论文标题
研究COVID-19的控制策略的随机方法在印度大流行
Stochastic approach to study control strategies of Covid-19 pandemic in India
论文作者
论文摘要
印度目前是Covid-19的最严重的国家之一。我们研究了印度Covid-19患者的公开数据，并分析了Seqir模型随机框架内检疫和社会疏远的可能影响，以说明大流行的控制策略。我们的仿真结果清楚地表明，在大流行开始时，应从早期开始保持适当的隔离和社会距离，并应继续直到结束以有效控制大流行。在将来，这需要在这种观点上具有更具社会纪律处分的生活方式。在系统动力学中非常可见的人口随机性在调节和控制大流行方面具有关键作用。
India is one of the worst affected countries by the Covid-19 pandemic at present. We studied publicly available data of the Covid-19 patients in India and analyzed possible impacts of quarantine and social distancing within the stochastic framework of the SEQIR model to illustrate the controlling strategy of the pandemic. Our simulation results clearly show that proper quarantine and social distancing should be maintained from an early time just at the start of the pandemic and should be continued till its end to effectively control the pandemic. This calls for a more socially disciplined lifestyle in this perspective in future. The demographic stochasticity, which is quite visible in the system dynamics, has a critical role in regulating and controlling the pandemic.
