Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Eisner Health, Los Angeles, CA, 90015, USA.
BMC Infect Dis. 2022 Aug 15;22(1):691. doi: 10.1186/s12879-022-07666-y.
Significant immune escape by the Omicron variant, along with the emergence of widespread worry fatigue, have called into question the robustness of the previously observed relation between population mobility and COVID-19 incidence.
We employed principal component analysis to construct a one-dimensional summary indicator of six Google mobility categories. We related this mobility indicator to case incidence among 111 of the most populous U.S. counties during the Omicron surge from December 2021 through February 2022.
Reported COVID-19 incidence peaked earlier and declined more rapidly among those counties exhibiting more extensive decline in mobility between December 20 and January 3. Based upon a fixed-effects, longitudinal cohort model, we estimated that every 1% decline in mobility between December 20 and January 3 was associated with a 0.63% decline in peak incidence during the week ending January 17 (95% confidence interval, 0.40-0.86%). Based upon a cross-sectional analysis including mean household size and vaccination participation as covariates, we estimated that the same 1% decline in mobility was associated with a 0.36% decline in cumulative reported COVID-19 incidence from January 10 through February 28 (95% CI, 0.18-0.54%).
Omicron did not simply sweep through the U.S. population until it ran out of susceptible individuals to infect. To the contrary, a significant fraction managed to avoid infection by engaging in risk-mitigating behaviors. More broadly, the behavioral response to perceived risk should be viewed as an intrinsic component of the natural course of epidemics in humans.
奥密克戎变体的显著免疫逃逸，以及广泛的担忧疲劳的出现，使得人们对先前观察到的人口流动与 COVID-19 发病率之间的关系的稳健性产生了质疑。
我们采用主成分分析构建了一个由六个谷歌移动类别组成的一维综合指标。我们将这一流动指标与 2021 年 12 月至 2022 年 2 月奥密克戎激增期间美国 111 个人口最多的县的病例发病率相关联。
报告的 COVID-19 发病率在移动性下降幅度较大的县中更早达到峰值，并在 12 月 20 日至 1 月 3 日之间更快下降。基于固定效应的纵向队列模型，我们估计，在 12 月 20 日至 1 月 3 日之间，每下降 1%的流动性与在 1 月 17 日结束的那一周发病率峰值下降 0.63%（95%置信区间，0.40-0.86%）有关。基于包括家庭平均规模和疫苗接种参与率作为协变量的横断面分析，我们估计，同样的 1%的流动性下降与 1 月 10 日至 2 月 28 日报告的 COVID-19 累计发病率下降 0.36%（95%CI，0.18-0.54%）有关。
奥密克戎并不是简单地席卷美国人口，直到它感染了所有易感人群。相反，相当一部分人通过采取降低风险的行为来避免感染。更广泛地说，对感知风险的行为反应应被视为人类传染病自然过程的内在组成部分。
