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Modelling Excess Mortality in Covid-19-Like Epidemics
1Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland.
Entropy (Basel, Switzerland)
|December 8, 2020
Summary
Simulations show that slowing epidemics too much early on increases their duration without significantly reducing long-term deaths. Hybrid lockdown strategies are particularly inefficient for controlling disease spread.
Area of Science:
- Epidemiology
- Computational modeling
- Public health
Background:
- Non-pharmaceutical interventions (NPIs) are crucial for managing epidemics.
- Understanding the impact of NPIs on epidemic dynamics and healthcare capacity is vital.
Purpose of the Study:
- To assess the cumulative deaths from hypothetical COVID-19-like epidemics using an agent-based model.
- To compare various non-pharmaceutical intervention strategies, including social distancing and lockdowns.
Main Methods:
- Development of an agent-based model simulating epidemic spread, ventilator availability, and mortality.
- Modeling local and non-local disease transmission on random geometric networks.
- Utilizing Monte Carlo simulations with parameters reflecting USA and Poland.
Main Results:
- Strategies significantly slowing early epidemic spread do not substantially decrease long-term deaths and prolong the epidemic duration.
- Hybrid strategies involving temporary lockdowns followed by complete release proved inefficient.
- Healthcare system capacity, simulated by ventilator availability, influences mortality outcomes.
Conclusions:
- Aggressive early mitigation may prolong epidemics without commensurate benefits in reducing overall mortality.
- Adaptive or phased NPI strategies require careful consideration to avoid inefficiency.
- Agent-based modeling provides a valuable tool for evaluating public health interventions during epidemics.
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