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Duration of a minor epidemic
William Tritch1, Linda J S Allen1
1Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA.
Infectious Disease Modelling
|March 7, 2019
Summary
This study provides new formulas for understanding minor disease outbreaks in epidemic models. These findings help predict epidemic duration and case counts, crucial for public health interventions.
Area of Science:
- Epidemiology
- Mathematical Biology
- Stochastic Processes
Background:
- Stochastic SIR epidemic models classify outbreaks as minor or major.
- Whittle's 1955 work established probabilities for minor/major epidemics.
- Minor epidemics are characterized by shorter durations and fewer cases than major ones.
Purpose of the Study:
- To derive analytical formulas approximating the probability density, mean, and higher-order moments for the duration of minor epidemics.
- To extend these findings to various stochastic epidemic models.
- To provide a foundation for numerical computation in complex models.
Main Methods:
- Derivation of analytical formulas for minor epidemic duration moments.
- Application to single-infected class SIR, SIS, and SIRS models.
- Numerical computation using multitype branching processes and backward Kolmogorov equations for complex models.
Main Results:
- Analytical approximations for minor epidemic duration probability density, mean, and moments.
- Demonstrated applicability across SIR, SIS, and SIRS models.
- Identified that minor epidemics become more common and longer when the transmission rate approaches one.
Conclusions:
- The derived formulas offer valuable insights into the duration of minor epidemics.
- These results are applicable to a range of stochastic epidemic models.
- Understanding minor epidemic dynamics is essential for effective disease control strategies.
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