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康涅狄格州实时 COVID-19 监测仪表板,为疫情防控提供支持:学术健康部门合作的经验教训。

A real-time COVID-19 surveillance dashboard to support epidemic response in Connecticut: lessons from an academic-health department partnership.

机构信息

Department of Epidemiology, Columbia Mailman School of Public Health, New York City, New York, USA.

Formerly The Stamford, Connecticut Department of Health, Stamford, Connecticut, USA.

出版信息

J Am Med Inform Assoc. 2022 Apr 13;29(5):958-963. doi: 10.1093/jamia/ocac025.

DOI:10.1093/jamia/ocac025
PMID:35196368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8903472/
Abstract

In response to the coronavirus disease-19 (COVID-19) pandemic, numerous institutions published COVID-19 dashboards for reporting epidemiological statistics at the county, state, or national level. However, statistics for smaller cities were often not reported, requiring these areas to develop their own data processing pipelines. For under-resourced departments of health, the development of these pipelines was challenging, leading them to rely on nonspecific and often delayed infection statistics during the pandemic. To avoid this issue, the Stamford, Connecticut Department of Health (SDH) contracted with the Columbia Mailman School of Public Health to develop an online dashboard that displays real-time case, death, test, vaccination, hospitalization, and forecast data for their city, allowing SDH to monitor trends for specific demographic and geographic groups. Insights from the dashboard allowed SDH to initiate timely and targeted testing/vaccination campaigns. The dashboard is widely used and highlights the benefit of public-academic partnerships in public health, especially during the COVID-19 pandemic.

摘要

针对新型冠状病毒肺炎(COVID-19)疫情,许多机构发布了 COVID-19 仪表盘,用于报告县、州或国家层面的流行病学统计数据。然而,较小城市的统计数据往往没有报告,这要求这些地区开发自己的数据处理管道。对于资源不足的卫生部门来说,开发这些管道具有挑战性,导致他们在疫情期间依赖非特定且往往延迟的感染统计数据。为避免这个问题,康涅狄格州斯坦福德市卫生部门(SDH)与哥伦比亚大学梅尔曼公共卫生学院签订合同,开发了一个在线仪表盘,用于显示其城市的实时病例、死亡、检测、疫苗接种、住院和预测数据,使 SDH 能够监测特定人口统计学和地理群体的趋势。从仪表盘获得的见解使 SDH 能够及时发起有针对性的检测/疫苗接种活动。该仪表盘得到了广泛应用,并突出了公共卫生领域中公立-学术合作的好处,尤其是在 COVID-19 大流行期间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a30/9006685/e2b429c336e3/ocac025f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a30/9006685/5b3d6760ce7c/ocac025f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a30/9006685/e2b429c336e3/ocac025f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a30/9006685/5b3d6760ce7c/ocac025f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a30/9006685/e2b429c336e3/ocac025f2.jpg

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