Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
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A table of common organisms, i.e. pathogens or other taxa, which is hierarchical in nature.

Diagram of hierarchical nature of organisms


  1. Ask questions of the presence/absence data at more abstract levels than target. For example, we test for Flu_A_H1 and Flu_A_H3 but have cases where we want to aggregate on all Flu A or all Flu.

  2. A place to store details about an organism, such as if it is considered reportable or not, to aid with automated processes.


  1. The data is hierarchical, but we’re in a relational model.

    The standard solution is to support a single parent/child relationship which is walked using “recursive” (actually iterative) queries in SQL and encoded into a view.

  2. We need to pick a taxonomy, and possibly ontology, to use for populating organism records. We likely want to start with a very constrained subset of what’s immediately useful to us, based on what’s most interesting in the existing targets.