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运用数值模拟预测旁遮普邦的 COVID-19 病例。

Numerical Simulation to Predict COVID-19 Cases in Punjab.

机构信息

Department of Mathematics, School of Chemical Engineering and Physical Sciences, Lovely Professional University, India.

Department of Mathematics, Hamedan Branch, Islamic Azad University, Hamedan, Iran.

出版信息

Comput Math Methods Med. 2022 Jul 22;2022:7546393. doi: 10.1155/2022/7546393. eCollection 2022.

Abstract

Coronavirus disease 2019 is a novel disease caused by a newly identified virus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). India recorded its first case of COVID-19 on 30 January 2020. This work is an attempt to calculate the number of COVID-19 cases in Punjab by solving a partial differential equation using the modified cubic B-spline function and differential quadrature method. The real data of COVID-19 cases and Google Community Mobility Reports of Punjab districts were used to verify the numerical simulation of the model. The Google mobility data reflect the changes in social behavior in real time and therefore are an important factor in analyzing the spread of COVID-19 and the corresponding precautionary measures. To investigate the cross-border transmission of COVID-19 between the 23 districts of Punjab with an analysis of human activities as a factor, the 23 districts were divided into five regions. This paper is aimed at demonstrating the predictive ability of the model.

摘要

新型冠状病毒病 2019 是一种由新型冠状病毒,即严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的新疾病。印度于 2020 年 1 月 30 日记录到首例 COVID-19 病例。本工作尝试通过使用修正三次 B 样条函数和微分求积法求解偏微分方程来计算旁遮普邦的 COVID-19 病例数。该模型的数值模拟使用了旁遮普邦 COVID-19 病例的真实数据和谷歌社区流动性报告进行验证。谷歌的移动数据实时反映社会行为的变化,因此是分析 COVID-19 传播和相应预防措施的重要因素。为了分析人类活动作为一个因素对旁遮普邦 23 个地区之间 COVID-19 的跨境传播,将这 23 个地区分为五个区域。本文旨在展示模型的预测能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1d1/9313927/09ea4626fda3/CMMM2022-7546393.001.jpg

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