Immunity to COVI-19 from Crossen’s perspective
COVID-19 has continued to create havoc and instill fear among most people in America and the whole world. On the 13th April, the New York Times published an article detailing how the immune system responds to the COVID-19 virus. The report demonstrates that due to scarcity of available data on the new strain of coronavirus, decision-makers who rely on science to inform policies construct a conceptual model that will provide assumptions of how the immune system might work (Lin et al., 2020). The model is solely based on scanty information available and facts about related viruses.
As Cynthia puts it in her book, sponsored studies have become America’s most potent and popular tool of persuasion, as much of what most people learn from them is false. Regarding the COVID-19 publication, constructing a model that will predict the variability of immune responses during the pathogenesis of the disease will require an enormous amount of data for the algorithm used to learn and make proper predictions accurately. The public will believe predictions made by the model regarding immune profiling. Still, much of it might be false, as many variables come into play to facilitate an immune response, ranging from patient’s genetic difference, environmental pressure, and health status.
The New York Times publication further elaborates on dynamics involved in cases of COVID-19 re-occurrence. Theories put forth regarding this phenomenon in South Korea because these patients had a false negative test in the middle of an ongoing infection or the infection had temporarily subsided, the re-emerged. To confidently provide a reliable scientific explanation to the re-occurrence of the diseases requires a systematic analysis of how the immune response changes over time (Pal et al., 2020). Since the pandemic came to effect as from December 2018, it is incorrect to extrapolate results observed in other viruses to the COVID-19 case, as viruses mutate over time as an adaptive technique. Much more research should be done to make such conclusions.
References
Lin, Q., Zhao, S., Gao, D., Lou, Y., Yang, S., Musa, S. S., Wang, M. H., Cai, Y., Wang, W., Yang, L., & He, D. (2020). A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China, with individual reaction and governmental action. International Journal of Infectious Diseases, 93(February), 211–216. https://doi.org/10.1016/j.ijid.2020.02.058
Pal, D., Ghosh, D., Santra, P. K., & Mahapatra, G. S. (2020). Mathematical Analysis of a COVID-19 Epidemic Model by using Data-Driven Epidemiological Parameters of Diseases Spread in India. MedRxiv, 2020.04.25.20079111. https://doi.org/10.1101/2020.04.25.20079111
https://www.nytimes.com/2020/04/13/opinion/coronavirus-immunity.html