Occupational and Industry Prevalence of New Long-Term Symptoms Within American Red Cross Blood Donors with and Without History of SARS-CoV-2 Infection.
AMERICAN JOURNAL OF INDUSTRIAL MEDICINE(2024)
摘要
PurposeLimited information is known about the burden of Long COVID by occupation and industry. This study compares the occurrence of self-reported new long-term symptoms lasting 4 weeks or longer among blood donors with and without prior SARS-CoV-2 infection by occupation and industry. MethodsThe American Red Cross invited blood donors 18 years and older who donated during May 4-December 31, 2021 to participate in online surveys. New long-term symptoms lasting 4 weeks or longer were assessed by self-reported occurrence of any of 35 symptoms since March 2020. SARS-CoV-2 infection status was determined by serological testing and self-report. We describe the prevalence of new long-term symptoms by SARS-CoV-2 infection status. We calculate the difference in reported new long-term symptoms by SARS-CoV-2 infection status within occupation and industry categories. ResultsData were collected from 27,907 employed adults - 9763 were previously infected and 18,234 were never infected with SARS-CoV-2. New long-term symptoms were more prevalent among those previously infected compared to the never-infected respondents (45% vs 24%, p < 0.05). Among all respondents, new long-term symptoms by occupation ranged from 26% (installation, maintenance, and repair) to 41% (healthcare support) and by industry ranged from 26% (mining) to 55% (accommodation and food services). New long-term neurological and other symptoms were commonly reported by those previously infected with SARS-CoV-2. DiscussionNew long-term symptoms are more prevalent among certain occupation and industry groups, which likely reflects differential exposure to SARS-CoV-2. These findings highlight potential need for workplace accommodations in a variety of occupational settings to address new long-term symptoms.
更多查看译文
关键词
COVID-19,industry,Long COVID,occupation,Post-COVID Conditions,SARS-CoV-2
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn