Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods
Pravin Arun Sawant, Sakshi Shantanu Hiralkar, Yogita Purushottam Hulsurkar, Mugdha Sharad Phutane, Uma Satish Mahajan, Abhay Machindra Kudale

TL;DR
This study uses machine learning to predict over-the-counter antibiotic use in rural India and identifies key factors driving this behavior.
Contribution
The study introduces a novel machine learning approach combining XGBoost and Boruta for predicting OTC antibiotic use in rural settings.
Findings
The prevalence of OTC antibiotic use in rural Pune was 35.9%.
XGBoost+Boruta model achieved an AUROC of 0.934 with 7 key predictors.
Key factors include antibiotic use for eye complaints and perception of pharmacy convenience.
Abstract
Over-the-counter (OTC) antibiotic use can cause antibiotic resistance, threatening global public health gains. To counter OTC use, this study used machine learning (ML) methods to identify predictors of OTC antibiotic use in rural Pune, India. The features of OTC antibiotic use were selected using stepwise logistic, lasso, random forest, XGBoost, and Boruta algorithms. Regression and tree-based models with all confirmed and tentatively important features were built to predict the use of OTC antibiotics. Five-fold cross-validation was used to tune the models’ hyperparameters. The final model was selected based on the highest area under the curve (AUROC) with a 95% confidence interval (CI) and the lowest log-loss. In rural Pune, the prevalence of OTC antibiotic use was 35.9% (95% CI, 31.6 to 40.5). The perception that buying medicines directly from a medicine shop/pharmacy is useful,…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAntibiotic Use and Resistance · Data-Driven Disease Surveillance · COVID-19 epidemiological studies
