Early Detection of Infant Common Illnesses (0–3 Years): Symptom-Based Dataset from Bangladesh

The data consists of 2,553 responses obtained through a survey from the parents and primary caregivers of the children under the age of three in Bangladesh. It provides detailed demographic information (like age and gender), symptom reports (including respiratory problems, diarrhea, fever, skin rashes, and ear infections), the concerns of caregivers and final names of illnesses. The survey was also designed to capture early markers of frequent infant illnesses, and to reflect observations made in real-world care.

The dataset aims to advance studies on early detection, monitoring and management of common childhood illness. It is a base for public health research, pediatric health studies and decision support systems both for parents and HCP. Moreover, it can be applied to machine learning purposes, such as symptom-based illness prediction and pattern analysis for the pediatric health records. Based on the provision of trustworthy and well-organized information, this dataset hopes to help in the timely diagnosis, intervention, and care of children outcomes in Bangladesh.
Keywords: Infant health; childhood illnesses; symptom dataset; healthcare dataset; machine learning; ARI; diarrhea; fever; Bangladesh