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印度奥里萨邦 SARS-CoV-2 传播动力学的流行病学分析:长达一年的探索性数据分析。

Epidemiological Analysis of SARS-CoV-2 Transmission Dynamics in the State of Odisha, India: A Yearlong Exploratory Data Analysis.

机构信息

School of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, Odisha, India.

All India Institute of Medical Sciences, Bhubaneswar 751019, Odisha, India.

出版信息

Int J Environ Res Public Health. 2021 Oct 25;18(21):11203. doi: 10.3390/ijerph182111203.

Abstract

COVID-19 remains a matter of global public health concern. Previous research suggested the association between local environmental factors and viral transmission. We present a multivariate observational analysis of SARS-CoV-2 transmission in the state of Odisha, India, hinting at a seasonal activity. We aim to investigate the demographic characteristics of COVID-19 in the Indian state of Odisha for two specific timelines in 2020 and 2021. For a comparative outlook, we chose similar datasets from the state of New York, USA. Further, we present a critical analysis pertaining to the effects of environmental factors and the emergence of variants on SARS-CoV-2 transmission and persistence. We assessed the datasets for confirmed cases, death, age, and gender for 29 February 2020 to 31 May 2020, and 1 March 2021 to 31 May 2021. We determined the case fatalities, crude death rates, sex ratio, and incidence rates for both states along with monthly average temperature analysis. A yearlong epi-curve analysis was conducted to depict the coronavirus infection spread pattern in the respective states. The Indian state of Odisha reported a massive 436,455 confirmed cases and 875 deaths during the 2021 timeline as compared to a mere 2223 cases and 7 deaths during the 2020 timeline. We further discuss the demographic and temperature association of SARS-CoV-2 transmission during early 2020 and additionally comment on the variant-associated massive rise in cases during 2021. Along with the rapid rise of variants, the high population density and population behavior seem to be leading causes for the 2021 pandemic, whereas factors such as age group, gender, and average local temperature were prominent during the 2020 spread. A seasonal occurrence of SARS-CoV-2 transmission is also observed from the yearlong epidemiological plot. The recent second wave of COVID-19 is a lesson that emphasizes the significance of continuous epidemiological surveillance to predict the relative risk of viral transmission for a specific region.

摘要

COVID-19 仍然是一个全球公共卫生关注的问题。之前的研究表明,局部环境因素与病毒传播之间存在关联。我们呈现了一项对印度奥里萨邦 SARS-CoV-2 传播的多变量观察分析,暗示了季节性活动。我们旨在调查 2020 年和 2021 年印度奥里萨邦 COVID-19 的人口统计学特征。为了进行比较,我们从美国纽约州选择了类似的数据集。此外,我们还对环境因素和变体对 SARS-CoV-2 传播和持久性的影响进行了批判性分析。我们评估了 2020 年 2 月 29 日至 5 月 31 日和 2021 年 3 月 1 日至 5 月 31 日期间确诊病例、死亡、年龄和性别相关的数据集。我们确定了两个州的病例死亡率、粗死亡率、性别比和发病率,以及每月平均温度分析。进行了为期一年的 epi 曲线分析,以描绘各自州的冠状病毒感染传播模式。与 2020 年相比,印度奥里萨邦在 2021 年报告了 436455 例确诊病例和 875 例死亡病例,而在 2020 年仅报告了 2223 例病例和 7 例死亡病例。我们进一步讨论了 2020 年初 SARS-CoV-2 传播的人口统计学和温度关联,并对 2021 年与变体相关的病例大量增加发表了评论。随着变体的迅速增加,高人口密度和人口行为似乎是 2021 年大流行的主要原因,而年龄组、性别和当地平均温度等因素在 2020 年的传播中较为突出。从全年的流行病学图中也可以观察到 SARS-CoV-2 传播的季节性发生。最近的第二波 COVID-19 疫情是一个教训,强调了持续进行流行病学监测以预测特定地区病毒传播的相对风险的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd8b/8582922/3f66f9dacccb/ijerph-18-11203-g001.jpg

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