Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.
Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.
复制标题
COVID-19 大流行期间美国工人社交接触模式的变化：2020 年 4 月至 2021 年 12 月。
DOI：
10.1101/2022.12.19.22283700
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Lopman,BenA
中科院分区：
文献类型：
--
作者：
Kiti,MosesC;Aguolu,ObianujuG;Zelaya,Alana;Chen,HolinY;Ahmed,Noureen;Battross,Jonathan;Liu,CarolY;Nelson,KristinN;Jenness,SamuelM;Melegaro,Alessia;Ahmed,Faruque;Malik,Fauzia;Omer,SaadB;Lopman,BenA
非药物干预措施最大限度地减少了社会接触，从而减少了流感和SARS-CoV-2等呼吸道病原体的传播。在全球范围内，劳动力的社会联系数据非常缺乏。在这项研究中，我们量化了美国员工两天的接触模式。接触被定义为面对面的谈话，涉及身体接触或接近另一个人，并使用电子自我保存日记收集。于2019冠状病毒病大流行期间，数据于2020年至2021年收集了4轮。第1轮（2020年4月至6月）、第2轮（2020年11月至2021年1月）、第3轮（2021年6月至8月）和第4轮（2021年11月至12月），1456名参与者报告的平均（标准差）接触次数分别为2.5（2.5）、8.2（7.1）、9.2（7.1）和10.1（9.5）。在第1轮和第2轮之间，我们报告每个参与者报告的平均接触次数增加了3倍，而第2-4轮没有大幅增加。然后，我们模拟了SARS-CoV-2在家庭，工作和社区环境中的传播。该模型显示，在第1轮的所有设置中，相对传输都有所减少。随后，在家庭和社区的传播增加，但在工作环境中仍然非常低。为了准确地参数化感染传播和控制模型，我们需要经验性的社会接触数据，这些数据可以捕捉人类在不同时间的混合行为。
Non-pharmaceutical interventions minimize social contacts, hence the spread of respiratory pathogens such as influenza and SARS-CoV-2. Globally, there is a paucity of social contact data from the workforce. In this study, we quantified two-day contact patterns among USA employees. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic self-kept diaries. Data were collected over 4 rounds from 2020 to 2021 during the COVID-19 pandemic. Mean (standard deviation) contacts reported by 1456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April–June 2020), 2 (November 2020–January 2021), 3 (June–August 2021), and 4 (November–December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2–4. We then modeled SARS-CoV-2 transmission at home, work, and community settings. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained exceptionally low in work settings. To accurately parameterize models of infection transmission and control, we need empirical social contact data that capture human mixing behavior across time.