A chemical engineer's take of COVID-19 epidemiology

Abstract

SARS-CoV-2, a novel coronavirus spreading worldwide, was declared a pandemic by the World Health Organization 3 months after the outbreak. Termed as COVID-19, airborne or surface transmission occurs as droplets/aerosols and seems to be reduced by social distancing and wearing mask. Demographic and geo-temporal factors like population density, temperature, healthcare system efficiency index and lockdown stringency index also influence the COVID-19 epidemiological curve. In the present study, an attempt is made to relate these factors with curve characteristics (mean and variance) using the classical residence time distribution analysis. An analogy is drawn between the continuous stirred tank reactor and infection in a given country. The 435 days dataset for 15 countries, where the first wave of epidemic is almost ending, have been considered in this study. Using method of moments technique, dispersion coefficient has been calculated. Regression analysis has been conducted to relate parameters with the curve characteristics.