climasus4r offers a complete ecosystem of tutorials for researchers in environmental epidemiology and public health. Explore the five tracks below — each one leads to a dedicated hub with in-depth tutorials.
9-Stage Pipeline Track
From importing DATASUS data to epidemiological modeling. Each stage corresponds to a phase of the integrated health, climate, and environment pipeline — follow them in order to build your complete pipeline.
Explore Track → 8 tutorialsAdvanced Modeling (sus_mod_*)
DLNM, attributable burden, case-crossover, multi-city pooling, machine learning, Bayesian spatial models, and SWOT vulnerability analysis. Recommended prerequisite: Stage 9 of the Track.
Explore Modeling → 8 tutorialsThematic Tutorials
Introductory tutorial, INMET data and ML-based gap filling, bioclimatic indices, climate-health aggregation strategies, heatwaves and cold waves. Perfect for deepening specific skills.
Explore Thematic → 4 case studiesCase Studies in Climate Epidemiology
Complete pipelines with real DATASUS + INMET data: pediatric respiratory mortality (SIM-DO), dengue in the Northeast (SINAN), cardiovascular mortality in older adults and heatwaves, hospitalizations and cold waves in the South (SIH).
View Case Studies → 3 tutorialsReproducible Analytical Pipelines (sus_rap_*)
Export, share, and re-run analyses as Reproducible Analytical Pipelines. Covers export, integration with targets, YAML recipes, a Shiny GUI, and full project scaffolding.