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Randomness accelerates the dynamic clearing process of the COVID-19 outbreaks in China
Sha He1, Dingding Yan1, Hongying Shu1
1School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, 710119, China.
Mathematical Biosciences
|August 2, 2023
Summary
Randomness in non-pharmaceutical interventions (NPIs) accelerates COVID-19 dynamic clearing. Increased random noise shortens the average time to control outbreaks, demonstrating NPIs
Area of Science:
- Epidemiology
- Mathematical Biology
- Statistical Modeling
Background:
- COVID-19 outbreaks in China were dynamically cleared using strong non-pharmaceutical interventions (NPIs).
- Outbreaks exhibited characteristics of small-scale, clustered events with low peak case numbers.
- Understanding the role of randomness in the dynamic clearing process is crucial.
Purpose of the Study:
- To investigate how randomness influences the dynamic clearing process of COVID-19 outbreaks.
- To quantify the effect of random noise on the speed of outbreak resolution.
- To estimate change points in stochastic control reproduction numbers (SCRNs).
Main Methods:
- Derived an iterative stochastic difference equation based on the stochastic SIR model.
- Calculated the stochastic control reproduction number (SCRN) and estimated change points using Bayesian techniques.
- Computed the mean first passage time (MFPT) during the decreasing phase to assess randomness impact.
Main Results:
- Random noise was found to accelerate the dynamic zeroing process of COVID-19 outbreaks.
- Enhanced randomness is conducive to dynamic zeroing, leading to shorter average clearing times.
- Calculated MFPTs for 26 outbreaks in China were consistent with observed intervention durations.
Conclusions:
- Powerful NPIs effectively reduce infected individuals during the exponential decline phase.
- Increased randomness in interventions can significantly shorten the overall time required for outbreak control.
- The findings support the strategic use of randomness to enhance the efficiency of epidemic control measures.
Keywords:
Change pointData fittingMean first passage timeNewly reported casesStochastic difference modelMore Related Videos
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