Suppr超能文献

使用地理编码识别群居性居住环境中的 COVID-19 疫情爆发:旧金山在单人间住宿酒店的疫情应对措施。

Using Geocoding to Identify COVID-19 Outbreaks in Congregate Residential Settings: San Francisco's Outbreak Response in Single-Room Occupancy Hotels.

机构信息

Disease Prevention and Control Branch, Population Health Division, San Francisco Department of Public Health, San Francisco, CA, USA.

COVID Command Center, San Francisco Department of Public Health, San Francisco, CA, USA.

出版信息

Public Health Rep. 2023 Jan-Feb;138(1):7-13. doi: 10.1177/00333549221128301. Epub 2022 Oct 14.

Abstract

More than 500 single-room occupancy hotels (SROs), a type of low-cost congregate housing with shared bathrooms and kitchens, are available in San Francisco. SRO residents include essential workers, people with disabilities, and multigenerational immigrant families. In March 2020, with increasing concerns about the potential for rapid transmission of COVID-19 among a population with disproportionate rates of comorbidity, poor access to care, and inability to self-isolate, the San Francisco Department of Public Health formed an SRO outbreak response team to identify and contain COVID-19 clusters in this congregate residential setting. Using address-matching geocoding, the team conducted active surveillance to identify new cases and outbreaks of COVID-19 at SROs. An outbreak was defined as 3 separate households in the SRO with a positive test result for COVID-19. From March 2020 through February 2021, the SRO outbreak response team conducted on-site mass testing of all residents at 52 SROs with outbreaks identified through geocoding. The rate of positive COVID-19 tests was significantly higher at SROs with outbreaks than at SROs without outbreaks (12.7% vs 6.4%; < .001). From March through May 2020, the rate of COVID-19 cases among SRO residents was higher than among residents of other settings (ie, non-SRO residents), before decreasing and remaining at an equal level to non-SRO residents during later periods of 2020. The annual case fatality rate for SRO residents and non-SRO residents was similar (1.8% vs 1.5%). This approach identified outbreaks in a setting at high risk of COVID-19 and facilitated rapid deployment of resources. The geocoding surveillance approach could be used for other diseases and in any setting for which a list of addresses is available.

摘要

旧金山有 500 多家单人客房旅馆(SRO),这是一种低成本的群居住房,设有共用浴室和厨房。SRO 的居民包括基本工人、残疾人和多代移民家庭。2020 年 3 月,随着对人口中 COVID-19 快速传播的潜在担忧增加,这些人患有不成比例的合并症、护理机会有限以及无法自我隔离,旧金山公共卫生部成立了 SRO 疫情应对小组,以确定和控制这种群居住宅环境中的 COVID-19 集群。该团队使用地址匹配地理编码,主动监测以识别 SRO 中的新病例和 COVID-19 疫情爆发。疫情爆发被定义为 SRO 中 3 个单独的家庭,他们的 COVID-19 检测结果呈阳性。从 2020 年 3 月到 2021 年 2 月,SRO 疫情应对小组对通过地理编码确定的爆发疫情的 52 家 SRO 中的所有居民进行了现场大规模检测。爆发疫情的 SRO 中 COVID-19 阳性检测率明显高于没有爆发疫情的 SRO(12.7%比 6.4%;<0.001)。从 2020 年 3 月到 5 月,SRO 居民的 COVID-19 病例率高于其他环境(即非 SRO 居民)中的居民,然后在 2020 年后期下降并与非 SRO 居民持平。SRO 居民和非 SRO 居民的年病死率相似(1.8%比 1.5%)。这种方法在 COVID-19 高风险环境中识别出了疫情,并迅速部署了资源。地理编码监测方法可用于其他疾病和任何有地址清单的环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af84/9730165/d469b4ce38b3/10.1177_00333549221128301-fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验