Login / Signup

What can we learn from the dynamics of the Covid-19 epidemic ?

Michel Peyrard
Published in: Chaos (Woodbury, N.Y.) (2023)
We investigate the mechanisms behind quasi-periodic outbursts on the Covid-19 epidemics. Data for France and Germany show that the patterns of outbursts exhibit a qualitative change in early 2022, which appears in a change in their average period and which is confirmed by the time-frequency analysis. This provides a signal that can be used to discriminate among several mechanisms. Two main ideas have been proposed to explain periodicity in epidemics. One involves memory effects and another considers exchanges between epidemic clusters and a reservoir of population. We test these two approaches in the particular case of the Covid-19 epidemics and show that the "cluster model" is the only one that appears to be able to explain the observed pattern with realistic parameters. The last section discusses our results in the context of early studies of epidemics, and we stress the importance to work with models with a limited number of parameters, which moreover can be sufficiently well estimated, to draw conclusions on the general mechanisms behind the observations.
Keyphrases
  • coronavirus disease
  • sars cov
  • respiratory syndrome coronavirus
  • electronic health record
  • machine learning
  • heat stress
  • water quality