基于线性回归的COVID-19疫苗接种进展数据可视化及预测

H. H. Nuha, Ahmad Abo Absa
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引用次数: 1

摘要

本文提供了COVID-19疫苗接种计划的数据可视化和分析。重要信息,如哪些国家的疫苗接种率和数量最高。除了世界各国使用和使用的疫苗类型外,还显示了关于疫苗使用的地理分布的信息图。为了对获得的数据进行建模,通过线性回归对日疫苗接种率进行建模,其中使用数据科学方法(即线性回归)对具有不同疫苗接种范围的五个样本国家进行处理。建模结果显示一个梯度系数,表示疫苗接种率的增加。预测结果显示,每日疫苗接种的最高增长率为每天增加1,826,126支疫苗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Visualization of COVID-19 Vaccination Progress and Prediction Using Linear Regression
This paper provides a data visualization and analysis of the COVID-19 vaccination program. Important information such as which countries have the highest vaccination rates and numbers. In addition to the types of vaccines used and used by countries in the world, an infographic on the geographic distribution of vaccine use is also shown. To model the obtained data, daily vaccination rates were modeled by linear regression in which five sample countries with different vaccination ranges were processed using data science approach, namely, linear regression. The modeling results show a gradient coefficient that represents an increase in vaccine rates. The prediction results showed that the highest rate of increase in daily vaccination was 1,826,126 additional vaccines per day.
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