A contact tracing SIR model for randomly mixed populations

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health Interventions

Background:

• Contact tracing is crucial for controlling infectious diseases.
• Traditional network models often require unavailable statistical contact data.
• Compartmental models like SIR are standard for epidemic simulation.

Purpose of the Study:

• To present a new SIR model approach for contact tracing.
• To evaluate the impact of contact tracing on epidemic control metrics.
• To assess the influence of tracing coverage and capacity.

Main Methods:

• Adapted a compartmental SIR model with edge dynamics.
• Integrated contact tracing and patient isolation into the model.
• Analyzed the effects on the control reproduction number and infected individuals.

Main Results:

• The model estimates the effectiveness of contact tracing based on coverage and capacity.
• The approach bypasses the need for detailed contact network statistics.
• Demonstrated potential for extension to more complex disease models.

Conclusions:

• The novel approach offers a feasible method for studying contact tracing effectiveness.
• It provides insights into optimizing public health interventions for epidemics.
• The model can be adapted for diseases with latent or asymptomatic phases.