DynODE Framework Wiki

This wiki is intended to provide a slightly more in-depth overview of the DynODE framework, which is a flexible and modular framework for simulating infectious disease dynamics. The framework is designed to be customizable and extensible, allowing users to easily modify and adapt it to their specific needs.

For disease specific implementations of this framework, please refer to DynODE-Models. Which may still be private but may become public in the future.

This wiki aims to cover the following topics:

1. The 4 major DynODE modules
   1. Configuration
   2. Simulation
   3. Inference
   4. Utils
2. The library backend of DynODE
   1. JAX
   2. Chex
   3. Numpyro
   4. Diffrax

Anticpated Applications of models build with DynODE include:

• Peak hospitalization incidence and timing
• Impact of a new variant be (particularly for COVID)
• Impact of H1N1/H3N2/B dominance and/or an antigenic shift
• Regional differences in burden
• Impact of vaccination timing/reformulation/increased uptake

After reading this wiki, I encourage you to check out the examples/ directory, which contains a set of example models of increasing complexity. Slowly building from a simple SIR model, adding seasonality modules, adding more compartments, and even inference capabilities.

After understanding the examples, I encourage you to write your own and put a PR up! We can always use more examples and its a good learning exercise to write your own model using the DynODE framework.

To really jump into the weeds, you can also check out the DynODE-Models where you can find disease specific implementations of the DynODE framework. These models are more complex and may require a deeper understanding of the framework, but they provide a good reference for how to implement more advanced features and functionalities.

Contact Us

For code specific questions reach out to:

Tom Hladish ([email protected]) or Ben Kok Toh ([email protected]) or Michael Batista([email protected])