Can Catastrophe Theory explain expansion and contagious of Covid-19?

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Since SARS-Cov-2 started spreading in China and turned into a pandemic disease called Covid-19, many articles about prediction with mathematical model have appeared in the literature. In addition to models in specialized journals, a significant amount of software was made available, presenting with dashboards spreading of the pandemic for each new. These models are solved by computer simulation of traditional exponential models as a representation of the growth of cases and deaths. Some more accurate models are based on existing variations of SIR model (Susceptible, Infected and Recovered). A third class of study is developed in spatial or probabilistic models as a way of forecasting the effect of Covid-19 around the world. Data on the number of positive cases in all countries, show that SARS-Cov-2 shows great resistance even after strategies of lockdown or social distancing. The purpose of this article is to show how the bifurcation theory, known as Catastrophe Theory, can help to understand why Covid-19 expansion rates change so much and even with low values for a longtime trigger contagion quickly and abruptly.

The Catastrophe Theory was conceived by the mathematician René Thom in the 60s with wide applications in works in the 70s. The outbreak of spruce budworm in Canada revealed a very interesting opportunity to test Catastrophe Theory whose explanation for the phenomenon was widely debated in the academic world. Inspired by the same mathematical approach to this phenomenon in Canada in the 1970s, we applied the Catastrophe Theory in the current Covid-19 pandemic. We observed that sudden outbreaks occur when the carrying capacity and the rate of expansion of the virus reach a region of bifurcation on the cusp surface. With actual Covid-19 data obtained from WHO, we fitted the dynamic model using the particle swarm technique and compared the results in the bifurcation plan with the Covid-19 outbreaks in different regions of the world. It is possible in many cases to observe the trajectory of the parameters between limit points in the bistable region and the consequent explosion of cases observed for each country assessed.

Article activity feed

  1. SciScore for 10.1101/2021.01.02.21249133: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.