Athreya Siva, Gadhiwala Nitya, Mishra Abhiti
Indian Statistical Institute, 8th Mile Mysore Road, Bangalore, 560059 India.
J Indian Soc Probab Stat. 2021;22(2):319-342. doi: 10.1007/s41096-021-00106-1. Epub 2021 Sep 24.
We study the effectiveness and limitations of contact-tracing, quarantine, and lockdown measures used in India to control the spread of COVID-19 infections. Using data provided in the media bulletins of Government of Karnataka we observe that the so called rule holds for secondary infections and classify them into clusters. Using a mixture of Poisson with Gamma model we establish that clusters show variation in deceased rates ( ), low reproduction numbers ( ), small dispersion( ), and that super-spreading events can occur. Further, migration due to relaxation in lockdown is unlikely to be the sole cause of recent surge. The methodology presented is universal in nature and can be applied whenever such precise data is available.
我们研究了印度为控制新冠病毒感染传播而采用的接触者追踪、隔离和封锁措施的有效性及局限性。利用卡纳塔克邦政府新闻公告中提供的数据,我们观察到所谓的规则适用于二次感染,并将其分类为集群。通过泊松分布与伽马模型的混合模型,我们确定集群在死亡率( )、低繁殖数( )、小离散度( )方面存在差异,并且可能会发生超级传播事件。此外,封锁措施放松导致的迁移不太可能是近期感染激增的唯一原因。本文提出的方法本质上具有通用性,只要有此类精确数据,均可应用。