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Monitoring real-time transmission heterogeneity from incidence data.
Yunjun Zhang1,2, Tom Britton3, Xiaohua Zhou1,2,4,5
1Department of Biostatistics, School of Public Health, Peking University, Beijing, China.
Plos Computational Biology
|December 1, 2022
Summary
This study introduces a new method to track epidemic transmission heterogeneity in real-time. The findings reveal Omicron
Area of Science:
- Epidemiology
- Mathematical Biology
- Infectious Disease Dynamics
Background:
- Transmission heterogeneity, influenced by host, pathogen, and environmental factors, can lead to superspreading events.
- Existing methods for assessing transmission heterogeneity often rely on unavailable data and ignore temporal trends.
- Understanding real-time heterogeneity is crucial for effective epidemic control.
Purpose of the Study:
- To develop a convenient method for estimating real-time transmission heterogeneity during an epidemic.
- To simultaneously estimate transmission heterogeneity and the effective reproduction number from incidence time series data.
- To assess the performance and robustness of the proposed method.
Main Methods:
- Developed an instant-individual-heterogenous infectiousness model within the branching process framework.
- Jointly characterized infectiousness variation between individuals and over time.
- Validated the model using simulated and real outbreak data, including incidence time series.
Main Results:
- The model accurately estimated overall and real-time transmission heterogeneities for six epidemics.
- Estimates were consistent with existing literature.
- The model demonstrated robustness to under-reporting and serial interval misspecification.
- Analysis of South African data suggested Omicron exhibits greater transmission heterogeneity than Delta.
Conclusions:
- The proposed model provides a reliable approach for real-time estimation of epidemic transmission heterogeneity using incidence data.
- This method offers a valuable tool for monitoring and managing infectious disease outbreaks.
- Findings highlight potential differences in transmission dynamics between COVID-19 variants like Omicron and Delta.
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