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International Conference on Mathematical Modeling in Epidemiology and Public Health

📅 15–16 May 2027 📍 Rome, Italy 👤 Standard / Listener

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$165

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Supporting global researchConnect with researchers across 30+ countries

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Conference session tracks

Key research areas covered across the sessions — tap a track to read more.

This track focuses on the development and application of mathematical models to understand the dynamics of infectious diseases. Contributions may include novel modeling approaches, simulations, and analyses that inform public health interventions.

This session will explore advanced statistical techniques used in the analysis of epidemiological data. Topics may include survival analysis, regression models, and Bayesian approaches tailored for public health research.

This track emphasizes the role of computational methods in public health research, including simulations and algorithm development. Participants are encouraged to present studies that leverage computational tools to enhance health systems and policy-making.

This session will address optimization methods applied to improve health system performance and resource allocation. Contributions may focus on operational research, decision-making frameworks, and efficiency assessments in healthcare delivery.

This track invites discussions on the application of data analytics techniques in epidemiology. Topics may include big data, machine learning, and predictive modeling to derive insights from health data.

This session will cover methodologies for assessing and managing risks associated with public health threats. Contributions may include quantitative risk assessment models and frameworks for decision-making in health policy.

This track focuses on the integration of biostatistical methods with mathematical modeling to study disease dynamics. Participants are encouraged to present research that bridges statistical theory and practical applications in epidemiology.

This session will explore the interplay between population dynamics and health outcomes through mathematical modeling. Contributions may include studies on demographic changes, migration patterns, and their implications for public health.

This track will highlight the use of simulation techniques to model complex epidemiological scenarios. Participants are invited to share innovative simulation frameworks that enhance understanding of disease spread and intervention strategies.

This session will focus on the role of mathematical modeling in predicting the outcomes of public health policies. Contributions may include case studies and theoretical frameworks that inform effective health interventions.

This track will explore cutting-edge developments in applied mathematics that impact public health and epidemiology. Participants are encouraged to present novel mathematical approaches and their applications in real-world health challenges.