1. Factor and 6th Polynomial Regression Analyses of COVID19 Data from 35 Countries Reveal 4 Patterns of Epidemic Evolution that Includes up to 4 Sequential Waves
- Author
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Rocha Ad
- Subjects
Polynomial regression ,Mutation rate ,Geography ,Natural selection ,Lineage (genetic) ,Evolutionary biology ,Pandemic ,Formal language ,Mutation (genetic algorithm) ,Covariance - Abstract
COVID Pandemics is now one year old, and virus not only spread across the world but also drastically changes by means of a high mutation rate, many of them appearing simultaneously at different geographic regions. Because of this mutation capacity the virus cannot be considered single entity as proposed current epidemiologic models, but has to be assumed as a fuzzy being that expresses itself as a family of variants, requiring its dynamics to be understood by means of new theoretical approaches and new epidemic data analyses. The purpose of the present paper is to discuss actual knowledge about COVID19 to better model its dynamics and analyze worldwide epidemic data under this point of view. To accomplish this, actual knowledge about the virus genome structure and replication process, as well as about its known mutations are reviewed, resulting in the proposal that: SARS Cov2 evolved from animals and/or other Human CoVs following the rules of natural selection due to its high rate of mutations that transformed its ancestors to better infect humans using ACE2 receptors, simultaneously in many distinct and widely distributed geographic regions, and it continues, nowadays, this kind of evolution across the world, largely independent from human mobility. Therefore, COVID19 concurrently appeared at many different world regions and have not one but multiple concurrent ancestors. Because of this, the theory of Formal Languages is proposed as an adequate tool to model the structure of COVID19 genome; its mutations and actual virus mutational evolution. This model justifies the use of Factor Analysis as a statistical tool to investigate patterns of covariation in a large number of variables and to determine if information may be condensed into small sets of these variables called principal components . Results shows that 4 patterns explain 75% of covariance of the Daily New Cases reported by 35 countries, indicating the existence of 4 worldwide epidemic patterns. 6th Polynomial regression was used to further investigation the national particularities of the epidemics of the different countries associated to each of these patterns. Results suggest that COVID19 high mutational rate creates simultaneously a large number of virus lineages across the world that submitted to natural selection, promotes distinct epidemic evolution in different countries, mostly dictated by the local virus mutational development rather than influenced by foreigner lineage importation. Based on this, actual Pandemic Dogmatic Management based on lockdown; stay home orders and indiscriminate mobility restriction is discussed and alternative solutions are suggested.
- Published
- 2021
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