Probabilistic and Causal Simulation Workflows
Coming soon. (CIEMSS)
Overview
Coming Soon - PyCIEMSS, ChiRho
Target Users:
CIEMSS tools can be used by modelers or researchers who are either bringing their own model or using one readily available, and are interested in using it to ask various questions relevant for supporting decisionmakers. Users may be particularly interested in probabilistic answers to their questions, and are not working in a time-constrained environment (and therefore can work with probabilistic simulation tools that require longer execution time). Users may also be interested in doing causal analysis and asking causal questions about past events, to help inform future policy decisions.
For example, a user may be someone like a modeler at county health department, who has an existing parameterized model and wants to ask various policy-relevant questions.
Features Supported:
Users can use CIEMSS tools to do probabilistic simulations and causal workflows to support policy-relevant questions:
- Bayesian calibration
- Probabilistic simulation (including forecasts)
- Implement interventions
- Counterfactual analysis and estimation of causal impacts of interventions
- Risk based optimization of intervention policies, under uncertainty
- Generate ensemble forecasts
Installation and Configuration Instructions
(please include links to repositories)
Examples
(please include visuals, screenshots of inputs and outputs, etc.)