Spatial analysis of COVID-19 for the state of Uttar Pradesh, India

Meet Fatewar, Sandeep Kumar, Shruti Gautam
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Abstract

The world is struggling to combat COVID-19 pandemic, which is caused by the SARS-CoV-2 virus. The pandemic has affected millions of people all across the globe since the first case has been reported in the Wuhan city of China in December 2019. India is the second most affected country in the world with more than 8.5 million confirmed cases (as of 10 November 2020) after USA. India is facing an unprecedented crisis due to the pandemic, leading to the Nation’s economy to a near standstill. The share of COVID-19 confirmed cases in six most affected States of India is approximately 60 percent. The analytical research tries to assess the impact of COVID-19 through spatial-statistical analysis for the state of Uttar Pradesh, which is one of the most affected states by COVID-19 in India. The detailed analysis has been carried out at district level. The impact of pandemic is more in regions (or districts), which are either having metropolis or airports along with high population density and growth rate during the last decade. Furthermore, inadequate number of health infrastructure facilities and low number of testing are some of the major factors making the situation worse in India. The spatial-statistical analysis enables to understand the pattern of spreading of disease by identifying the hot-spot areas, perceiving the trend of transmission of disease spatially, and understanding the extent of the pandemic over a period of time.
印度北方邦COVID-19的空间分析
世界正在努力抗击由SARS-CoV-2病毒引起的COVID-19大流行。自2019年12月中国武汉市报告首例病例以来,新冠肺炎疫情已影响到全球数百万人。印度是世界上受影响第二大的国家,确诊病例超过850万例(截至2020年11月10日),仅次于美国。由于大流行,印度正面临前所未有的危机,导致国家经济几乎停滞不前。在印度六个受影响最严重的邦,COVID-19确诊病例的比例约为60%。分析性研究试图通过对北方邦的空间统计分析来评估COVID-19的影响,北方邦是印度受COVID-19影响最严重的州之一。在地区一级进行了详细的分析。大流行的影响更多的是在区域(或地区),这些地区在过去十年中要么有大都市或机场,要么人口密度高,增长率高。此外,卫生基础设施数量不足和检测数量少是使印度情况恶化的一些主要因素。空间统计分析可以通过识别热点地区,感知疾病的空间传播趋势,了解一段时间内大流行的程度,从而了解疾病的传播模式。
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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