BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Nathaniel Osgood DTSTART:20230629T170000Z DTEND:20230629T180000Z DTSTAMP:20260424T101157Z UID:ToposInstituteColloquium/103 DESCRIPTION:Title: Towards Compositional System Dynamics for Public Health \nby Nathaniel Osgood as part of Topos Institute Colloquium\n\n\nAbstr act\nFor decades\, System Dynamics (SD) modeling has served as a prominent \, diagram-centric methodology used for public health modeling. Much of it s strength arises from its versatile use of 3 types of diagrams\, with eac h serving both to elevate transparency across the interdisciplinary teams responsible for most impactful models\, and to reason about patterns of sy stem behavior. Causal loop diagrams (CLDs) are used in semi-qualitative pr ocesses early in the modeling process and seek to support insight into fee dback structure\, behavioral modes\, and leverage points. As modeling pro ceeds\, system structure diagrams further distinguish stocks (accumulation s) from flows and material from informational dependencies. Stock & flow d iagrams build on that representation to characterize mathematical dependen cies\, quantify parameters and initial values for stocks\, and have been p articularly widely used in scenario simulation in public health and mathem atical epidemiology. While ubiquitous use of diagrams renders SD modeling markedly effective in supporting team science and shaping stakeholders’ mental models\, existing tools suffer from a number of shortcomings. The se include poor support for modularity\, cumbersome and obscurant model st ratification\, and an inability to capture the relationships between the 3 diagram types. Within this talk\, we describe initial progress towards cr eating a framework for compositional System Dynamics\, including theory\, API support via StockFlow.jl within AlgebraicJulia\, and ModelCollab -- a real-time collaborative tool to support interdisciplinary teams in modular ly building\, composing and flexibly analyzing Stock & Flow diagrams. Our approach separates syntax from semantics\, and characterizes diagrams usin g copresheaves with a schema category. Diagram composition draws on the th eory of structured cospans and undirected wiring diagrams\, and employs pu llbacks for model stratification. Model interpretation is achieved via fun ctorial semantics\, with ordinary differential equations being just one of several semantic domains supported. After describing the current state of implementation\, we describe plans for future work\, including enriching support for CLDs\, and adding support for several computational statistics algorithms and additional types of structurally-informed model analyses. This is joint work with John Baez\, Evan Patterson\, Nicholas Meadows\, S ophie Libkind\, Alex Alegre and Eric Redekopp.\n LOCATION:https://researchseminars.org/talk/ToposInstituteColloquium/103/ END:VEVENT END:VCALENDAR