Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Abstract

The RF classifier emerged as the top-performing model for predicting children in Tanzania who have not received any vaccinations. This comprehensive approach enabled the accurate identification of zero-dose children, highlighting the effectiveness of machine learning in enhancing public health initiatives and optimising vaccination strategies. Using this algorithm can enhance health outcomes and reduce the prevalence of vaccine-preventable diseases in Tanzania.

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