论文标题
社区和政策制定者使用的COVID-19-19流行病学模型
A COVID-19 Epidemiological Model for Community and Policy Maker Use
论文作者
论文摘要
在MATLAB/GNU八度范围内开发并实施了Covid-19的流行病学模型，以供公共卫生从业人员，政策制定者和公众使用。该模型区分了该疾病的四个阶段：感染，生病，严重生病和更好。根据对疾病扩散的观察，该模型被初步参数化。该模型与死亡率为1.5％一致。使用该模型的初步模拟表明，在这种病毒的背景下，诸如“牛群免疫”和“扁平曲线”之类的概念具有高度误导性。基于这些概念的公共政策不足以保护人口。仅将病毒的R0降低到1以下是将Covid-19的死亡负担保持在正常季节性流感范围内的有效策略。由于该模型估计的R0值范围从中国以外的2.82范围内到2月下旬至2020年3月上旬的西方世界的3.83，这意味着成功地以大于65％（全球）或75％（西方世界）的有效性与该病毒作斗争。
An epidemiological model for COVID-19 was developed and implemented in MATLAB/GNU Octave for use by public health practitioners, policy makers and the general public. The model distinguishes four stages in the disease: infected, sick, seriously sick, and better. The model was preliminarily parameterized based on observations of the spread of the disease. The model is consistent with a mortality rate of 1.5 %. Preliminary simulations with the model indicate that concepts such as "herd immunity" and "flattening the curve" are highly misleading in the context of this virus. Public policies based on these concepts are inadequate to protect the population. Only reducing the R0 of the virus below 1 is an effective strategy for maintaining the death burden of COVID-19 within the normal range of seasonal flu. As R0 values estimated with the model range from 2.82 worldwide outside of China and 3.83 in the Western world in late February - early March 2020, this means social distancing with effectiveness greater than 65 % (worldwide) or 75 % (Western world) are needed to combat the virus successfully.
