Mathematical and Statistical Modeling and Dynamics in Demography, Epidemiology, and Biostatistics

Dear Colleagues,

The increasing availability of complex demographic, epidemiological, and biomedical data, together with advances in mathematical and statistical theory, has created new opportunities and challenges in modeling population dynamics, disease transmission, and health-related processes. Mathematical and statistical models play a crucial role in understanding, predicting, and controlling demographic and epidemiological phenomena, as well as in supporting evidence-based decision-making in public health and social policy.

This Special Issue aims to bring together high-quality original research that advances the theory, methodology, and application of mathematical and statistical modeling in demography, epidemiology, and biostatistics. We particularly welcome contributions that emphasize analytical and computational methods, data-driven modeling, and interdisciplinary approaches bridging mathematics and statistics with the social and health sciences. Applications to real data and theoretical approaches are equally welcome.

Topics of interest include, but are not limited to, the following:

• Mathematical models in population dynamics and demography;
• Epidemiological modeling of infectious and non-infectious diseases;
• Deterministic and stochastic models in epidemiology and biostatistics;
• Statistical inference and estimation for dynamic population models;
• Time-series, longitudinal, and survival analysis in demographic and health data;
• Spatial and spatio-temporal modeling in demography and epidemiology;
• Network-based and agent-based models of disease spread;
• Bayesian and machine learning approaches in various disciplines;
• Optimal control, optimization, and intervention strategies in public health;
• Advances in health economic evaluation;
• Uncertainty quantification and sensitivity analysis in demographic and epidemiological models;
• Model validation, identifiability, and data integration;
• Applications to real-world demographic, epidemiological, or biomedical datasets;
• Forecasting approaches demography, epidemiology, or (health) econometrics;
• Approaches in meta-analysis;
• Nowcast approaches for migration, disease monitoring, or other fields with limited data quality;
• Big data approaches for demography, epidemiology, and biostatistics.

Dr. Patrizio Vanella
Guest Editor

Manuscript Submission Information

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