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Prediction of COVID-19 Outbreak in India adopting Bhilwara Model of Containment

机译:采用Bhilwara遏制模型预测印度的COVID-19暴发

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The epidemic of coronavirus disease-2019 (COVID-19) establishes a medical emergency of worldwide concern with an exceptionally high danger of spread and affect the entire worldwide. In India, there has been a steady ascent in the infection with 20,080 cases on April 21 even after a countrywide lockdown. Bhilwara lockdown & containment model flattens the infection curve of COVID-19 cases just within 10 days of initial spread. This paper has described the Bhilwara model and compare the model with India COVID-19 outbreak lockdown along with a prediction for a reduction in the number of upcoming cases with its implementation. In experimentation, the Bhilwara model is simulated using 3rd-degree polynomial curve fitting techniques, and the mean growth rate of infection is calculated on the COVID-19 spread curve for a group of days depicting the effect of policies defined by Bhilwara administration. Using calculated mean growth rate, COVID-19 spread is predicted with 3rd-degree polynomial regression utilizing a dataset of all states of India. Results found that with the implementation of the Bhilwara model all over India, the infection transmission rate is reduced to a significant level. Results motivate government authorities to implement new policies and adaption of the Bhilwara model of containment to flatten the COVID-19 outbreak curve.
机译:2019年冠状病毒病(COVID-19)流行病在全球范围内引起了医疗紧急情况,其蔓延的危险性极高,并影响到整个世界。在印度,即使在全国范围内封锁之后,4月21日的感染仍呈上升趋势,达到20,080例。 Bhilwara锁定和遏制模型仅在初始传播的10天内就将COVID-19病例的感染曲线展平。本文介绍了Bhilwara模型,并将该模型与印度COVID-19爆发锁定进行了比较,并预测了实施该模型可以减少即将发生的案件数量。在实验中,使用3模拟了Bhilwara模型 rd 阶多项式曲线拟合技术,并在COVID-19传播曲线上计算了几天的平均感染增长率,描述了Bhilwara给药定义的策略的效果。使用计算出的平均增长率,可以预测COVID-19传播为3 rd 利用印度所有州的数据集进行高次多项式回归。结果发现,在整个印度实施Bhilwara模型后,感染的传播率降低到了可观的水平。结果激励政府当局实施新政策,并采用Bhilwara遏制模型来平整COVID-19爆发曲线。

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