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Unit of Biomathematics (UBM)

Unit of Biomathematics (UBM)

Unit of Biomathematics (UBM)

Published on: 27 November 2025

The UBM is a strategic hub dedicated to the development, testing, and application of quantitative tools to understand and address complex challenges within biological systems. It brings together multidisciplinary expertise in mathematical and statistical modeling, data analysis, population dynamics, and the optimization of agricultural and health systems. Its activities include the design, testing, and validation of predictive models for agricultural productivity, forest production, forest or species population dynamics, and the study of interactions between environmental factors and human health. 

The unit also develops mathematical approaches to support the sustainable management of natural resources. The UBM works closely with national and international partners to integrate field data, digital innovations, and operational needs. It also contributes to advanced training for students and early-career researchers through supervision, specialized workshops, and the dissemination of innovative biomathematical tools.

Fields of Activities and Research

  • Development and testing of mathematical tools applied to Agronomy, Forestry, Health, and Environment
  • Mathematical and statistical modeling of infectious disease dynamics
  • Evaluation of the impact of pharmaceutical and non-pharmaceutical interventions on infectious disease transmission
  • Advanced statistical modeling of biological systems
  • Spatio-temporal analysis in agriculture, public health, and environmental sciences
  • Modeling of population dynamics and epidemics
  • Artificial intelligence and machine learning applied to agro-environmental and health data
  • Predictive modeling for productivity assessment
  • Mathematical epidemiology and modeling of emerging diseases
  • Optimization of agricultural production systems
  • Modeling of ecosystem services and biodiversity
  • Data science applied to sensors, drones, and remote sensing
  • Quantitative assessment of climate change impacts
  • Bioeconomy and modeling for sustainable natural resource management
  • Numerical simulation