School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi110067, India.
Epidemiol Infect. 2020 Aug 28;148:e200. doi: 10.1017/S0950268820001946.
India is one of the severely affected countries by the Covid-19 pandemic at present. Within the stochastic framework of the SEQIR model, we studied publicly available data of the Covid-19 patients in India and analysed possible impacts of quarantine and social distancing as controlling strategies for the pandemic. Our stochastic simulation results clearly show that proper quarantine and social distancing should be maintained right from the start of the pandemic and continued until its end for effective control. This calls for a more disciplined social lifestyle in the future. However, only social distancing and quarantine of the exposed population are found not sufficient enough to end the pandemic in India. Therefore, implementation of other stringent policies like complete lockdown as well as increased testing of susceptible populations is necessary. The demographic stochasticity, which is quite visible in the system dynamics, has a critical role in regulating and controlling the pandemic.
印度是目前受新冠疫情影响最严重的国家之一。在 SEIR 模型的随机框架下，我们研究了印度新冠患者的公开数据，并分析了隔离和社会疏离作为控制大流行的策略的可能影响。我们的随机模拟结果清楚地表明，应从大流行开始就一直保持适当的隔离和社会疏离，并持续到大流行结束，以进行有效控制。这就要求未来的社会生活方式更加自律。然而，研究结果还表明，仅对暴露人群进行社会疏离和隔离不足以在印度结束疫情。因此，有必要实施其他严格的政策，如全面封锁以及增加对易感人群的检测。在系统动力学中，人口统计学随机性在调节和控制大流行方面起着关键作用。
