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An evidence review of face masks against COVID-19.针对 COVID-19 的口罩有效性评估综述
Proc Natl Acad Sci U S A. 2021 Jan 26;118(4). doi: 10.1073/pnas.2014564118.
2
Face masks considerably reduce COVID-19 cases in Germany.口罩大大减少了德国的 COVID-19 病例。
Proc Natl Acad Sci U S A. 2020 Dec 22;117(51):32293-32301. doi: 10.1073/pnas.2015954117. Epub 2020 Dec 3.
3
City-Scale Agent-Based Simulators for the Study of Non-pharmaceutical Interventions in the Context of the COVID-19 Epidemic: IISc-TIFR COVID-19 City-Scale Simulation Team.用于研究新冠疫情背景下非药物干预措施的基于智能体的城市规模模拟器:印度科学研究所-塔塔基础研究所新冠疫情城市规模模拟团队
J Indian Inst Sci. 2020;100(4):809-847. doi: 10.1007/s41745-020-00211-3. Epub 2020 Nov 12.
4
Association of Country-wide Coronavirus Mortality with Demographics, Testing, Lockdowns, and Public Wearing of Masks.全国冠状病毒死亡率与人口统计学、检测、封锁和公众戴口罩的关系。
Am J Trop Med Hyg. 2020 Dec;103(6):2400-2411. doi: 10.4269/ajtmh.20-1015. Epub 2020 Oct 26.
5
Paradigm Shifts in Cardiac Care: Lessons Learned From COVID-19 at a Large New York Health System.心脏护理的范式转变:从纽约大型医疗系统的 COVID-19 中学到的经验教训。
Curr Probl Cardiol. 2021 Mar;46(3):100675. doi: 10.1016/j.cpcardiol.2020.100675. Epub 2020 Jul 31.
6
Effects of Weather on Coronavirus Pandemic.天气对冠状病毒大流行的影响。
Int J Environ Res Public Health. 2020 Jul 27;17(15):5399. doi: 10.3390/ijerph17155399.
7
Rationing care by frailty during the COVID-19 pandemic.在 COVID-19 大流行期间,根据虚弱程度分配医疗护理。
Age Ageing. 2021 Jan 8;50(1):7-10. doi: 10.1093/ageing/afaa171.
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PEEP/ FIO2 ARDSNet Scale Grouping of a Single Ventilator for Two Patients: Modeling Tidal Volume Response.两名患者使用一台呼吸机时的PEEP/FiO₂ ARDSNet量表分组:潮气量反应建模
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9
Mask use during COVID-19: A risk adjusted strategy.新冠期间的口罩使用:风险调整策略。
Environ Pollut. 2020 Nov;266(Pt 1):115099. doi: 10.1016/j.envpol.2020.115099. Epub 2020 Jun 25.
10
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县级层面 COVID-19 口罩令对医院资源消耗和死亡率影响的分析。

Analysis of the Effects of COVID-19 Mask Mandates on Hospital Resource Consumption and Mortality at the County Level.

机构信息

From the US Army Institute of Surgical Research and the Brooke Army Medical Center, JBSA Fort Sam Houston, Texas, the Uniformed Services University of the Health Sciences, Bethesda, Maryland, the Madigan Army Medical Center, Joint Base Lewis McChord, Washington, the 2nd Brigade Combat Team, 4th Infantry Division, Fort Carson, Colorado, and the 121st Field Hospital, Camp Humphreys, Republic of Korea.

出版信息

South Med J. 2021 Sep;114(9):597-602. doi: 10.14423/SMJ.0000000000001294.

DOI:10.14423/SMJ.0000000000001294
PMID:34480194
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8395971/
Abstract

OBJECTIVES

Coronavirus disease 2019 (COVID-19) threatens vulnerable patient populations, resulting in immense pressures at the local, regional, national, and international levels to contain the virus. Laboratory-based studies demonstrate that masks may offer benefit in reducing the spread of droplet-based illnesses, but few data are available to assess mask effects via executive order on a population basis. We assess the effects of a county-wide mask order on per-population mortality, intensive care unit (ICU) utilization, and ventilator utilization in Bexar County, Texas.

METHODS

We used publicly reported county-level data to perform a mixed-methods before-and-after analysis along with other sources of public data for analyses of covariance. We used a least-squares regression analysis to adjust for confounders. A Texas state-level mask order was issued on July 3, 2020, followed by a Bexar County-level order on July 15, 2020. We defined the control period as June 2 to July 2 and the postmask order period as July 8, 2020-August 12, 2020, with a 5-day gap to account for the median incubation period for cases; longer periods of 7 and 10 days were used for hospitalization and ICU admission/death, respectively. Data are reported on a per-100,000 population basis using respective US Census Bureau-reported populations.

RESULTS

From June 2, 2020 through August 12, 2020, there were 40,771 reported cases of COVID-19 within Bexar County, with 470 total deaths. The average number of new cases per day within the county was 565.4 (95% confidence interval [CI] 394.6-736.2). The average number of positive hospitalized patients was 754.1 (95% CI 657.2-851.0), in the ICU was 273.1 (95% CI 238.2-308.0), and on a ventilator was 170.5 (95% CI 146.4-194.6). The average deaths per day was 6.5 (95% CI 4.4-8.6). All of the measured outcomes were higher on average in the postmask period as were covariables included in the adjusted model. When adjusting for traffic activity, total statewide caseload, public health complaints, and mean temperature, the daily caseload, hospital bed occupancy, ICU bed occupancy, ventilator occupancy, and daily mortality remained higher in the postmask period.

CONCLUSIONS

There was no reduction in per-population daily mortality, hospital bed, ICU bed, or ventilator occupancy of COVID-19-positive patients attributable to the implementation of a mask-wearing mandate.

摘要

目的

2019 年冠状病毒病(COVID-19)威胁着弱势群体,导致地方、地区、国家和国际各级都面临着巨大的压力,需要采取措施来控制病毒。基于实验室的研究表明,口罩可能有助于减少飞沫传播疾病的传播,但很少有数据可以评估口罩在人群基础上通过行政命令的效果。我们评估了德克萨斯州贝克萨尔县(Bexar County)全县范围内戴口罩命令对每人口死亡率、重症监护病房(ICU)使用率和呼吸机使用率的影响。

方法

我们使用公开报告的县级数据,进行了一项混合方法的前后分析,并结合了其他公共数据源的协方差分析。我们使用最小二乘法回归分析来调整混杂因素。德克萨斯州于 2020 年 7 月 3 日发布了州级口罩令,随后贝克萨尔县于 2020 年 7 月 15 日发布了县级口罩令。我们将对照期定义为 6 月 2 日至 7 月 2 日,将戴口罩命令后的时期定义为 2020 年 7 月 8 日至 8 月 12 日,中间间隔 5 天以考虑病例的中位数潜伏期;分别使用 7 天和 10 天的较长时间间隔来住院和 ICU 入院/死亡。数据以每 10 万人为单位报告,使用美国人口普查局报告的相应人口。

结果

从 2020 年 6 月 2 日至 8 月 12 日,贝克萨尔县报告了 40771 例 COVID-19 病例,总共有 470 人死亡。该县每天新增病例的平均数为 565.4(95%置信区间[CI] 394.6-736.2)。每天平均住院的阳性患者数量为 754.1(95%CI 657.2-851.0),在 ICU 的为 273.1(95%CI 238.2-308.0),使用呼吸机的为 170.5(95%CI 146.4-194.6)。每天平均死亡人数为 6.5(95%CI 4.4-8.6)。在戴口罩后的时期,所有测量结果的平均值都更高,包括调整模型中的协变量。在调整交通活动、全州总病例数、公共卫生投诉和平均温度后,戴口罩后的时期每天的病例数、医院床位占用率、ICU 床位占用率、呼吸机占用率和每日死亡率仍然更高。

结论

由于实施了戴口罩的规定,贝克萨尔县每人口的每日死亡率、医院床位、ICU 床位或 COVID-19 阳性患者使用呼吸机的人数并没有减少。