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The cross-scale correlations between individuals and nations in COVID-19 mortality
Lei Zhang1, Yu-Rong She1, Guang-Hui She1
1Institute of Health System Engineering, College of Engineering, Peking University, Beijing, China.
Scientific Reports
|August 16, 2022
Summary
Understanding COVID-19 mortality variations is key. This study reveals logistic laws and identifies median age and bed occupancy as crucial factors, predicting a 38.5% death reduction with doubled beds in older populations.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- COVID-19 mortality rates vary significantly across nations.
- Quantifying the medical and social determinants of this variation remains a challenge.
Purpose of the Study:
- To quantitatively model COVID-19 mortality.
- To identify key factors influencing mortality variations.
- To predict future epidemic trends and resource needs.
Main Methods:
- Analysis of COVID-19 mortality data from 54 countries across four waves.
- Application of logistic and power law models.
- Identification of critical thresholds for median age and hospital bed occupancy.
Main Results:
- Mortality temporal evolution follows a logistic law globally.
- A universal linear relationship exists between early mortality growth time and epidemic duration.
- Saturation mortality is power-law dependent on median age (threshold ≈38) and bed occupancy (threshold ≈22%).
Conclusions:
- Median age and hospital bed occupancy are critical thresholds explaining COVID-19 mortality variations.
- Doubling bed capacity could reduce deaths by 38.5% in countries with older populations.
- The developed model enables early prediction of epidemic duration and hospital bed demand for future waves.
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