论文标题
印度多个地区的Covid-19的流行参数
Epidemic parameters for COVID-19 in several regions of India
论文作者
论文摘要
据报道，在2020年4月，印度不同地理区域的公开时间序列和死亡的贝叶斯分析。发现最初的明显快速生长素感染可能部分是由于混杂因素，例如初始疾病监测的快速升高。简要讨论了如果忽略了这种可能性，会出现的谬论。 4月10日之后的增长与时间独立但依赖于区域的指数一致。由此，使用已知病例和死亡提取R0。在许多情况下，这两个估计值在许多情况下是一致的。对于这些CFR。可以看出，CFR和R0一起增加。讨论了这一观察结果的一些公共卫生影响，包括如果医疗设施保持足够的话，则需要增加目标间隔。
Bayesian analysis of publicly available time series of cases and fatalities in different geographical regions of India during April 2020 is reported. It is found that the initial apparent rapid growthin infections could be partly due to confounding factors such as initial rapid ramp-up of disease surveillance. A brief discussion is given of the fallacies which arise if this possibility is neglected. The growth after April 10 is consistent with a time independent but region dependent exponential. From this, R0 is extracted using both known cases and fatalities. The two estimates are seen to agree in many cases; for these CFR is reported. It is seen that CFR and R0 increase together. Some public health implications of this observation are discussed, including a target doubling interval if medical facilities are to remain adequate.
