Occupations and their impact on the spreading of COVID-19 in urban communities.

Occupations and their impact on the spreading of COVID-19 in urban communities.
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DOI:
10.1038/s41598-022-18392-5
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发表时间:
2022-08-18
期刊:
影响因子:
4.6
通讯作者:
Ghita, Maria-Cristina
Ghita, Maria-Cristina
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Hancean, Marian-Gabriel;Lerner, Juergen;Perc, Matjaz;Oana, Iulian;Bunaciu, David-Andrei;Stoica, Adelina Alexandra;Ghita, Maria-Cristina

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目前的疫情对员工造成了严重影响。为了更好地了解职业在COVID-19传播中所起的作用,我们分析了2020年8月1日至10月31日期间在布加勒斯特收集的真实网络数据。这些数据记录了6895名患者的性别、年龄和职业,以及他们与之互动的13,272人,从而提供了一个来自城市环境的社交网络,COVID-19就是通过这个网络传播的。值得注意的是,我们发现医疗职业对病毒的传播没有显著影响。相反,我们发现常见的传播链始于在私营部门工作的受感染者,并与配偶,兄弟姐妹或老年亲属等非活跃的改变有关。我们使用关系超事件模型来评估社区传播中最可能的同质性和网络效应。我们发现同性恋与年龄和反同性恋与性别和就业能力。我们注意到,尽管我们欢迎更多的数据来进行更深入的网络分析,但我们的研究结果可能有助于公共当局更好地针对表现不佳的疫苗接种活动。
The current pandemic has disproportionally affected the workforce. To improve our understanding of the role that occupations play in the transmission of COVID-19, we analyse real-world network data that were collected in Bucharest between August 1st and October 31st 2020. The data record sex, age, and occupation of 6895 patients and the 13,272 people they have interacted with, thus providing a social network from an urban setting through which COVID-19 has spread. Quite remarkably, we find that medical occupations have no significant effect on the spread of the virus. Instead, we find common transmission chains to start with infected individuals who hold jobs in the private sector and are connected with non-active alters, such as spouses, siblings, or elderly relatives. We use relational hyperevent models to assess the most likely homophily and network effects in the community transmission. We detect homophily with respect to age and anti-homophily with respect to sex and employability. We note that, although additional data would be welcomed to perform more in-depth network analyses, our findings may help public authorities better target under-performing vaccination campaigns.
DOI: 10.1038/s41597-022-01374-7
发表时间: 2022-05-31
期刊: SCIENTIFIC DATA
影响因子: 9.8
作者:
Hancean, Marian-Gabriel;Ghita, Maria Cristina;Perc, Matjaz;Lerner, Juergen;Oana, Iulian;Mihaila, Bianca-Elena;Stoica, Adelina Alexandra;Bunaciu, David-Andrei
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期刊: INFECTION
影响因子: 7.5
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