Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics.

Area of Science:

• Epidemiology
• Mathematical Biology
• Infectious Disease Dynamics

Background:

• Mathematical modeling is crucial for understanding COVID-19 epidemiological dynamics.
• The momentary reproduction ratio r(t) guides public health interventions.
• Understanding disease spread after control measures is vital.

Purpose of the Study:

• Investigate critical fluctuations around the epidemiological threshold.
• Explain the dynamic behavior of COVID-19 spreading post-lockdown.
• Analyze the role of transmission rates and infectivity in epidemic waves.

Main Methods:

• Utilized simple, analytically tractable mathematical models.
• Applied findings to more complex models of COVID-19 epidemics.
• Analyzed epidemic dynamics in both supercritical and subcritical regimes.

Main Results:

• Critical fluctuations can cause new epidemic waves even with stable transmission rates.
• The subcritical regime, not the supercritical one, explains post-lockdown COVID-19 dynamics.
• Small disease import in the subcritical regime is key to understanding spreading patterns.

Conclusions:

• Epidemic dynamics post-lockdown are better explained by the subcritical regime with low import.
• The momentary reproduction ratio hovering around its threshold value is significant.
• This research refines understanding of COVID-19 resurgence post-intervention.