  Countries highly exposed to incoming traffic from China were expected to be
at the highest risk of COVID-19 spread. However, COVID-19 case numbers
(infection levels) are negatively correlated with incoming traffic-level.
Moreover, infection levels are positively correlated with population-size,
while the latter should only affect infection-level once herd immunity is
reached. These could be explained if a low-virulence strain (LVS) began
spreading a few months earlier from China, providing immunity from the later
emerging known SARS-CoV-2 high-virulence strain (HVS). We find that the
dynamics of the COVID-19 pandemic depend on the LVS and HVS spread
doubling-times and the delay between their initial onsets. We find that LVS
doubling-time to be $T_L\sim1.59\pm0.17$ times slower than the HVS ($T_H$), but
its earlier onset allowed its global wide-spread to the levels required for
herd-immunity. In countries exposed earlier to the LVS and/or having smaller
population-size, the LVS achieved herd-immunity earlier, allowing less time for
the spread of the HVS, and giving rise to lower HVS-infection levels. Such
model accurately predicts a country's infection-level ({\rm R^{2}=0.74};
p-value of {\rm 5.2\times10^{-13}}), given only its population-size and
incoming-traffic from China. It explains the negative correlation with
incoming-traffic ($c_{exp}$), the positive correlation with the population size
(n_{pop}) and their specific relations (${\rm N}_{{\rm cases}}\propto
n_{pop}^{{\rm T_{L}/{\rm T_{H}}}}\times c_{exp}^{{\rm T_{L}/{\rm T_{H}-1}}}$).
We find that most countries should have already achieved herd-immunity. Further
COVID-19-spread in these countries is limited and is not expected to rise by
more than a factor of 2-3. We suggest tests/predictions to further verify the
model and biologically identify the LVS, and discuss the implications.
