ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach

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Year : 2026 | Volume : 3 | 02 | Page :
    By

    Shrutika Bhasme,

  • Ramsa Ansari,

  • Anamika Dhawan,

  1. Research Scholar, MCA Thakur Institute of Management Studies, Career Development & Research, Mumbai, Maharashtra, India
  2. Research Scholar, MCA Thakur Institute of Management Studies, Career Development & Research, Mumbai, Maharashtra, India
  3. Research Scholar, MCA Thakur Institute of Management Studies, Career Development & Research, Mumbai, Maharashtra, India

Abstract

Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated or unvaccinated. Among various algorithms tested—including Logistic Regression, Decision Trees, Support Vector Machines, and Random Forest—the Random Forest classifier demonstrated superior performance with 89.6% accuracy, 0.88 precision, 0.90 recall, and 0.89 F1-score. Feature importance analysis revealed that parental awareness, family income, maternal education level, distance to healthcare centers, and availability of immunization facilities were the most significant predictors. These findings provide actionable, data-driven insights for healthcare policymakers to design targeted interventions aimed at improving immunization rates in underserved rural areas, highlighting the potential of machine learning in strengthening public health strategies through early identification of at-risk children and optimized resource allocation.

Keywords: Machine Learning, Childhood Immunization, Rural India, Predictive Analytics, Random Forest, Healthcare Access

How to cite this article:
Shrutika Bhasme, Ramsa Ansari, Anamika Dhawan. ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach. International Journal of Vaccines. 2026; 03(02):-.
How to cite this URL:
Shrutika Bhasme, Ramsa Ansari, Anamika Dhawan. ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach. International Journal of Vaccines. 2026; 03(02):-. Available from: https://journals.stmjournals.com/ijv/article=2026/view=247683


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Ahead of Print Subscription Review Article
Volume 03
02
Received 08/04/2026
Accepted 28/05/2026
Published 26/06/2026
Publication Time 79 Days
21

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