论文标题
锁定是否遏制了19009年感染率在印度的传播:数据驱动的分析
Did the lockdown curb the spread of COVID-19 infection rate in India: A data-driven analysis
论文作者
论文摘要
为了分析印度执行三个连续的全国性锁定的有效性,我们对四个关键参数进行了数据驱动分析,从而降低了传输速率,限制了增长率,使流行曲线变平并改善了医疗保健系统。通过考虑四个不同的指标,即繁殖率,生长速率,倍增时间和死亡与恢复率来量化这些。在印度分析了COVID-19的发病率数据(在2020年3月2日至2020年5月31日)中爆发,以最佳拟合流行曲线,利用指数级增长,最大似然估计,顺序贝叶斯方法和时间依赖时间依赖的生殖。最佳拟合(基于考虑的数据)是用于时间依赖的方法。因此,该方法用于评估对有效繁殖率的影响。锁定3结束前的锁定期间,有效繁殖率的降低了45美元\%$。在同一时期,增长率从锁定前的$ 393 \%$降低到锁定3后的$ 33 \%$,伴随着平均加倍的时间增加$ 4 $ - $ 6 $ 6 $ 6美元至$ 12 $ - $ 14 $ 14美元。最后,死亡与捕获比率从$ 0.28 $(锁定前)下降到锁定3后的0.08美元。总而言之,所有被认为评估锁定有效性的四个指标,从锁定前的锁定期结束到锁定后的锁定级别分析,从锁定前的锁定期结束。
In order to analyze the effectiveness of three successive nationwide lockdown enforced in India, we present a data-driven analysis of four key parameters, reducing the transmission rate, restraining the growth rate, flattening the epidemic curve and improving the health care system. These were quantified by the consideration of four different metrics, namely, reproduction rate, growth rate, doubling time and death to recovery ratio. The incidence data of the COVID-19 (during the period of 2nd March 2020 to 31st May 2020) outbreak in India was analyzed for the best fit to the epidemic curve, making use of the exponential growth, the maximum likelihood estimation, sequential Bayesian method and estimation of time-dependent reproduction. The best fit (based on the data considered) was for the time-dependent approach. Accordingly, this approach was used to assess the impact on the effective reproduction rate. The period of pre-lockdown to the end of lockdown 3, saw a $45\%$ reduction in the rate of effective reproduction rate. During the same period the growth rate reduced from $393\%$ during the pre-lockdown to $33\%$ after lockdown 3, accompanied by the average doubling time increasing form $4$-$6$ days to $12$-$14$ days. Finally, the death-to-recovery ratio dropped from $0.28$ (pre-lockdown) to $0.08$ after lockdown 3. In conclusion, all the four metrics considered to assess the effectiveness of the lockdown, exhibited significant favourable changes, from the pre-lockdown period to the end of lockdown 3. Analysis of the data in the post-lockdown period with these metrics will provide greater clarity with regards to the extent of the success of the lockdown.