The spread of diseases, both communicable and non-communicable, is a major global concern that affects morbidity and mortality rates worldwide. Mathematical modeling has become an increasingly important tool in understanding the dynamics of disease transmission and evaluating the effectiveness of interventions. At the population level, mathematical models can help predict the spread of infectious diseases and the impact of various control measures, such as vaccination, lock-down or quarantine. At the cellular level, mathematical models can provide insight into the behavior of individual cells and their interactions in disease processes, such as cancer growth and progression. The COVID-19 pandemic has highlighted the critical need for mathematical modeling to inform public health policies and improve health outcomes. In this context, the development of mathematical models that incorporate both population-level and cellular-level factors can provide a more comprehensive understanding of disease dynamics and inform the design of more effective interventions.
Mathematical modeling can help in understanding the dynamics of disease transmission and progression, identifying risk factors, and evaluating the effectiveness of various intervention strategies. It can also aid in the development of new diagnostic and treatment methods. At the population level, mathematical models can be used to predict the spread of infectious diseases and mitigation strategies. They can also be used to estimate the burden of chronic diseases, such as diabetes and cancer, and assess the cost-effectiveness of different prevention and treatment strategies.
At the cellular level, mathematical models can be used to study the dynamics of cellular processes and interactions involved in disease progression. For example, models can be developed to study the behavior of cancer cells and their interaction with the immune system. They can also be used to predict the efficacy of different chemotherapy regimens and optimize treatment protocols.
There are several types of mathematical models, for example, deterministic, stochastic, and agent-based models, each with its own unique strengths and limitations. Our Research Topic welcomes all types of mathematical and computational models that focus on disease dynamics and encourage authors to submit original research articles that explore new research directions. To maintain the highest standards of quality, our journal follows the Frontiers review guidelines, which require a rigorous peer review process. To maintain the highest standards of quality, our journal follows the Frontiers review guidelines, which require a rigorous peer review process. The purpose of this process is to ensure that all submitted manuscripts are thoroughly evaluated by expert reviewers to ensure that they meet the highest scientific standards. This approach ensures that high-quality manuscripts can be published efficiently while maintaining scientific integrity.
In general, articles covering the following topics are the primary focus of publication on this platform:
- Infectious disease dynamics and control
- Non-infectious disease dynamics and control
- Vector-borne disease transmission and control
- Food-borne disease
- Public health
- Data-driven models
- Virus dynamics models
- Molecular and cellular mathematical models
- Qualitative analysis (Equilibria and stability, phase space analysis, bifurcation, chaos, existence/non-existence of periodic solutions)
The spread of diseases, both communicable and non-communicable, is a major global concern that affects morbidity and mortality rates worldwide. Mathematical modeling has become an increasingly important tool in understanding the dynamics of disease transmission and evaluating the effectiveness of interventions. At the population level, mathematical models can help predict the spread of infectious diseases and the impact of various control measures, such as vaccination, lock-down or quarantine. At the cellular level, mathematical models can provide insight into the behavior of individual cells and their interactions in disease processes, such as cancer growth and progression. The COVID-19 pandemic has highlighted the critical need for mathematical modeling to inform public health policies and improve health outcomes. In this context, the development of mathematical models that incorporate both population-level and cellular-level factors can provide a more comprehensive understanding of disease dynamics and inform the design of more effective interventions.
Mathematical modeling can help in understanding the dynamics of disease transmission and progression, identifying risk factors, and evaluating the effectiveness of various intervention strategies. It can also aid in the development of new diagnostic and treatment methods. At the population level, mathematical models can be used to predict the spread of infectious diseases and mitigation strategies. They can also be used to estimate the burden of chronic diseases, such as diabetes and cancer, and assess the cost-effectiveness of different prevention and treatment strategies.
At the cellular level, mathematical models can be used to study the dynamics of cellular processes and interactions involved in disease progression. For example, models can be developed to study the behavior of cancer cells and their interaction with the immune system. They can also be used to predict the efficacy of different chemotherapy regimens and optimize treatment protocols.
There are several types of mathematical models, for example, deterministic, stochastic, and agent-based models, each with its own unique strengths and limitations. Our Research Topic welcomes all types of mathematical and computational models that focus on disease dynamics and encourage authors to submit original research articles that explore new research directions. To maintain the highest standards of quality, our journal follows the Frontiers review guidelines, which require a rigorous peer review process. To maintain the highest standards of quality, our journal follows the Frontiers review guidelines, which require a rigorous peer review process. The purpose of this process is to ensure that all submitted manuscripts are thoroughly evaluated by expert reviewers to ensure that they meet the highest scientific standards. This approach ensures that high-quality manuscripts can be published efficiently while maintaining scientific integrity.
In general, articles covering the following topics are the primary focus of publication on this platform:
- Infectious disease dynamics and control
- Non-infectious disease dynamics and control
- Vector-borne disease transmission and control
- Food-borne disease
- Public health
- Data-driven models
- Virus dynamics models
- Molecular and cellular mathematical models
- Qualitative analysis (Equilibria and stability, phase space analysis, bifurcation, chaos, existence/non-existence of periodic solutions)