KGR-SKATER: Monthly Respiratory Deaths and Air Quality in California

Modeling results and supporting data for a spatiotemporal procedure applied to monthly time series of respiratory-related deaths across California. The dataset includes surrogate variables for air quality exposure and social deprivation indices used to learn graph and kernel structures. Data and code are available via a linked Dryad repository.

Use Cases

• Benchmarking spatiotemporal forecasting models based on the described KGR-SKATER procedure.
• Analyzing relationships between social deprivation indices and respiratory mortality based on the graph structure mentioned.
• Studying the impact of air quality exposure on health outcomes using the constructed surrogate variables.
• Testing integrated nested Laplace approximation (INLA) for high-dimensional non-Gaussian data as described.

Strengths

• Data and code are openly available via a Dryad repository link.
• Model results are validated against reference models for in-sample and out-of-sample fit.
• The dataset is small (5.5 KB), facilitating quick download and inspection.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The description is focused on the modeling procedure; the specific data content is not detailed.

Provenance

Source

Author Jeffrey Wu, shared via figshare.

Collection Method

Likely contains processed results from modeling monthly respiratory deaths, using social deprivation indices and air quality measures.

Freshness

Last updated 2026-05-21 07:31:24; freshness should be verified.

Geography

California, USA.