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Research Article |

An Adaptive Representational Explanation of COVID-19’s Evolution

The outbreak of the SARSCoV-2 (COVID-19) virus in 2019 heralded the beginning of a global epidemic. In the past three years, the virus has mutated significantly at least five times, each time creating new variants that pose unprecedented challenges to human survival and adaptation. Through long-term replication and bidirectional selection founded on the environment, the evolution of the virus strains from Alpha, Beta, Gamma, Delta to Omicron and a series of variants, reflecting their increasing ability of adaption to the environment. Its biological adaptation instinct enables its mutated strains to continuously evade the protection of vaccines in the process of evolution, and the toxicity is gradually weakened, so that the virus can adapt to the physical environment of the host (human or animal) to the greatest extent, and can coexist for a long time. Using adaptive characterization as the explanation method, it is shown that virus is an adaptive agent and its variation is the result of adaptive process. As a basic explanatory framework, adaptive representation reflects the essential operating mechanism of various functional systems.This method can well explain the changes in human immunity and the changes in understanding of the novel coronavirus, and also reflects the interpretation role of adaptive representation in biological variation, conceptual change and theoretical replacement, which can use adaptive representation to better understand the changes in the material structure of the virus and the evolutionary means based on environmental adaptability.

COVID-19, Viral Mutation, Environment, Host, Adaptive Representation

APA Style

Li, R., Wei, Y. (2023). An Adaptive Representational Explanation of COVID-19’s Evolution. Social Sciences, 12(6), 294-302.

ACS Style

Li, R.; Wei, Y. An Adaptive Representational Explanation of COVID-19’s Evolution. Soc. Sci. 2023, 12(6), 294-302. doi: 10.11648/

AMA Style

Li R, Wei Y. An Adaptive Representational Explanation of COVID-19’s Evolution. Soc Sci. 2023;12(6):294-302. doi: 10.11648/

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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