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人口规模和多样的气候条件是印度成为下一个新冠疫情大流行中心的驱动因素吗?

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

作者信息

Samanta Palas, Dey Sukhendu, Ghosh Apurba Ratan

机构信息

Department of Environmental Science, Sukanta Mahavidyalaya, University of North Bengal, Dhupguri, West Bengal, India.

Department of Environmental Science, The University of Burdwan, Burdwan, West Bengal, India.

出版信息

Results Phys. 2021 Jul;26:104454. doi: 10.1016/j.rinp.2021.104454. Epub 2021 Jun 12.

Abstract

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 ( 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, as strategic management policy. Therefore, it is predicted, India could be the next epicenter of COVID-19 outbreak because of its over population.

摘要

尽管自2020年3月24日新冠疫情爆发以来印度实施了全国范围的封锁,但新冠病毒感染人数仍在逐日增加。截至2021年6月10日,印度已记录了29182072例新冠病例和359695例死亡病例。许多因素有助于影响新冠病毒的传播率和流行程度。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)与人口数量(PM)相结合,以确定它们对印度新冠病毒快速传播的影响。基于受试者工作特征(ROC)分类模型,研究了AT、H和PM参数对新冠病毒传播的敏感性。结果表明,AT和H模型对引发病毒传播以及区分感染者和健康者的敏感性非常低(曲线下面积值分别为0.26和0.37,低于AUC值0.5)。相反,PM模型对新冠病毒传播以及区分感染者和健康者高度敏感(AUC值为0.912,大于AUC值0.5),大约225万人口必须实施诸如社交距离、个人卫生等战略管理政策。因此,据预测,由于人口过多,印度可能成为下一个新冠疫情爆发的中心。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f43c/8197627/0c0fea398594/gr1_lrg.jpg

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