Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study (Preprint)

BACKGROUND Cervical cancer ranked as the fourth most common cancer affecting women, contributing to approximately 660,000 new diagnoses and 350,000 fatalities worldwide. Effective early screening has been shown to reduce cervical cancer incidence by up to 80% and prevent over 40% of new cases. OBJECTIVE The aim of this study is to assess a machine learning-based prediction model and identify the key predictors influencing cervical cancer screening uptake among women aged 30–49 in Sub-Saharan Africa. METHODS For this study, a weighted dataset of 33,952 from the 2022 Demographic and Health Survey (DHS) in Ghana, Kenya, Mozambique, and Tanzania was used. STATA version 17 and Python 3.10 were used for data preprocessing and analysis. MinMax and Standard Scalar were applied for feature scaling, and Recursive Feature Elimination (RFE) was used for feature selection. An 80:20 ratio was applied for data splitting. Tomek Links with Random Over-Sampling were used for handling class imbalance. Seven models were selected and trained using both balanced and unbalanced datasets. Model evaluation was performed using ROC-AUC, accuracy, and confusion matrix. RESULTS The proportion of cervical cancer screening in sub-Saharan Africa was 13%, which is lower than reported in previous studies. Random Forest is the best-performing model, achieving an accuracy of 78%, an AUC of 86%, an F1 score of 79%, a recall of 81%, and a precision of 77%. The waterfall plot's SHAP analysis showed that Wealth status, awareness of STIs, HIV testing exposure, age at first sexual intercourse, educational level, residency, smartphone ownership, having a single sexual partner, and previous health status are predictors of cervical cancer screening. CONCLUSIONS Improving education and awareness, expanding access to screening especially in rural areas leveraging both digital health and community-based outreach, integrating screening with other health services, and addressing socioeconomic barriers are recommended strategies to increase cervical cancer screening rates in sub-Saharan Africa.