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纽约市家庭的迁移以及新泽西州、康涅狄格州和纽约县新冠病例的第二个高峰。

Migration of households from New York City and the Second Peak in Covid-19 cases in New Jersey, Connecticut and New York Counties.

作者信息

Schulman Adam, Bhanot Gyan

机构信息

Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA.

Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, 08854, USA.

出版信息

medRxiv. 2021 Mar 31:2021.03.29.21254583. doi: 10.1101/2021.03.29.21254583.

Abstract

The five boroughs of New York City (NYC) were early epicenters of the Covid-19 pandemic in the United States, with over 380,000 cases by May 31. High caseloads were also seen in nearby counties in New Jersey (NJ), Connecticut (CT) and New York (NY). The pandemic started in the area in March with an exponential rise in the number of daily cases, peaked in early April, briefly declined, and then, showed clear signs of a second peak in several counties. We will show that despite control measures such as lockdown and restriction of movement during the exponential rise in daily cases, there was a significant net migration of households from NYC boroughs to the neighboring counties in NJ, CT and NY State. We propose that the second peak in daily cases in these counties around NYC was due, in part, to the movement of people from NYC boroughs to these counties. We estimate the movement of people using "Change of Address" (CoA) data from the US Postal Service, provided under the "Freedom of Information Act" of 1967. To identify the timing of the second peak and the number of cases in it, we use a previously proposed SIR model, which accurately describes the early stages of the coronavirus pandemic in European countries. Subtracting the model fits from the data identified, we establish the timing and the number of cases, N, in the second peak. We then related the number of cases in the second peak to the county population density, P, and the excess Change of Address, E into each county using the simple model which fits the data very well with α = 0.68, β = 0.31 (R = 0.74, p = 1.3e-8). We also find that the time between the first and second peaks was proportional to the distance of the county seat from NY Penn Station, suggesting that this migration of households and disease was a directed flow and not a diffusion process. Our analysis provides a simple method to use change of address data to track the spread of an infectious agent, such as SARS-Cov-2, due to migrations away from epicenters during the initial stages of a pandemic.

摘要

纽约市的五个行政区是美国新冠疫情早期的震中,截至5月31日,病例超过38万例。新泽西州(NJ)、康涅狄格州(CT)和纽约州(NY)附近的县也出现了高病例数。疫情于3月在该地区爆发,每日病例数呈指数级增长,4月初达到峰值,随后短暂下降,然后在几个县出现了明显的第二次峰值迹象。我们将表明,尽管在每日病例数呈指数级增长期间采取了封锁和限制行动等控制措施,但仍有大量家庭从纽约市行政区净迁移到新泽西州、康涅狄格州和纽约州的邻近县。我们认为,纽约市周边这些县每日病例数的第二次峰值部分归因于人们从纽约市行政区向这些县的流动。我们使用根据1967年《信息自由法》提供的美国邮政服务的“地址变更”(CoA)数据来估计人口流动情况。为了确定第二次峰值的时间及其病例数,我们使用了先前提出的SIR模型,该模型准确描述了欧洲国家新冠疫情的早期阶段。从识别出的数据中减去模型拟合值,我们确定了第二次峰值的时间和病例数N。然后,我们使用简单模型将第二次峰值中的病例数与县人口密度P以及每个县的地址变更超额值E相关联,该模型与数据拟合得非常好,α = 0.68,β = 0.31(R = 0.74,p = 1.3e - 8)。我们还发现,第一次和第二次峰值之间的时间与县城到纽约宾夕法尼亚车站的距离成正比,这表明这种家庭和疾病的迁移是有方向的流动,而不是扩散过程。我们的分析提供了一种简单方法,可利用地址变更数据来追踪传染病病原体(如SARS-CoV-2)在疫情初期因从震中迁移而导致的传播情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3f/8020985/181dcae6ca1f/nihpp-2021.03.29.21254583-f0003.jpg

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