehensive model checking. We illustrate various modeling situations using open-access epidemiological data in conjunction with simulation experiments.

Personal deposited dose and its influencing factors at several Greek sites: an analysis in respect to seasonal and diurnal variations.

The deposited dose in the human respiratory tract and its influencing factors were investigated for 8 urban/suburban locations within Greek cities. A dosimetry model (ExDoM2) was implemented assuming a 24-h exposure scenario to ambient PM whereby regional deposition rates were obtained. Simulations were performed considering three cases (Sahara dust, cold, and warm periods) with seasonal and diurnal variations examining the relative sources and other influencing factors in each case.