PTTI Computational Models
Computational Models for Population-wide Testing, Tracing and Isolation
Project maintained by ptti
Hosted on GitHub Pages — Theme by mattgraham
Multi-paradigm modelling modelling in Python
The PTTI software package is designed for running epidemiological models
with interventions. It contains the models used in our technical
SEIR-TTI paper where we show how to do testing and contact tracing in
a compartmental model and our more policy-oriented PTTI paper where
we use it to explore a number of policy scenarios for the UK. The
- Formalism-agnostic: we believe in checking models against each other,
as it’s the best way to understand which models work best in what
circumstances. So we have ordinary differential equation models,
agent-based models, network, and rule-based models.
- Simple configuration: simulations are described in a user-friendly
YAML file (though there is nothing to prevent running them directly
in Python if you wish).
- Interventions: the simulation is stopped at set times or on certain
conditions, parameters are changed, and the simulation continues.
- Parallel execution: simulations can be conducted in parallel using
as many CPUs as are available, and also supports MPI for use in
High-Performance Computing environments.
- Easy extension to other models: we provide an interface definition
that any model implementation with any number of compartments or
states or agents can use to be incorporated into the simulation
machinery. It does have to be written in Python. We’re sorry, it
would have taken too long to make this software in Haskell.
An on-line demo is available for exploring scenarios with interventions
like those in the PTTI paper.
Scaling up epidemiological models with RBM
This is a collection of models as described in our paper,
[Scaling up epidemiological models with rule-based modelling].
They are written in the Kappa language and the models themselves
can be found in the models/ subdirectory of the repository on
the Github. It is also possible to simulate them in your
web browser with the links below: