1 INTRODUCTION

All of the policies adopted or proposed so far to slow the spread of the novel coronavirus require immediate and extensive behavioral change. However, changing behavior is difficult even when the benefits are borne by solid science. Doing so effectively requires an appreciation for how people learn behaviors and translate information into action. Evidence‐based policies for altering health behaviors are not new. For example, a decade‐old systematic review of the health interventions literature identified 26 common behavior change techniques such as providing various kinds of information, setting up graded tasks, and making contracts (Abraham & Michie, 2008). Perhaps most influentially, behavioral economists have proposed nudges to influence people's behaviors (Thaler & Sunstein, 2009), including ones that reduce coronavirus transmission (Everett, Colombatto, Chituc, Brady, & Crockett, 2020; Van Bavel et al., 2020). Beyond concerns regarding the efficacy of various nudges (Hummel & Maedche, 2019; Szaszi, Palinkas, Palfi, Szollosi, & Aczel, 2018), this approach lacks an integrative theoretical framework for understanding why humans have particular heuristics, how behaviors are shaped by social and economic structures, and which nudges are likely to work in different socio‐cultural contexts.

Insights from the evolutionary human sciences can improve the behavioral change toolkit for researchers and policy makers. Specifically, effective policy should be based on an understanding of humans as a cultural and cooperative species. Socially transmitted information and culturally‐informed motivations shape behavior change. The structure of social networks and how group identities map onto those networks influence transmission dynamics. Information can spread from person to person, similar to the way diseases spread (Cavalli‐Sforza & Feldman, 1981; Centola, 2018; Sperber, 1996). Just as with disease, the epidemiology of information is subject to structural and behavioral influences on transmissibility. Below, we show why and how (a) the pandemic poses several adaptive challenges with important tradeoffs, (b) people use social information to learn how to deal with these, and (c) people adopt social norms in a group‐based context.

中文翻译：

---

COVID世界中行为变化的动态

1引言

迄今为止，通过或提议采取的所有旨在减缓新型冠状病毒传播的政策都需要立即且广泛的行为改变。但是，即使收益是由可靠的科学带来的，改变行为也是困难的。有效地做到这一点需要对人们如何学习行为以及将信息转化为行动的理解。以证据为基础的改变健康行为的政策并不新鲜。例如，对健康干预文献进行了十年的系统回顾，确定了26种常见的行为改变技术，例如提供各种信息，设置分级任务和签订合同（Abraham＆Michie，2008年）。也许最有影响力的是，行为经济学家提出了微调来影响人们的行为（Thaler＆Sunstein，2009年），包括减少冠状病毒传播的病毒（Everett，Colombatto，Chituc，Brady和Crockett，2020； Van Bavel等，2020）。除了担心各种微调的功效（Hummel＆Maedche，2019 ; Szaszi，Palinkas，Palfi，Szollosi，＆Aczel，2018）外，这种方法还缺乏一个综合的理论框架来理解人类为何具有特定的启发式思想，行为如何被社会塑造和经济结构，以及哪些推动因素可能在不同的社会文化环境中发挥作用。

进化人类科学的见解可以改善研究人员和政策制定者的行为改变工具包。具体而言，有效的政策应基于对人类作为文化和合作物种的理解。社交信息和文化动机会影响行为改变。社交网络的结构以及群体身份如何映射到这些网络上会影响传播动态。信息可以在人与人之间传播，类似于疾病传播的方式（Cavalli-Sforza＆Feldman，1981； Centola，2018； Sperber，1996）。就像疾病一样，信息的流行病学也受到结构和行为对传播能力的影响。下面，我们说明原因和（a）大流行如何带来重大权衡的几个适应性挑战；（b）人们使用社会信息来学习如何应对这些挑战；（c）人们在基于群体的环境中采用社会规范。