Establishing a Data Science Unit within Burkina Faso's National Observatory of Population Health (ONSP) to Enhance Public Health Decision-Making
Conference
65th ISI World Statistics Congress 2025
Format: IPS Abstract - WSC 2025
Keywords: "big, "data, "population, "statistical
Session: IPS 867 - Big Data and AI Transformations in Emerging Scientific and Population Studies
Monday 6 October 10:50 a.m. - 12:30 p.m. (Europe/Amsterdam)
Abstract
Introduction: Data Science is an interdisciplinary field that uses methods, algorithms and tools to extract knowledge and information from data. It combines aspects of statistics, mathematics, computer science and specific application domains to analyze large and complex data sets. The applications of Data Science are extensive and impact numerous fields, including healthcare, scientific research, and various others. Specifically, it facilitates more informed decision-making, enhances operational processes, fosters the development of new products or services, and addresses complex health challenges. The aim of this communication is to elucidate the process of establishing a Data Science unit within Burkina Faso's Observatoire National de la Santé des Populations (ONSP).
Methods: The key steps in setting up a Data Science unit within the National Observatory of Population Health (ONSP) of Burkina Faso, include data collection and cleaning, data exploration and visualization, statistical analysis, predictive modeling and results evaluation. Data scientists within this unit will use techniques such as machine learning, deep learning, text analysis, data mining, and other methodologies to identify trends, patterns, and hidden insights within population and health data.
Results: The ONSP, an integral component of the National Institute of Public Health (INSP) of Burkina Faso, plays a pivotal role in the collection, analysis, and dissemination of health-related data. The integration of Data Science at the ONSP offers substantial opportunities for improving public health decision-making. By conducting comprehensive needs assessments, assembling a skilled workforce, establishing a suitable technological infrastructure, managing data effectively, fostering collaborative efforts, and developing relevant analytical models, the ONSP will be able to fully exploit the potential of data and provide valuable insights for public health decision-making in Burkina Faso.
Conclusion: By establishing a comprehensible Data Science framework at ONSP, Burkina Faso can enhance its understanding of the health challenges faced by its population, leading to the development of more effective health policies and informed public health decisions. Such initiatives will contribute to the improvement of the overall health and well-being of the population while also strengthening efforts to combat diseases and promote health.