Periodic recurrent waves of Covid-19 epidemics and vaccination campaign

TL;DR

This study analyzes the periodic recurrent waves of Covid-19 using wavelet analysis and a novel 3D helicoid vortex model, highlighting the impact of vaccination and viral mutations on wave dynamics over two years.

Contribution

It introduces a new wavelet-based method and a 3D helicoid vortex model to analyze Covid-19 wave patterns and the effects of vaccination campaigns.

Findings

Main wave period of 120 days identified

Vaccination elongates the recurrence period

Recurrent waves linked to viral mutations and containment measures

Abstract

While understanding of periodic recurrent waves of Covid-19 epidemics would aid to combat the pandemics, quantitative analysis of data over a two years period from the outbreak, is lacking. The complexity of Covid-19 recurrent waves is related with the concurrent role of i) the containment measures enforced to mitigate the epidemics spreading ii) the rate of viral gene mutations, and iii) the variable immune response of the host implemented by vaccination. This work focuses on the effect of massive vaccination and gene variants on the recurrent waves in a representative case of countries enforcing mitigation and vaccination strategy. The spreading rate is measured by the ratio between the reproductive number Rt(t) and the doubling time Td(t) called RIC-index and the daily fatalities number. The dynamics of the Covid-19 epidemics has been studied by wavelet analysis and represented by a non-linear helicoid vortex in a 3D space where both RIC-index and fatalities change with time. The onset of periodic recurrent waves has been identified by the transition from convergent to divergent trajectories on the helicoid vortex. We report a main period of recurrent waves of 120 days and the elongation of this period after the vaccination campaign