The COVID-19 outbreak began in December 2019 and soon became a global pandemic, resulting in major public health consequences for countries across the world. As the COVID-19 outbreak evolved, individuals were challenged to understand the risk of COVID-19 and to identify ways to stay safe. This understanding was accomplished through COVID-19 communication ecologies that consist of interpersonal, organizational, and mediated communication resources. In the current study, we examine the U.S. COVID-19 communication ecology in September 2021. We introduce the communication ecology network (CEN) model, which posits that similar useful communication resources will cluster in a communication ecology, and we use network analysis for visualization of the ecology. Our results indicate a robust COVID-19 communication ecology. The most important communication resources in the ecology were partisan and organizational communication resources. We identify and discuss five clusters within the COVID-19 communication ecology and examine how use of each of these clusters is associated with belief in COVID-19 misinformation. Our use of network analysis illustrates benefits of this analytical approach to studying communication ecologies.

COVID-19疫情始于2019年12月，并很快成为全球大流行病，对世界各国造成了重大公共卫生后果。随着COVID-19爆发的发展，人们面临着挑战以了解COVID-19的风险并确定保持安全的方法。这种理解是通过COVID-19通信生态系统实现的，该通信生态系统包括人际，组织和中介的通信资源。在当前的研究中，我们研究了2021年9月的美国COVID-19通信生态系统。我们引入了通信生态网络（CEN）模型，该模型假定相似的有用通信资源将聚集在通信生态系统中，并且我们使用网络分析进行可视化生态。我们的结果表明了强大的COVID-19沟通生态。生态学中最重要的交流资源是党派和组织交流资源。我们确定并讨论了COVID-19沟通生态系统中的五个集群，并研究了如何利用这些集群与对COVID-19错误信息的信念相关联。我们对网络分析的使用说明了这种分析方法研究通信生态的好处。