wahisdb

This package accesses and formats veterinary disease data from WOAH WAHIS. As of June 2024, WAHIS disease outbreak data is not available in a format conducive to automatic updates. EHA has an agreement with WOAH to access static data extracts, released via SharePoint, which we process here and upload to a public DoltHub (https://www.dolthub.com/repositories/ecohealthalliance/wahisdb).

In the future, WOAH plans to release a public-facing application program interface (API), which will facilitate automatic data extraction.

Data were last updated from static reports in March 2024.

Database Tables

• wahis_epi_events Summarizes high level event data, where each row is an independent event, as defined by the reporting country. epi_event_id_unique is the generated primary key. This table included hand-curated disease name standardization and taxonomy.
• wahis_outbreaks Detailed location and impact data for outbreak subevents (e.g., individual farms within a larger outbreak event). report_outbreak_species_id_unique is a generated unique primary key. This table can be joined with wahis_epi_events by epi_event_id_unique.
• wahis_six_month_status Disease status by 6-month semester. unique_id is a generated unique primary key.
• wahis_six_month_controls Control measures applied by disease and taxa by 6-month semester. unique_id is a generated unique primary key.
• wahis_six_month_quantitative Aggregated impact data from outbreak events reports AND six monthly reports on 6-month basis. six_month_quantitative_unique_id is a generated unique primary key.
• disease_key Lookup table for cleaning and standardizing disease names. Curated manually with cross reference to the Animal Disease Ontology (ANDO) (http://agroportal.lirmm.fr/ontologies/ANDO/?p=summary)
• taxon_key Lookup table for cleaning and standardizing taxon names. Manually curated.
• schema_table Description of each table within the database.
• schema_fields Description of each field within the database.

Targets

This project uses the {targets} package to create its analysis pipeline. The steps are defined in the _targets.R file and the workflow can be executed by running targets::tar_make().

Repository Structure and Reproducibility

• wahisdb/ contains the dolt database. See Dolt instructions below.
• R/ contains functions used in this analysis.
• wahis-extracts/ contains raw report extracts from WAHIS SharePoint releases. This folder contains archives of older versions. The most recent version is defined within the code pipeline in _targets.R.
• keys/ contains manually-curated lookup tables for disease name and taxon cleaning.

Dolt

• Install and configure the database software, dolt: https://www.dolthub.com/blog/2020-02-03-dolt-and-dolthub-getting-started/
• Install: sudo curl -L https://github.com/dolthub/dolt/releases/latest/download/install.sh | sudo bash
• Provide credentials: dolt config --global --add user.email YOU@DOMAIN.COM and dolt config --global --add user.name "YOUR NAME" Login: dolt login
• Copy key to https://www.dolthub.com/settings/credentials
• Clone the dolt database: dolt clone ecohealthalliance/wahisdb

renv

• This project uses the {renv} framework to record R package dependencies and versions. Packages and versions used are recorded in renv.lock and code used to manage dependencies is in renv/ and other files in the root project directory. On starting an R session in the working directory, run renv::restore() to install R package dependencies.