As part of the World Class University (WCU) Program, the Department of Statistics at Universitas Diponegoro (UNDIP) successfully hosted a Visiting Lecturer Online session featuring Dr. Olatunji Johnson from the Department of Mathematics, University of Manchester. The event, held on May 20, 2025, via Zoom, attracted more than 200 participants, including students, faculty members, and researchers interested in advanced statistical methodologies for global public health.
In his opening remarks, Dr.Eng. Adi Wibowo, S.Si., M.Kom., Vice Dean of the Faculty of Science and Mathematics, emphasized the critical role of model-based statistics in global public health. He underscored its relevance to data-driven decision-making, highlighting how spatial data analysis enhances the accuracy and effectiveness of healthcare strategies. Dr. Adi also commended the initiative for fostering international academic collaboration, reinforcing UNDIP’s commitment to advancing statistical research.
Moderated by Fariz Budi Arafat, S.Si., M.Stats., the session delved into model-based geostatistics, with a particular emphasis on spatial data analysis for healthcare decision-making. Dr. Johnson presented an engaging lecture covering linear and generalized linear models, Bayesian inference, parametric correlation functions, and spatial statistics. His insights provided a comprehensive understanding of the role of location-based statistical modeling in public health research, emphasizing data sparsity challenges and the ethical importance of honest reporting in statistical modeling.
A highlight of the session was the case study on malaria and Loa loa diagnostic test modeling in Africa, where Dr. Johnson showcased joint modeling techniques to predict safe areas for mass drug administration. He discussed the importance of correlation functions and Bayesian methods, demonstrating the effectiveness of a two-stage strategy for classifying epidemiological regions.
The session concluded with an engaging Q&A, where participants explored practical applications of Integrated Nested Laplace Approximation (INLA) and spatial correlation in epidemiological research. Attendees received certificates of appreciation, and discussions paved the way for future collaborations and upcoming general lecture series. The Department of Statistics at UNDIP remains committed to advancing statistical methodologies and interdisciplinary research through global academic partnerships.