Reducing SARS-CoV-2 infectious spreading patterns by removing S and R compartments from SIR model equation

Telles, C. R.

This research points to the asymptotic instability of SIR model and its variants to predict the behavior of SARS-CoV-2 infection spreading patterns over the population and time aspects. Mainly for the S and R terms of the equation, the predictive results fail due to confounding environment of variables that sustain the virus contagion within population complex network basis of analysis. While S and R are not homologous data of analysis, thus with improper topological metrics used in many researches, these terms leads to the asymptotic feature of I term as the most stable point of analysis to achieve proper predictive methods. Having in its basis of formulation the policies adopted by countries, I therefore presents a stable fixed point orientation in order to be used as a predictive analysis of nearby future patterns of SARS-CoV-2 infection. New metrics using a Weinbull approach for I are presented and fixed point orientation (sensitivity of the method) are demonstrated empirically by worldwide statistical data.