General SIR model for visible and hidden epidemic dynamics
1Institute of Hydromechanics, National Academy of Sciences of Ukraine, Kyiv, Ukraine.
Frontiers in Artificial Intelligence
|March 11, 2025
Summary
A new SIR model simulates hidden epidemic dynamics, accurately predicting pertussis waves in England. This approach aids in understanding and forecasting infectious disease spread.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Infectious Disease Dynamics
Background:
- Asymptomatic and unregistered cases significantly impact epidemic dynamics.
- Accurate simulation and prediction models are crucial for public health interventions.
Purpose of the Study:
- To propose a general SIR (Susceptible-Infectious-Recovered) model for simulating hidden epidemic dynamics.
- To simplify parameter identification through analytical solutions for differential equations.
Main Methods:
- Developed a novel general SIR model incorporating asymptomatic and unregistered individuals.
- Derived analytical solutions for the system of differential equations.
- Simulated two waves of the pertussis epidemic in England (2023-2024) assuming zero hidden cases.
Main Results:
- The model accurately predicted accumulated and daily pertussis case numbers.
- The duration of the second epidemic wave was also predicted with high accuracy.
- Projected achievement of pre-outbreak case levels (9 new cases/month) by May 2025 if current trends persist.
Conclusions:
- The proposed SIR model effectively simulates and predicts epidemic behavior, including pertussis.
- The approach offers a valuable tool for public health planning and disease surveillance.
- Analytical solutions enhance the practicality of parameter identification in epidemiological models.
Keywords:
SIR modelhidden epidemic dynamicsmathematical modeling of infection diseasesparameter identificationpertussis epidemic in EnglandMore Related Videos
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