An autonomous compartmental model for accelerating epidemics.
Nazmi Burak Budanur1,2, Björn Hof2
1Max Planck Institute for the Physics of Complex Systems (MPIPKS), Dresden, Germany.
Plos One
|July 18, 2022
Summary
The COVID-19 epidemic accelerated in Fall 2020 due to testing capacity limits, not just time-dependent factors. This led to more undetected cases, increasing the effective reproduction rate and underestimating epidemic spread in standard models.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- Rapid increases in COVID-19 cases and effective reproduction rates were observed in Europe in Fall 2020.
- Epidemic acceleration is typically attributed to time-dependent factors like travel, seasonality, or pathogen mutations.
Purpose of the Study:
- To investigate if epidemic acceleration can be explained by the exhaustion of public health capacity limits.
- To develop a compartmental model that incorporates testing and contact tracing capacity limits.
Main Methods:
- Utilized a time-independent, autonomous compartmental model.
- Incorporated capacity limits for testing and contact tracing into the model.
- Analyzed data from Austria as a case study.
Main Results:
- The model demonstrated that epidemic acceleration coincides with the exhaustion of mitigation efforts.
- An increasing fraction of undetected cases drives the effective reproduction rate higher.
- Standard models without capacity limits systematically underestimate the effective reproduction rate.
Conclusions:
- Testing and contact tracing capacity limits are critical factors in epidemic dynamics.
- Models must account for these limits to accurately estimate epidemic spread and reproduction rates.
- This approach provides a more realistic understanding of COVID-19 acceleration during periods of high case incidence.
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