STATISTICAL ANALYSIS OF COVID-19 VACCINATIONS: KARACHI AS A CASE STUDY

Danish Hassan, Usama Raza, Zaubaria Malick, A. Bakar, Hamza Khan, Muhammad Danish Khan, Kashif Javed
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Abstract

The entire world has started to vaccinate their respective countries' citizens to get rid of COVID-19 from their country. Likewise other countries, Pakistan has also started the vaccination process for its citizens and unlike the rest of the world, there have been different types of vaccines in Pakistan with different manufacturers and with different immunity booster levels. Through statistical analysis of vaccination in this research paper, we have tried to understand the diverse level of vaccines in Karachi and tried to get an understanding of the vaccination process happening in Karachi. For this kind of research, we have maintained the questionnaire and spread it through emails, WhatsApp, and Facebook.  The questionnaire was sent to about 500 people from July to August 2021. The results obtained depict the satisfaction of the vaccination process with normal side effects. Unlike other countries, Pakistan is among the countries where the mass vaccination process has always been very difficult to conduct. Further using the data of seven stations for prediction purposes Multiple Linear Regression (MLR) models were constructed. A better future trend analysis of COVID-19 can be observed using these constructed models. The data for the time series modeling from, 1st January 2021 to 25 August 2021, was taken from National Command and Control (NCOC) Pakistan.
新冠肺炎疫苗接种统计分析——以卡拉奇为例
全世界已经开始为各自国家的公民接种疫苗,以摆脱本国的新冠肺炎。与其他国家一样,巴基斯坦也开始了其公民的疫苗接种过程,与世界其他国家不同,巴基斯坦有不同类型的疫苗,制造商不同,免疫增强水平不同。通过对本研究论文中疫苗接种的统计分析,我们试图了解卡拉奇疫苗的多样性水平,并试图了解卡拉奇正在发生的疫苗接种过程。对于这类研究,我们保留了问卷,并通过电子邮件、WhatsApp和Facebook进行传播。调查问卷于2021年7月至8月发送给约500人。所获得的结果描述了疫苗接种过程对正常副作用的满意度。与其他国家不同,巴基斯坦是大规模疫苗接种过程一直很难进行的国家之一。进一步利用七个站点的数据进行预测,构建了多元线性回归(MLR)模型。使用这些构建的模型可以观察到新冠肺炎更好的未来趋势分析。2021年1月1日至2021年8月25日的时间序列建模数据取自巴基斯坦国家指挥控制中心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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