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.

中文翻译：

---

一位化学工程师对 COVID-19 流行病学的看法


SARS-CoV-2 是一种在全球范围内传播的新型冠状病毒，疫情爆发 3 个月后，世界卫生组织宣布其为大流行病。被称为 COVID-19 的空气传播或表面传播以飞沫/气溶胶形式发生，并且似乎可以通过保持社交距离和佩戴口罩来减少。人口密度、温度、医疗保健系统效率指数和封锁严格指数等人口和地时因素也会影响 COVID-19 流行病学曲线。在本研究中，尝试使用经典的停留时间分布分析将这些因素与曲线特征（均值和方差）联系起来。将连续搅拌釜反应器与特定国家的感染进行类比。本研究考虑了第一波疫情即将结束的 15 个国家的 435 天数据集。利用矩量技术的方法，计算了色散系数。已进行回归分析以将参数与曲线特征联系起来。