It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US.
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US.
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DOI：
10.1038/s41746-021-00523-3
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发表时间：
2021-10-27
影响因子：
15.2
通讯作者：
Fox EB
中科院分区：
文献类型：
--
作者：
Jewell S;Futoma J;Hannah L;Miller AC;Foti NJ;Fox EB
限制人际交往是限制SARS-CoV-2传播的一项重要技术。尽管早期研究发现，在美国最初爆发的疫情中，手机移动与感染传播之间存在很强的联系，但尚不清楚这种关系是否在不同地点和时间持续存在。我们提出了一个可解释的统计模型，以确定流动性和感染率之间的时空变化关系。利用美国1年的县级数据，我们发现，在2020年春季，人口最多的县，人口流动性的急剧下降往往与感染率的下降同时发生。然而，这种联系在其他地点和时间上有很大的不同。我们的研究结果对模型的灵活性很敏感，因为更严格的模型平均了局部效应并掩盖了大部分时空变化。我们得出的结论是，流动性似乎不是感染率的可靠领先指标，这可能具有重要的政策含义。
Restricting in-person interactions is an important technique for limiting the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Although early research found strong associations between cell phone mobility and infection spread during the initial outbreaks in the United States, it is unclear whether this relationship persists across locations and time. We propose an interpretable statistical model to identify spatiotemporal variation in the association between mobility and infection rates. Using 1 year of US county-level data, we found that sharp drops in mobility often coincided with declining infection rates in the most populous counties in spring 2020. However, the association varied considerably in other locations and across time. Our findings are sensitive to model flexibility, as more restrictive models average over local effects and mask much of the spatiotemporal variation. We conclude that mobility does not appear to be a reliable leading indicator of infection rates, which may have important policy implications.
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影响因子：
16.6
作者：
Nouvellet P;Bhatia S;Cori A;Ainslie KEC;Baguelin M;Bhatt S;Boonyasiri A;Brazeau NF;Cattarino L;Cooper LV;Coupland H;Cucunuba ZM;Cuomo-Dannenburg G;Dighe A;Djaafara BA;Dorigatti I;Eales OD;van Elsland SL;Nascimento FF;FitzJohn RG;Gaythorpe KAM;Geidelberg L;Green WD;Hamlet A;Hauck K;Hinsley W;Imai N;Jeffrey B;Knock E;Laydon DJ;Lees JA;Mangal T;Mellan TA;Nedjati-Gilani G;Parag KV;Pons-Salort M;Ragonnet-Cronin M;Riley S;Unwin HJT;Verity R;Vollmer MAC;Volz E;Walker PGT;Walters CE;Wang H;Watson OJ;Whittaker C;Whittles LK;Xi X;Ferguson NM;Donnelly CA
通讯作者：
Donnelly CA
影响因子：
64.8
作者：
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通讯作者：
Tatem, Andrew J.
影响因子：
56.3
作者：
Badr, Hamada S.;Du, Hongru;Gardner, Lauren M.
通讯作者：
Gardner, Lauren M.
DOI：
10.1016/s2589-7500(20)30293-4
发表时间：
2021-03
期刊：
The Lancet. Digital health
影响因子：
--
作者：
Rader B;White LF;Burns MR;Chen J;Brilliant J;Cohen J;Shaman J;Brilliant L;Kraemer MUG;Hawkins JB;Scarpino SV;Astley CM;Brownstein JS
通讯作者：
Brownstein JS
影响因子：
9.8
作者：
Carteni, Armando;Francesco, Luigi Di;Martino, Maria
通讯作者：
Martino, Maria