A preceding low-virulence strain pandemic inducing immunity against COVID-19

TL;DR

This study proposes that an earlier spreading low-virulence strain of COVID-19 induced herd immunity, explaining unexpected infection patterns and correlations across countries, and provides a predictive model based on strain dynamics and country-specific factors.

Contribution

It introduces a novel model suggesting an early low-virulence strain led to herd immunity, explaining COVID-19 spread patterns and correlations with traffic and population size.

Findings

LVS spread earlier and slower than HVS, enabling herd immunity.

Model predicts infection levels with high accuracy (R^2=0.74).

Most countries likely already achieved herd immunity.

Abstract

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.