The COVID-19 pandemic has spread uncertainty and social disruption, and exacerbated political divides in the United States. Most studies of the drivers of the epidemic focus on victim characteristics without consideration of drivers in the general population. This study presents statistical models that track the underlying factors in the general population associated with the spread of the pandemic and addresses how social learning mechanisms have led people to adopt perspectives and behaviors depending on their social context. Despite many social, physiological and economic factors, the statistical drivers of the pandemic primarily relate to the presence of vectors and the probability of transmission. However, the relationship between these drivers and COVID-19 deaths is weak and variable outside of the New York metropolitan area. Furthermore, the per capita death rate in much of the country has been much lower than the New York metropolitan area. There have been two very different experiences with the pandemic, one where the signals of its danger have been obvious from the start and one where the signals have been much weaker. Social learning mechanisms (in-group information sharing, imitation, costly punishment) have amplified the effect of people’s experiences with the pandemic. Sheltering in cities and protesting shutdowns in rural areas probably were initially adaptive somatic efforts in the evolutionary sense, given the different realities of the pandemic versus its economic costs in urban versus rural environments. These adaptations, however, have deepened the political divides in an already Balkanized country. The paper concludes with practical recommendations for how to use social learning theory for disseminating information on how to combat the pandemic.

COVID-19大流行已经蔓延了不确定性和社会动荡，并加剧了美国的政治分歧。关于流行病驱动因素的大多数研究都关注受害者的特征，而没有考虑一般人群中的驱动因素。这项研究提出了统计模型，这些模型跟踪了与大流行蔓延相关的普通人群的基本因素，并探讨了社会学习机制如何使人们根据其社会背景采用观点和行为。尽管有许多社会，生理和经济因素，大流行的统计驱动因素主要与病媒的存在和传播的可能性有关。但是，这些驱动程序与COVID-19死亡之间的关系是脆弱的，并且在纽约大都市区之外是可变的。此外，该国大部分地区的人均死亡率远低于纽约都会区。大流行有两种截然不同的经历，一种是从一开始就已经明显意识到其危险的信号，而另一种信号则要弱得多。社会学习机制（小组内信息共享，模仿，代价高昂的惩罚）放大了人们对大流行的经历的影响。考虑到大流行的现实与城市和农村环境的经济成本不同，从进化的意义上说，在城市庇护和在农村地区抗议停工可能最初是适应性的体力活动。但是，这些调整加深了一个已经巴尔干化国家的政治分歧。