论文标题
一个动力学模型,用于定性理解和分析印度对控制SARS-COV-2病毒传播的COVID-19疾病所施加的完全锁定的影响
A kinetic model for qualitative understanding and analysis of the effect of complete lockdown imposed by India for controlling the COVID-19 disease spread by the SARS-CoV-2 virus
论文作者
论文摘要
SARS-COV-2病毒引起的目前正在进行的全球大流行正在全球造成严重破坏。没有任何疫苗以及任何确定的药物可以治愈,这使情况变得非常严重。因此,只有少数有效的工具可以包含这种疾病的快速传播速度,称为Covid-19。 2020年3月24日,印度联盟政府从第二天起宣布了整个国家的前所未有的完全封锁。在整个人类历史上,在全球任何地方都没有进行类似规模和规模的行动。这项研究旨在使用覆盖96%以上印度领土的动力学模型科学分析该决定的含义。该模型受到与印度有关的大量现实参数的进一步限制,以捕获印度普遍存在的地面现实,例如:(i)真正的状态人口密度分布,(ii)在模拟的零零日(2020年3月20日)的零零日(iii)跨越平均群体的差异(IV)的迁移,(IV)的迁移方式(IIV),(iv地理,(vi)基于2011年人口普查,(VIII)世界卫生组织(WHO)人口统计学明智的感染率和(IX)孵化期报告的基于2011年人口普查的印度人口统计数据的不同迁移模式,(VII)印度人口统计数据。该模型没有试图对疾病独立传播的长期预测。但是要比较两种不同的方案(完全锁定与无锁定)。在模型假设的框架中,我们的模型最终显示了锁定的巨大成功,即在人口一小部分内包含该疾病,而在没有该疾病的情况下,这将导致非常严重的情况。
The present ongoing global pandemic caused by SARS-CoV-2 virus is creating havoc across the world. The absence of any vaccine as well as any definitive drug to cure, has made the situation very grave. Therefore only few effective tools are available to contain the rapid pace of spread of this disease, named as COVID-19. On 24th March, 2020, the the Union Government of India made an announcement of unprecedented complete lockdown of the entire country effective from the next day. No exercise of similar scale and magnitude has been ever undertaken anywhere on the globe in the history of entire mankind. This study aims to scientifically analyze the implications of this decision using a kinetic model covering more than 96% of Indian territory. This model was further constrained by large sets of realistic parameters pertinent to India in order to capture the ground realities prevailing in India, such as: (i) true state wise population density distribution, (ii) accurate state wise infection distribution for the zeroth day of simulation (20th March, 2020), (iii) realistic movements of average clusters, (iv) rich diversity in movements patterns across different states, (v) migration patterns across different geographies, (vi) different migration patterns for pre- and post-COVID-19 outbreak, (vii) Indian demographic data based on the 2011 census, (viii) World Health Organization (WHO) report on demography wise infection rate and (ix) incubation period as per WHO report. This model does not attempt to make a long-term prediction about the disease spread on a standalone basis; but to compare between two different scenarios (complete lockdown vs. no lockdown). In the framework of model assumptions, our model conclusively shows significant success of the lockdown in containing the disease within a tiny fraction of the population and in the absence of it, it would have led to a very grave situation.