Advances in Mathematical Modelling for Infectious Disease Control and Prevention

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Background

Mathematical modelling and control theory are essential for comprehending and managing the spread of infectious diseases such as HIV, COVID-19, and influenza. These tools enable researchers to simulate transmission dynamics accurately, which is vital for developing effective control policies and informing public health decisions. Recent studies have focused on various aspects of disease spread, leveraging methods like optimal and impulsive control to predict and curb epidemics. However, there remain significant gaps in our understanding of the long-term effects and efficacy of these interventions, particularly in how they interact with public health policies and awareness campaigns.

This Research Topic aims to consolidate recent advancements and foster further research in mathematical modelling and control of infectious diseases. It will explore the incorporation of innovative control strategies into existing models, assess their impact, and measure effectiveness in various public health scenarios. Additionally, it seeks to refine mathematical tools that deal with the unique challenges posed by infectious diseases, improving accuracy in predictions and effectiveness in disease management.

To gather further insights into mathematical models and control mechanisms, we welcome articles addressing, but not limited to, the following themes:

• Infectious disease dynamics and transmission models
• Awareness-based interventions and their impact on disease spread
• Within-host dynamics and inter-host interactions
• Novel mathematical modelling approaches, including fractional calculus and stochastic models
• Population dynamics and impacts on disease transmission
• Theoretical frameworks for understanding basic reproduction numbers and stability
• Implementation of control theories such as impulsive and feedback control
• Development and analysis of numerical schemes for solving control problems
• The role of time-delayed systems in disease modelling
• Methods for sensitivity analysis and model validation using real-world data

Contributions may include theoretical studies, empirical research, and case studies that apply these thematic elements to specific infectious diseases, aiding in the effective deployment of control measures and policy development.

Keywords: Infectious Disease Modeling, Control theory, Transmission Dynamics, Optimal Control, Public Health Policy

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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