Abstract Large in‐person gatherings of travelers who do not socially distance are classified as the “highest risk” for COVID‐19 spread by the Centers for Disease Control and Prevention (CDC). From August 7–16, 2020, nearly 500,000 motorcycle enthusiasts converged on Sturgis, South Dakota for its annual rally in an environment without mask‐wearing requirements or other mitigating policies. This study is the first to explore this event's public health impacts. First, using anonymized cell phone data, we document that foot traffic at restaurants/bars, retail establishments, and entertainment venues rose substantially at event locations. Stay‐at‐home behavior among local residents fell. Second, using a synthetic control approach, we find that the COVID‐19 case rate increased substantially in Meade County and in the state of South Dakota in the month following the Rally. Finally, using a difference‐in‐differences model to assess nationwide spread, we find that following the Sturgis event, counties outside of South Dakota that contributed the highest inflows of rally attendees experienced a 6.4–12.5% increase in COVID‐19 cases relative to counties without inflows. Our findings highlight that local policy decisions assessing the tradeoff between local economic benefits and COVID‐19 health costs will not be socially optimal in the presence of large contagion externalities.

中文翻译：

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超级传播事件的传染外部性：斯特吉斯摩托车拉力赛和 COVID ‐19

摘要 美国疾病控制与预防中心 (CDC) 将没有社交距离的旅行者的大型面对面聚会归类为 COVID-19 传播的“最高风险”。从 2020 年 8 月 7 日至 16 日，近 500,000 名摩托车爱好者聚集在南达科他州的斯特吉斯，在没有戴口罩要求或其他缓解政策的环境中举行年度集会。这项研究是第一个探索这一事件的公共卫生影响的研究。首先，使用匿名手机数据，我们记录了餐厅/酒吧、零售场所和娱乐场所的客流量在活动地点大幅增加。当地居民的居家行为有所下降。其次，使用综合控制方法，我们发现，在集会后的一个月内，米德县和南达科他州的 COVID-19 病例率大幅上升。最后，使用差异中的差异模型来评估全国范围内的传播，我们发现在 Sturgis 事件之后，南达科他州以外的集会参与者流入量最高的县的 COVID-19 病例相对于没有流入的县。我们的研究结果强调，在存在大量传染外部性的情况下，评估当地经济利益和 COVID-19 健康成本之间权衡的当地政策决策不会是社会最优的。与没有流入的县相比，南达科他州以外的集会参加者流入量最高的县的 COVID-19 病例增加了 6.4-12.5%。我们的研究结果强调，在存在大量传染外部性的情况下，评估当地经济利益和 COVID-19 健康成本之间权衡的当地政策决策不会是社会最优的。与没有流入的县相比，南达科他州以外的集会参加者流入量最高的县的 COVID-19 病例增加了 6.4-12.5%。我们的研究结果强调，在存在大量传染外部性的情况下，评估当地经济利益和 COVID-19 健康成本之间权衡的当地政策决策不会是社会最优的。