Incorporating infectious duration-dependent transmission into Bayesian epidemic models.
Caitlin Ward1, Grant D Brown1, Jacob J Oleson1
1Department of Biostatistics, University of Iowa, Iowa City, Iowa, USA.
Biometrical Journal. Biometrische Zeitschrift
|October 26, 2022
Summary
This study introduces a new method for infectious disease modeling, using infectious duration-dependent transmissibility. This approach improves the estimation of the reproductive number, especially for viral outbreaks like Ebola.
Area of Science:
- Epidemiology
- Mathematical Biology
- Computational Statistics
Background:
- Bayesian compartmental models are crucial for understanding infectious disease dynamics.
- Estimating infectious period duration is challenging due to limited data.
- Current models often use simplistic, biologically implausible assumptions for infectious duration.
Purpose of the Study:
- To develop a novel approach for fitting Bayesian compartmental models.
- To incorporate biologically realistic infectious duration-dependent (IDD) transmissibility.
- To improve the estimation of the time-varying reproductive number.
Main Methods:
- Developed a novel compartmental modeling approach with IDD transmissibility.
- Fixed the infectious period duration to simplify model fitting.
- Evaluated different IDD transmissibility curve functional forms via simulation.
Main Results:
- The proposed IDD transmissibility approach improves estimation of the time-varying reproductive number.
- Simulations demonstrated the effectiveness of various IDD transmissibility curves.
- The method was illustrated using data from the 1995 Ebola Virus Disease outbreak.
Conclusions:
- IDD transmissibility is a more biologically plausible and computationally efficient method for compartmental modeling.
- This approach enhances the accuracy of infectious disease spread predictions.
- The method shows promise for analyzing real-world epidemic data, such as Ebola outbreaks.
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