From health and climate data to disease forecasts
GHRtools is a suite of R packages that support climate and health workflows by streamlining health and climate data collection and harmonization, exploratory analysis, Bayesian modelling and forecasting.
Our tools
data4health
- Access, preprocess and aggregate health data at customized spatiotemporal resolutions.
- Use a set of functions to streamline health data pipelines or leverage a user-friendly graphical interface provided as a Shiny app within the package.
clim4health
- Obtain, transform and export climate data including reanalyses, forecasts, hindcasts, and weather stations.
- Apply common transformations of climate data including postprocessing, downscaling, spatiotemporal aggregations, and construct threshold-based vector suitability indicators.
GHRexplore
- Perform exploratory analysis of temporal and spatiotemporal health data including case counts, incidence rates, and covariates.
- Produce high-quality time series, heatmaps, seasonality, bivariate and correlation plots, as well as choropleth maps, with many customization options.
GHRmodel
- A modular and flexible approach to modeling health outcomes using INLA.
- It addresses common challenges when fitting INLA models, including covariate transformations, formula definitions with complex covariate effects, model fitting, diagnostic plots and model statistics.
GHRpredict
- Generate predictions of models fitted with GHRmodel.
- Evaluate the quality of your predictions using out-of-sample statistics, graphical diagnostics and outbreak detection capabilities using cross-validation