论文标题
SARS-COV-2大流行：了解锁定在印度受影响最大的州的影响
SARS-COV-2 Pandemic: Understanding the Impact of Lockdown in the Most Affected States of India
论文作者
论文摘要
SARS-COV-2已阻止了世界的脚步，三分之一的人口被迫留在家里。在这里，我们提出了一项关于印度国家表现的比较研究，以遏制受大流行影响最大的疾病传播。我们是根据2020年3月14日至2020年4月17日收集的数据来做到的。我们通过比较平滑的时间序列和百分比变化以及每日确认案件的变化点检测来做到这一点。我们还讨论了各州在遏制疾病和地面实施方面采用的不同政策和策略。我们开发了Arima（P，D，Q）模型，其中（P，D，Q）是通过最小化AIK（Akaike信息标准）获得的。这些模型用于对该国进行预测，该国表明，到2020年5月7日，印度将拥有约50,237个确认的案件，而增加了11天。在每个州的绩效的基础上，我们认为基于该特定地区的人口统计学的地方一级策略，而不是中央和统一的策略。
SARS-COV-2 has stopped the world in its footsteps and a third of the population has been forced to stay at home. Here we present a comparative study of the performance of states of India, in curbing the spread of the disease, that are most affected by the pandemic. We have done so based on the data collected between 14th March, 2020 to 17th April, 2020. We do this by comparing the smoothened time series and percentage changes along with change point detection of the daily confirmed cases. We also discuss the different policies and strategies adopted by the states in curbing the disease and the ground level implementation. We have developed ARIMA(p,d,q) models where (p,d,q) are obtained by minimising the AIK(Akaike Information Criterion). These models are used to make forecasts for the country which show that by 7th May, 2020, India would have around 50,237 confirmed cases and a doubling rate of 11 days. On the basis of the performance, of each state, we argue that a local level strategy which is based on the demographics of that particular region be developed instead of a central and uniform one.
