Metadata-Version: 2.4
Name: vaxflux
Version: 0.4.0
Summary: Flexible bayesian models for seasonal vaccine uptake.
Project-URL: Homepage, https://github.com/ACCIDDA/vaxflux
Project-URL: Issues, https://github.com/ACCIDDA/vaxflux/issues
Author-email: Carl Pearson <cap1024@unc.edu>, Joshua Macdonald <jmacdo16@jh.edu>, Timothy Willard <twillard@unc.edu>
License-Expression: MIT
License-File: LICENSE
Keywords: bayesian,epidemiology,forecasting,modeling,public-health,seasonal,time-series,vaccine
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering
Classifier: Typing :: Typed
Requires-Python: <3.15,>=3.11
Requires-Dist: arviz<1.0.0,>=0.19.0
Requires-Dist: jax<0.10.0,>=0.9.2
Requires-Dist: jaxlib<0.10.0,>=0.9.2
Requires-Dist: numpy<3.0.0,>=2.1.0
Requires-Dist: numpyro>=0.20.1
Requires-Dist: pandas<4,>=3.0.0
Requires-Dist: pydantic>=2.12.5
Requires-Dist: requests>=2.32.3
Requires-Dist: scipy>=1.17.1
Requires-Dist: xarray>=2024.7.0
Provides-Extra: demo
Requires-Dist: arviz-plots[matplotlib]>=0.5.0; extra == 'demo'
Requires-Dist: graphviz>=0.21; extra == 'demo'
Requires-Dist: ipykernel>=7.1.0; extra == 'demo'
Requires-Dist: jupyter>=1.1.1; extra == 'demo'
Requires-Dist: matplotlib>=3.10.8; extra == 'demo'
Requires-Dist: nbconvert>=7.16.6; extra == 'demo'
Requires-Dist: seaborn>=0.13.2; extra == 'demo'
Provides-Extra: plot
Requires-Dist: matplotlib>=3.10.8; extra == 'plot'
Description-Content-Type: text/markdown

# `vaxflux` - Seasonal Vaccine Uptake Modeling

`vaxflux` is a python package for modeling seasonal vaccine uptake like
influenza vaccines. It is capable of incorporating arbitrary covariates and
geographic regions, observations at multiple time scales, modeling the effects
of interventions, and more.

## Getting Started

`vaxflux` can either be installed from PyPI:

```bash
uv pip install vaxflux
```

or from source:

```bash
git clone git@github.com:ACCIDDA/vaxflux.git
cd vaxflux
uv sync --locked
```

# Funding Acknowledgement

This project was made possible by cooperative agreement CDC-RFA-FT-23-0069 from
the CDC's Center for Forecasting and Outbreak Analytics. Its contents are solely
the responsibility of the authors and do not necessarily represent the official
views of the Centers for Disease Control and Prevention.
