Journal
CANADIAN JOURNAL OF CHEMICAL ENGINEERING
Volume 101, Issue 3, Pages 1529-1540Publisher
WILEY
DOI: 10.1002/cjce.24557
Keywords
chemical engineering; epidemiological model; mortality rate; SARS-CoV-2
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Chemical engineering plays a crucial role in understanding and combating the COVID-19 epidemic. This study successfully determines the intrinsic mortality rate of COVID-19 during the first wave using a combination of data and approaches, and proposes a mathematical model related to age.
Chemical engineering involves a skill set that is transferrable to a broad range of other areas. A case in point is the work that is being done by chemical engineers to better understand and fight the COVID-19 epidemic. In this study, we consider a problem that has eluded the COVID-19 research community, which is nevertheless very tractable with a chemical engineering mindset: the true or intrinsic mortality rate of COVID-19, that is, the fraction or percentage of COVID-19-infected people that die of the disease. We solve this problem in two locations (Spain and the state of New York) for the epidemic's first wave using a combination of daily death data, a fit of a computer simulation of an epidemiological model with adjustable parameters, and independent results of immunological blood testing on a random sample of the population. Parallels are drawn with the problem of determining the turnover frequency of a catalyst based on a similar combination of data and approaches. It is concluded from the study that the intrinsic mortality rate of COVID-19 was 1.45 +/- 0.45% during the first wave, a number that reflects OECD countries. By incorporating data on the age dependence of the mortality rate, a relationship f(mort) = (3.0 +/- 0.7) x 10(-5) exp(0.1a), where a is the age in years, is tentatively put forward for the mortality rate as a fraction.
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