论文标题
为什么锁定：关于SARS-COV-2在印度的传播，一种网络方法
Why lockdown : On the spread of SARS-CoV-2 in India, a network approach
论文作者
论文摘要
我们分析了从2020年3月1日至2020年4月17日受到COVID-19影响的印度地区或城市数量的时间序列数据。我们在时间序列网络数据的框架框架中研究了数据。网络是通过使用纬度和经度坐标指定的地区或城市的大地距离来定义的。我们特别将分析限制在印度东北部的所有地区以外的所有地区。与最近有关在不久的将来感染SARS-COV-2人数的预测的研究不同，在本说明中，重点是了解该病毒在印度地区传播的动态。我们通过考虑多种度量，特别是光谱半径，代数连接性，平均聚类系数，平均路径长度和社区结构来对模型网络进行光谱和结构分析。此外，我们研究了锁定之前和之后的地区或城市数量给出的总体扩张属性。这些研究表明，锁定对长距离地区或城市中SARS-COV-2的传播产生了重大影响。但是，只有在锁定大约两周后才能观察到这种影响。我们推测，这是由于封锁之前的Covid-19测试数量不足而发生的，这无法阻止感染该病毒的人的运动，但没有在长距离内检测到。
We analyze the time series data of number of districts or cities in India that are affected by COVID-19 from March 01, 2020 to April 17, 2020. We study the data in the framework of time series network data. The networks are defined by using the geodesic distances of the districts or cities specified by the latitude and longitude coordinates. We particularly restrict our analysis to all but districts in the north-eastern part of India. Unlike recent studies on the projection of the number of people infected with SARS-CoV-2 in the near future, in this note, the emphasis is on understanding the dynamics of the spread of the virus across the districts of India. We perform spectral and structural analysis of the model networks by considering several measures, notably the spectral radius, the algebraic connectivity, the average clustering coefficient, the average path length and the structure of the communities. Furthermore, we study the overall expansion properties given by the number of districts or cities before and after lockdown. These studies show that lockdown has a significant impact on the spread of SARS-CoV-2 in districts or cities over long distances. However, this impact is only observed after approximately two weeks of lockdown. We speculate that this happened due to the insufficient number of tests for COVID-19 before the lockdown which could not stop the movement of people infected with the virus but not detected, over long distances.
