Spatio–Temporal Methods in Environmental Epidemiology with R (2nd edition)

This edition: Includes new chapter on data science Updated material on measurement error, deterministic modeling, infectious diseases, preferential sampling Introduces modern computational methods, including INLA, together with code for implementation Represents major new direction in environmental epidemiology Full color throughout Underscores increasing need to consider dependencies in both space and time when modeling epidemiological data. Students learn how to identify and model patterns in spatio-temporal data as well as exploit dependencies over space and time to reduce bias and inefficiency.