Chaos theory in the understanding of COVID-19 pandemic dynamics.

The chaos theory, a field of study in mathematics and physics, offers a unique lens through which to understand the dynamics of the COVID-19 pandemic. This theory, which deals with complex systems whose behavior is highly sensitive to initial conditions, can provide insights into the unpredictable and seemingly random nature of the pandemic's spread. In this review, we will discuss some literature data with the aim of showing how chaos theory could provide valuable perspectives in understanding the complex and dynamic nature of the COVID-19 pandemic.

The chaos law is a principal driver of natural selection: A proposition on the evolution of recently emerged coronaviruses.

Here we propose that viruses emerging in the human population undergo an evolution that is conditioned by the rules of chaos. Our data support the notion that the initial growth rate "r" affects the chances of the virus to establish a long-lasting relationship with the new host. Indeed, an emerging virus is able to spread and adapt only when it displays an initial r falling in a range frankly associated with chaotic growth.

On the intrinsic nature of viral pathogenesis: The assumption of a Darwinian paradigm to describe COVID-19 pandemic.

Our hypothesis about evolution of the COVID-19 pandemic foresees an inverse relation between infectivity (R0) and lethality (L) of SARS-CoV-2. The above parameters are driven by a continuing mutation process granting the virus a clear survival advantage over virulence. For interpreting this relation we adopted a simple equation, R0 × L k, by which R0 and L depend upon a constant k, that corresponds to an intrinsic property of the viral species involved.