Table 1.
Model parameter summary.
Fig 1.
Epidemiological dynamics under interventions to block infection.
Initially, infections rise exponentially (though national COVID-19 testing programs were also ramping up). During stringent intrvention and effective cessation of viral transmission, between t0 and t1, infection decays exponentially with a half-life of t½ = ln(2)/r0, where r0 is derived from the slope of the ln-transformed infection data. This provides a minimal estimate for the value of parameter δ, assuming partial intervention efficacy (0<η<1). This decay will decelerate reaching a lower steady state. Infections will naturally rebound upon lifting of interventions and/or loss of vaccine efficacy with a doubling time of t2 = ln(2)/r and r also calculated from the exponential up-slope. The system will converge with damped oscillations to an elevated infection steady state. This basic pattern will recur as interventions are deployed at different times. Parameter values: σ = 104 S∙wk-1, β = 10−5 V-1∙wk-1, δ = 0.64∙wk-1, η = 70%, t0 = 16, t1 = 28.
Fig 2.
A) COVID-19 case levels for 10 nations with no or ineffective interventions increased nearly-exponentially then spontaneously stabilized around 100 cases per km2 built area. B) The Republic of South Africa and Armenia exhibit cycling infection dynamics with spontaneous orbits around a setpoint of approximately 100 cases per km2 built area for 24 months. Data are normalized to built-up area to account for density effects in infection rates.
Fig 3.
COVID-19 positive confirmed cases between February 2020 and September 2021.
Data are normalized to built-up area to account for density effects in infection rates. On this scale the recurring patterns become apparent. The exponential decay during lockdowns and following vaccination is clear, as are the geometric rebound trajectories. On this scale the recurring patterns in COVID-19 community diffusion kinetics are undoubtedly evident. Shaded areas indicate the duration of aggressive interventions such as social lockdowns.
Fig 4.
COVID-19 positive confirmed cases in ten US states conforming to inclusion criteria from February 2020 to September 2021.
More rural and less dense populations have lower COVID-19 infection rates, in general. Data are normalized to built-up area to account for density effects in infection rates.
Fig 5.
COVID-19 positive confirmed cases for Australia and New Zealand from February 2020 to September 2021.
The strict "Zero COVID" policies implemented for 35 months kept infection levels at low rates but they rebounded when restrictions were lifted and achieved levels similar to those in Europe. Shaded areas indicate the duration of aggressive interventions. Data are normalized to the built-up area to account for density effects in infection rates.
Table 2.
COVID-19 kinetic characteristics in countries with no effective interventions.
Table 3.
Optimized COVID-19 model parameter values.
Fig 6.
Logistic curves for first five waves of COVID-19 in Israel and the number of weeks each waves took to run its course.