Estimation of the potential spread risk of COVID-19: Occurrence assessment along the Yangtze, Han, and Fu River basins in Hubei, China

中国 长江 流域 分水岭 地理 风险评估 环境科学 水文学(农业) 水资源管理 构造盆地 地图学 地质学 地貌学 计算机科学 机器学习 考古 岩土工程 计算机安全
作者
Bo Yang,Wei Li,Jingquan Wang,Zixin Tian,Xiaonong Cheng,Yongli Zhang,Rui Qiu,Shuhua Hou,Hongguang Guo
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:746: 141353-141353 被引量:14
标识
DOI:10.1016/j.scitotenv.2020.141353
摘要

Given that the novel coronavirus was detected in stool and urine from diagnosed patients, the potential risk of its transmission through the water environment might not be ignored. In the current study, to investigate the spread possibility of COVID-19 via the environmental media, three typical rivers (Yangtze, Han, and Fu River) and watershed cities in Hubei province of China were selected, and a more comprehensive risk assessment analysis method was built with a risk index proposed. Results showed that the risk index in the Yangtze River Basin is about 10−12, compared to 10−10 and 10−8 in the Han and Fu River Basins, and the risk index is gradually reduced from Wuhan city to the surrounding cities. The safety radius and safety time period for the Yangtze, Han, and Fu River are 8 km/14 h, 20 km/30 h and 36 km/36 h, respectively. The linear relationship between the risk potential calculated by the QMRA model and the multiple linear regression proved that the built index model is statistically significant. By comparing the theoretical removal rates for the novel coronavirus, our study proposed an effective method to estimate the potential spread risk of COVID-19 in the typical river basins.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
why发布了新的文献求助10
3秒前
完美世界应助huang采纳,获得10
3秒前
3秒前
5秒前
5秒前
星辰大海应助hhh采纳,获得10
6秒前
7秒前
pppppristine发布了新的文献求助10
8秒前
10秒前
飞快的臻发布了新的文献求助10
10秒前
11秒前
汩浥发布了新的文献求助10
11秒前
11秒前
Orange应助why采纳,获得10
11秒前
科研通AI6.2应助吃个馍馍采纳,获得10
12秒前
wanci应助执着的翩跹采纳,获得10
13秒前
小信鸽完成签到,获得积分10
13秒前
13秒前
14秒前
15秒前
赘婿应助盒子采纳,获得30
16秒前
芫华发布了新的文献求助10
16秒前
16秒前
Hello应助liva采纳,获得10
17秒前
Gustav_Lebon发布了新的文献求助10
17秒前
lurongjun发布了新的文献求助30
19秒前
molihuakai应助夜雨采纳,获得10
19秒前
飞快的乘风完成签到,获得积分10
20秒前
慕青应助liva采纳,获得10
20秒前
21秒前
Lucas应助pppppristine采纳,获得10
21秒前
孟阳发布了新的文献求助50
22秒前
茉莉完成签到 ,获得积分10
23秒前
23秒前
乐乐应助liva采纳,获得10
23秒前
大个应助科研通管家采纳,获得10
25秒前
25秒前
英姑应助Gustav_Lebon采纳,获得10
25秒前
ddd应助科研通管家采纳,获得10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7618256
求助须知:如何正确求助?哪些是违规求助? 9193532
关于积分的说明 19704516
捐赠科研通 7190749
什么是DOI,文献DOI怎么找? 3272214
关于科研通互助平台的介绍 2434900
邀请新用户注册赠送积分活动 2267419