Forecasting improvements for better reproductive health and family planning operations in global health supply chains

R
Python
Machine Learning
Hybrid Intelligence
Uncertainity
Social Good
2nd year PhD Student, Data Lab for Social Good Research Group, Cardiff Business School, UK
Published

September 27, 2022

My research focuses on addressing inefficiencies in supply chain management for contraceptive products in developing countries. These inefficiencies often lead to shortages, limiting women’s reproductive autonomy and exacerbating societal challenges. By integrating probabilistic forecasting with inventory optimization, I aim to create a novel approach that accounts for uncertainties, poor data quality, and local demand variations. This interdisciplinary project involves collaboration with scholars from Cardiff Business School, the School of Computer Science & Informatics, and the United States Agency for International Development (USAID). The goal is to improve access to contraceptives, reduce unintended pregnancies, and prevent unsafe abortions, ultimately benefiting women, healthcare providers, governments, and donor organizations.

Supervision team

Funder

Welsh Graduate School for the Social Sciences (WGSSS)