vaxstats is a powerful tool designed to support statistical forecasting models tailored specifically for vaccine studies.
It provides a robust command-line interface and modular architecture, enabling researchers to efficiently analyze, forecast, and visualize vaccine-related data.
This tool is particularly useful in predicting trends and understanding the impact of vaccines over time.
- Data Preparation: Clean and prepare vaccine-related datasets for analysis.
- Forecasting: Apply statistical forecasting models to predict future trends based on historical data.
- Visualization: Generate insightful visualizations to aid in the interpretation of forecasting results.
- Modular Design: Easily extendable with custom models and analysis routines.
This project was developed as part of OASCI's Scientific Computing Core (SC2) initiative to enhance interdisciplinary computational research. We appreciate contributions and feedback from the broader community.
In particular, we designed and implemented this software in collaboration with the following group(s):
- Dr. Doug Reed in the Center for Vaccine Research at the University of Pittsburgh.
Clone the repository:
git clone https://github.com/oasci/vaxstats.gitInstall vaxstats using pip after moving into the directory.
pip install .This will install all dependencies and vaxstats into your current Python environment.
We use pixi to manage Python environments and simplify the developer workflow.
Once you have pixi installed, move into vaxstats directory (e.g., cd vaxstats) and install the environment using the command
pixi installNow you can activate the new virtual environment using
pixi shellThis project is released under the Apache-2.0 License as specified in LICENSE.md.