马哈拉施特拉邦各县根据环境污染物和气象因素划分的 COVID-19 病例分布情况

IF 0.1 Q4 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
B. Madhu, Brototi Biswas, Dhivya Karegam, Arun Kumar Yadav
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引用次数: 0

摘要

人们研究了温度、降水等环境因素以及空气中的各种其他污染物,如二氧化氮(NO2)、二氧化碳等,以了解冠状病毒疾病-19(COVID-19)的生存和传播情况。印度缺乏根据空气污染物和气象因素对 COVID-19 病例分布情况的研究。因此,本研究以马哈拉施特拉邦各地区 COVID-19 病例的聚类图为目标,研究 COVID-19 与环境因素之间的关系。 空气污染变量二氧化氮柱密度(mol/m2)、二氧化硫柱密度(mol/m2)、气溶胶吸收指数(Ai)、一氧化碳(CO)柱密度(mol/m2)和臭氧柱密度(mol/m2)是从谷歌地球引擎(GEE)(https://code.earthengine.google.com/)中提供的哨兵-5P 数据集中提取的。气象变量降水量(m)、温度(t)和湿度(k)从谷歌地球引擎中的欧洲环境署 5 陆地再分析数据集中提取,该数据集提供分辨率为 1113.2 m 的数据。这些数值与每日病例、密度和其他人口因素相关联。 研究确定了马哈拉施特拉邦几个地区的病例群。这些地区是普纳、艾哈迈德纳加尔、孟买、纳西克和那格浦尔。在大多数月度数据中,人口密度和二氧化氮是重要因素。 本研究利用公共平台上的数据来评估 COVID-19 与环境因素之间的关联。研究发现,二氧化氮、一氧化碳和艾等各种环境因素可能与该地区 COVID-19 病例的增加有关。然而,生态偏差可能会引起注意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distribution of COVID-19 Cases According to Environmental Pollutants and Meteorological Factors in Districts of Maharashtra
Environmental factors such as temperature, precipitation, and various other pollutants in the air like nitrogen dioxide (NO2), CO2, etc., have been studied for sustenance and transmission of Coronavirus disease-19 (COVID-19). Studies from India are lacking about the distribution of COVID-19 cases according to air pollutants and meteorological factors. Hence, the present study was conducted to study the relationship between COVID-19 and environmental factors with the objectives of Cluster mapping of the COVID-19 cases district-wise for the state of Maharashtra. The air pollution variables NO2 column density (mol/m2), sulfur dioxide column density (mol/m2), Aerosol absorbing index (Ai), Carbon monoxide (CO) column density (mol/m2), and Ozone column density (mol/m2) were extracted from Sentinel-5P datasets available in Google Earth Engine (GEE) (https://code.earthengine.google.com/). The meteorological variables precipitation (m), temperature (t), and humidity (k) were extracted from the European Environmental Agency 5-Land reanalysis dataset in GEE, which provides data at a resolution of 1113.2 m. The preprocessing and retrieval of data were carried out in GEE. These values were correlated with daily cases, density, and other demographic factors. The study identified a cluster of cases in few districts of Maharashtra. These districts were Pune, Ahmednagar, Mumbai, Nashik, and Nagpur. Population density and NO2 were important factors in most of the monthly data. The present study used data available on public platforms to assess the association between COVID-19 and environmental factors. The study found that various environmental factors such as NO2, CO, and Ai may be associated with increase cases of COVID-19 in the district. However, ecological bias may be kept in mind.
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来源期刊
Journal of Marine Medical Society
Journal of Marine Medical Society PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
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发文量
70
审稿时长
40 weeks
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