APREA – Applied Probability Research in Eastern Africa
Applied Probability Research in Eastern Africa (APREA) is a regional research group focused on using applied probability and statistics to address problems in health, economics and the environment.
The network has included researchers from the University of Nairobi, Kenyatta University, the Technical University of Kenya, Makerere University, Kyambogo University and Eduardo Mondlane University. Its principal collaborating institutions in Sweden have been KTH Royal Institute of Technology and Linköping University.
APREA was supported by the International Science Programme (ISP) through 2025.
Selected publications
The publications below are records in the CoRE-Math publication dataset explicitly reported under APREA.
2024
Abade, E., et al. (2024). A Collaborative Approach to Advancing Research and Training in Public Health Data Science – Challenges, Opportunities and Lessons Learnt. Frontiers in Public Health. DOI: 10.3389/fpubh.2024.1474947
Aognon, S. B., Tonnang, H. E. Z., Ngare, P., Kiplangat, B. K., Abelman, S., & Herr, J. K. (2024). Optimizing microbe-infected mosquito release: a stochastic model for malaria prevention. Frontiers in Applied Mathematics and Statistics. DOI: 10.3389/fams.2024.1465153
Baranon, M. D., Weke, P., Alladatin, J., Ale, B. M., & Lang’at, A. K. (2024). Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Applied and Computational Mathematics. DOI: 10.11648/j.acm.20241304.11
Baranon, M. D., Weke, P., Alladatin, J., & Ale, B. M. (2024). Markov modeling on dynamic state space for genetic disorders and infectious diseases with mutations: Probabilistic framework, parameter estimation, and applications. Computational and Mathematical Biophysics. DOI: 10.1515/cmb-2024-0005
Baranon, M. D., Weke, P., Alladatin, J., & Ale, B. M. (2024). Modeling the Progression of Genetic Disorders and Infectious Diseases with Mutations by Extended Markov Processes on Dynamic State-Space: A Probabilistic Perspective. Research in Mathematics. DOI: 10.28919/cmbn/8497
Candia, D. A., Weke, P., Muhua, G., & Manene, M. (2024). A multi-level analysis of help-seeking behaviour of male victims of intimate partner violence. Sri Lanka Journal of Applied Statistics. DOI: 10.4038/sljas.v25i1.8121
Kiche, J., Mwaniki, I., Orowe, I., & Weke, P. (2024). Classification of Pneumonia, Tuberculosis and Covid-19 from Chest X-ray Images Using Convolution Neural Network Model. International Journal of Statistics and Probability. DOI: 10.5539/ijsp.v13n4p42
Langat, K. K., Waititu, A. G., & Ngare, P. O. (2024). Modified XGBoost Hyper-Parameter Tuning Using Adaptive Particle Swarm Optimization for Credit Score Classification. Machine Learning Research. DOI: 10.11648/j.mlr.20240902.15
Mandia, A. N., Weke, P., & Mung’atu, J. (2024). Measuring multivariate negative dependence in higher dimensions using copula-based approach. Universal Journal of Applied Mathematics. DOI: 10.13189/ujam.2024.120202
Opondo, R., Bundi, D., & Weke, P. (2024). Modelling and Forecasting Unemployment Trends in Kenya Using Advanced Machine Learning Techniques. American Journal of Theoretical and Applied Statistics. DOI: 10.11648/j.ajtas.20241306.16