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International Conference on Mathematical Modeling in Epidemiology and Public Health - (ICMMEPH-27)

15th - 16th April 2027 , Prague - Czech Republic

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Call For Papers

The (ICMMEPH-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Applied Mathematics, Mathematical Modeling are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Mathematical modeling of infectious diseases
  • Statistical methods in epidemiological studies
  • Modeling public health interventions effectiveness
  • Mathematical modeling of vaccination strategies
  • Applications of machine learning in epidemiology
  • Mathematical modeling of disease transmission dynamics
  • Impact of social behavior on disease spread
  • Mathematical modeling of chronic diseases
  • Epidemiological modeling of health systems
  • Mathematical modeling of health disparities
  • Statistical analysis of health data
  • Mathematical modeling of outbreak responses
  • Applications of network theory in epidemiology
  • Mathematical modeling of mental health issues
  • Modeling the impact of environmental factors on health
  • Mathematical modeling of healthcare resource allocation
  • Epidemiological modeling of non-communicable diseases
  • Mathematical modeling of health policy impacts
  • Applications of data science in public health
  • Mathematical modeling of aging populations

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.