Using control charts to understand community variation in COVID-19.
Using control charts to understand community variation in COVID-19.
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DOI：
10.1371/journal.pone.0248500
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Provost LP
中科院分区：
文献类型：
--
作者：
Inkelas M;Blair C;Furukawa D;Manuel VG;Malenfant JH;Martin E;Emeruwa I;Kuo T;Arangua L;Robles B;Provost LP
随着2019冠状病毒病（COVID-19）大流行的发展，决策者需要采取行动的信号。我们的目标是展示统计过程控制的新用途，以提供及时和可解释的COVID-19数据显示，为当地缓解和遏制策略提供信息。医疗保健和其他行业使用统计过程控制来研究变化和分解数据，以了解过程和系统的行为并对其进行干预。我们开发了一个州（加州）内县和市/社区级别的控制图，以说明其对决策者的潜在价值。我们发现，COVID-19的发病率因地区和次区域而异，有指数和非指数增长和下降的时期。这种分类提供了决策者可以用来应对这一流行病的粒度。附加说明的时间序列介绍将事件和政策与观察到的数据联系起来，这可能有助于动员和指导居民和其他利益攸关方的行动。政策制定者和社区需要获得相关、准确的数据，以应对不断演变的COVID-19疫情。由于控制图在实时决策中可能易于使用和解释，并在社区有意义的层面上就流行病进行沟通，因此控制图可能很有价值。
Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities.
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影响因子：
5.4
作者：
Neuhauser, Duncan;Provost, Lloyd;Bergman, Bo
通讯作者：
Bergman, Bo
影响因子：
1.2
作者：
Perla, Rocco J.;Provost, Lloyd P.;Parry, Gareth J.
通讯作者：
Parry, Gareth J.
影响因子：
2.3
作者：
Finnerty, Patricia;Provost, Lloyd;Berns, Scott
通讯作者：
Berns, Scott
DOI：
10.1002/ajmg.b.32445
发表时间：
2016-09
期刊：
American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
影响因子：
--
作者：
Duarte RRR;Troakes C;Nolan M;Srivastava DP;Murray RM;Bray NJ
通讯作者：
Bray NJ
影响因子：
--
作者：
Benneyan, JC;Lloyd, RC;Plsek, PE
通讯作者：
Plsek, PE