An Interpretable Predictive Model of Vaccine Utilization for Tanzania

@article{Hariharan2020AnIP,
  title={An Interpretable Predictive Model of Vaccine Utilization for Tanzania},
  author={Ramkumar Hariharan and John C. Sundberg and Giacomo Gallino and Ashley Schmidt and Drew Arenth and Suvrit Sra and Benjamin Fels},
  journal={Frontiers in Artificial Intelligence},
  year={2020},
  volume={3}
}
Providing accurate utilization forecasts is key to maintaining optimal vaccine stocks in any health facility. Current approaches to vaccine utilization forecasting are based on often outdated population census data, and rely on weak, low-dimensional demand forecasting models. Further, these models provide very little insights into factors that influence vaccine utilization. Here, we built a state-of-the-art, machine learning model using novel, temporally and regionally relevant vaccine… 

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