Heterogeneity is an important characteristic that affects the spread of infectious diseases, such as the heterogeneity of people and regions. Drivers and impacts on the biodynamics of heterogeneous infectious diseases and non-infectious diseases, including the spread of infectious diseases, tumors, etc, involve many complex mechanisms, so this heterogeneity may be ignored. For heterogeneous populations, intervention measures based on location or age for high-risk groups can be implemented to improve the efficiency of control strategies. Therefore, it is necessary to develop spatial models, age-structured models, or network models to help understand complicated mechanisms and predict future trends. As a result, understanding the impact of heterogeneity is crucial for policymakers to allocate healthcare resources and design effective control strategies.
The main goal of this Research Topic is to provide a platform to exhibit the research achievements on understanding the impact of heterogeneity, predicting the emergence and re-emergence of infectious diseases, projecting effective treatment strategies for non-infectious diseases, and evaluating the potential risks.
Topics of interest to this collection include but are not limited to:
• The impact of spatial heterogeneity on the transmission dynamics of infectious diseases;
• How age-structure affects the transmission dynamics of infectious diseases;
• Treatment strategies for chronic diseases;
• Targeted vaccination under limited resources;
• How epidemic spreads in complex networks;
• Optimal control strategies.
Heterogeneity is an important characteristic that affects the spread of infectious diseases, such as the heterogeneity of people and regions. Drivers and impacts on the biodynamics of heterogeneous infectious diseases and non-infectious diseases, including the spread of infectious diseases, tumors, etc, involve many complex mechanisms, so this heterogeneity may be ignored. For heterogeneous populations, intervention measures based on location or age for high-risk groups can be implemented to improve the efficiency of control strategies. Therefore, it is necessary to develop spatial models, age-structured models, or network models to help understand complicated mechanisms and predict future trends. As a result, understanding the impact of heterogeneity is crucial for policymakers to allocate healthcare resources and design effective control strategies.
The main goal of this Research Topic is to provide a platform to exhibit the research achievements on understanding the impact of heterogeneity, predicting the emergence and re-emergence of infectious diseases, projecting effective treatment strategies for non-infectious diseases, and evaluating the potential risks.
Topics of interest to this collection include but are not limited to:
• The impact of spatial heterogeneity on the transmission dynamics of infectious diseases;
• How age-structure affects the transmission dynamics of infectious diseases;
• Treatment strategies for chronic diseases;
• Targeted vaccination under limited resources;
• How epidemic spreads in complex networks;
• Optimal control strategies.