论文标题
COVID 19感染动态的简单随机SIR模型：从欧洲学习
A simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe
论文作者
论文摘要
在此简短的说明中，我们使用随机的SIR模型对进化的区域趋势进行建模。 SIR动力学使用\ textit {itô-stochastic微分方程}表示。我们首先根据感染，恢复和死亡的24天历史从欧洲地区的可用每日数据中得出模型的参数。派生的参数已被汇总为投影印度次大陆的未来趋势，该次大陆目前正处于感染周期的早期阶段。这些预测旨在作为制定社会政治反对措施减轻Covid-19的指南。
In this short note we model the region-wise trends of the evolution to COVID-19 infections using a stochastic SIR model. The SIR dynamics are expressed using \textit{Itô-stochastic differential equations}. We first derive the parameters of the model from the available daily data from European regions based on a 24-day history of infections, recoveries and deaths. The derived parameters have been aggregated to project future trends for the Indian subcontinent, which is currently at an early stage in the infection cycle. The projections are meant to serve as a guideline for strategizing the socio-political counter measures to mitigate COVID-19.
