An Interpretable Predictive Model of Vaccine Utilization for Tanzania

  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},
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 Current approaches to vaccine utilization forecasting are based on often outdated population census data, and rely on weak, low-dimensional demand forecasting models.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… 

Figures and Tables from this paper

Predictive Analytics Using Machine Learning to Identify ART Clients at Health System Level at Greatest Risk of Treatment Interruption in Mozambique and Nigeria
Machine-learned models outperformed current classification techniques and showed potential to better direct health worker resources toward patients at greatest risk of loss to follow-up (LTFU) and wider application.
A feasibility study proposal of the predictive model to enable the prediction of population susceptibility to COVID-19 by analysis of vaccine utilization for advising deployment of a booster dose
A predictive model for predicting the susceptible vaccinated population using generalized vaccination distribution data, daily vaccination rate, and vaccine type, in conjunction with a recurrent neural network for predicted the spread of infection in a specific geographic area is proposed.
A Proposed Framework on Integrating Health Equity and Racial Justice into the Artificial Intelligence Development Lifecycle
A framework is proposed to incorporate ethical AI principles into the development process in ways that intentionally promote racial health equity and social justice and may exacerbate structural inequities that can lead to disparate health outcomes.


Return On Investment From Childhood Immunization In Low- And Middle-Income Countries, 2011-20.
Assessment of return on investment associated with achieving projected coverage levels for vaccinations to prevent diseases related to ten antigens in ninety-four low- and middle-income countries during 2011-20, the Decade of Vaccines found that net returns amounted to 44 times the costs.
Simply put: Vaccination saves lives
The impact in the United States of immunization against nine vaccine-preventable diseases, including smallpox and a complication of one of those diseases, congenital rubella syndrome, showing representative annual numbers of cases in the 20th century compared with 2016 reported cases.
Vaccine Wastage Assessment After Introduction of Open Vial Policy in Surat Municipal Corporation Area of India
The implementation of the open vial policy (OVP) in Surat city has led to a significant lowering in the vaccine wastage, leading to savings due to lower vaccine requirements.
Classification and regression trees
  • W. Loh
  • Computer Science
    WIREs Data Mining Knowl. Discov.
  • 2011
This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Random Forests
Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
A forecast model for pharmaceutical requirements based on an artificial neural network
A support tool for the demand forecast management of local pharmacies based on the forecast of the requirements obtained through the implementation of a Radial Basis Function (RBF) neural network is introduced.
fastai: A Layered API for Deep Learning
This paper has used this library to successfully create a complete deep learning course, which was able to write more quickly than using previous approaches, and the code was more clear.