Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic.
Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic.
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DOI：
10.1371/journal.pone.0239572
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Ratnadiwakara D
中科院分区：
文献类型：
--
作者：
Narayanan RP;Nordlund J;Pace RK;Ratnadiwakara D
社交距离是一种旨在减少COVID-19传播的非药物策略，可能是因为个人自愿与他人保持距离以避免感染疾病。另外，也可能是由于地方当局施加的管辖限制。我们运行简化形式的模型，社会距离作为县级外生人口变量和司法固定效应的函数为49个州，以评估人口和司法效应在解释社会距离行为方面的相对贡献。为了考虑传染病可能的空间方面，我们还模拟了与周边县人口变量相关的溢出效应，并考虑了依赖于周边县人口变量的干扰。我们每周运行模型，并检查自COVID-19疫情在美国爆发以来估计系数随时间的演变。这些估计的系数表达了能够并选择呆在家里以避免疾病的个人的显示偏好。使用手机跟踪数据测量的居家行为表现出相当大的横截面变化，从2020年1月底到2020年3月底增加了9倍以上，然后到2020年6月中旬下降了约50%。我们的估计结果表明，人口外生变量解释这种变化比从司法固定效应的预测。此外，从人口外生变量和司法固定效应的解释显示了一个不断发展的相关性，在样本期内，最初部分抵消，并最终相互加强。此外，预测的社会距离，从人口外生变量显示大量的空间自回归依赖，表明集群的社会距离行为。居家行为的差异性增加，加上高度的空间依赖性，可能导致社会距离的热点和冷点相对集中，这对疾病的传播和缓解具有影响。
Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced form models of social distancing as a function of county-level exogenous demographic variables and jurisdictional fixed effects for 49 states to assess the relative contributions of demographic and jurisdictional effects in explaining social distancing behavior. To allow for possible spatial aspects of a contagious disease, we also model the spillovers associated with demographic variables in surrounding counties as well as allow for disturbances that depend upon those in surrounding counties. We run our models weekly and examine the evolution of the estimated coefficients over time since the onset of the COVID-19 pandemic in the United States. These estimated coefficients express the revealed preferences of individuals who were able to and chose to stay at home to avoid the disease. Stay-at-home behavior measured using cell phone tracking data exhibits considerable cross-sectional variation, increasing over nine-fold from the end of January 2020 to the end of March 2020, and then decreasing by about 50% through mid-June 2020. Our estimation results show that demographic exogenous variables explain substantially more of this variation than predictions from jurisdictional fixed effects. Moreover, the explanations from demographic exogenous variables and jurisdictional fixed effects show an evolving correlation over the sample period, initially partially offsetting, and eventually reinforcing each other. Furthermore, the predicted social distance from demographic exogenous variables shows substantial spatial autoregressive dependence, indicating clustering in social distancing behavior. The increased variance of stay-at-home behavior coupled with the high level of spatial dependence can result in relatively intense hotspots and coldspots of social distance, which has implications for disease spread and mitigation.
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