2 Getting started

This R targets pipeline for environmental health impact assessment has been developed on R 4.1.2 “Bird Hippie” and RStudio 2021.09.2 “Ghost Orchid”. It requires R >= 4.0.0 and access to the CARDAT platform’s Environment_General data storage folder on Cloud CARDAT.

The structure and syntax of an R targets pipeline may be unfamiliar to you depending on your level of coding experience. Depending on your intended usage, some or all of the following may guide your understanding of the workflow. Links to further useful examples and documentation are provided in the references.

2.1 Initial setup and run-through

To run the Air Health SWS for the first time:

  1. Download and unzip or clone the air-health-sws-r-targets repository from the Code dropdown button.

  2. Load the R project. Open the _targets.R script.

    • _targets.R and config.R scripts are where you customise the workflow to suit your study needs.
    • Define global variables in config.R
      • Set your analysis year and states (location) to set the study coverage – note with the initial data inputs in the pipeline, years are limited to 2010-2015.
      • Set your directory pathway to CARDAT data
        • Set dir_cardat to the correct path (parent directory of the CARDAT Environment_General folder).
    • Line 112 – data extraction and derivation
      • Provide counterfactual scenario(s) and calculate the delta, counterfactual being the alternative air pollution exposure level
        • This can either be an absolute number (e.g. a guideline value such as the WHO guidelines)
        • Or a derived value – e.g. the minimum value from monitoring data.
    • Line 147 – Analysis
      • Input risk estimate:
        • Relative risk, including 95% confidence intervals, uses 1.062 (1.041, 1.084) is the default – as per WHO guidelines

  3. Open the main.R script. (This is not integral to the targets pipeline but is a place to keep all the useful commands for visualising, running and exploring the pipeline outside of the pipeline itself.) Begin running the script line-by-line from the top.

    • On opening the project, RStudio may prompt you to install packages. Alternatively, use the custom installation function install_pkgs() (installs the latest version of the library if it is not already available). This step may take some time.
    • Visualise and examine metadata of the targets pipeline
    • Run the pipeline
    • Examine pipeline outputs

  4. See the results of the desired target with tar_read(target_name).

See Issues for known error codes and troubleshooting.