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Are population size and diverse climatic conditions the driving factors for next COVID-19 pandemic epicenter in India?

机译:人口规模和多样化的气候条件下一个Covid-19大流行震中的驱动因素吗?

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Although a nationwide lockdown was imposed in India amid COVID-19 outbreak since March 24, 2020, the COVID-19 infection is increasing day-by-day. Till June 10, 2021 India has recorded 29,182,072 COVID cases and 359,695 deaths. A number of factors help to influence COVID-19 transmission rate and prevalence. Accordingly, the present study intended to integrate the climatic parameters, namely ambient air temperature (AT) and relative humidity (H) with population mass (PM) to determine their influence for rapid transmission of COVID-19 in India. The sensibility of AT, H and PM parameters on COVID-19 transmission was investigated based on receiver operating characteristics (ROC) classification model. The results depicted that AT and H models have very low sensibility (i.e.,lower area under curve value 0.26 and 0.37, respectively compared with AUC value 0.5) to induce virus transmission and discrimination between infected people and healthy ones. Contrarily, PM model is highly sensitive (AUC value is 0.912, greater than AUC value 0.5) towards COVID-19 transmission and discrimination between infected people and healthy ones and approximate population of 2.25?million must impose like social distancing, personal hygiene,etc.as strategic management policy. Therefore, it is predicted, India could be the next epicenter of COVID-19 outbreak because of its over population.
机译:虽然在2020年3月24日自3月24日起,Covid-19爆发的印度施加了全国锁定,但Covid-19的感染日益增加。直到6月10日,印度2021年录得29,182,072份Covid病例和359,695人死亡。许多因素有助于影响Covid-19传输速率和流行率。因此,本研究旨在将气候参数,即环境空气温度(AT)和相对湿度(H)与人群质量(PM)相结合,以确定它们对印度Covid-19快速传输的影响。基于接收器操作特性(ROC)分类模型,研究了Covid-19传输上的AT,H和PM参数的可感性。所描绘的结果,AT和H型号具有非常低的可感性(即,曲线值下的下面积0.26和0.37,分别与AUC值0.5)分别为感染者和健康之间的病毒传播和歧视。相反,PM模型非常敏感(AUC值为0.912,大于AUC值0.5)对Covid-19感染者和健康的传播和歧视,以及2.25?百万的近似人口必须强加如社会疏远,个人卫生等。作为战略管理政策。因此,它是预测的,由于其超过人群,印度可能是Covid-19爆发的下一个震中。

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