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Nat Commun:美国的新冠情况到底如何了?

2020-12-04 haibei MedSci原创

截至2020年6月1日,美国疾病控制和预防中心报告,美国有104232例确诊或可能的COVID-19相关死亡病例。这是下一个受影响最严重国家报告死亡人数的两倍多。

目前,美国首例由COVID-19引起的死亡事件在2月6日发生在加州圣克拉拉县。在整个2020年3月,美国各州政府实施了各种非药物干预措施(NPIs),如学校停课和在家待命,以限制SARS-CoV-2的传播,并确保COVID-19严重病例的数量不超过卫生系统的能力。

2020年4月,美国(US)归因于COVID-19的死亡人数超过了意大利。

Courtemanche等人使用事件研究模型确定,这种NPIs成功地降低了美国各县COVID-19病例的增长率。

截至2020年6月1日,美国疾病控制和预防中心报告,美国有104232例确诊或可能的COVID-19相关死亡病例。这是下一个受影响最严重国家报告死亡人数的两倍多。

最近,研究人员在Nature Communications发文,其利用公开的死亡数据,在贝叶斯层次半机制框架内,联合建立了美国各州一级的疫情模型。

对于每个州,研究人员估计了已被感染的个体数量、目前具有传染性的个体数量和随时间变化的繁殖数量(由感染者造成的二次感染的平均数量)。

研究人员利用流动性的变化来把握非药物干预和其他行为变化对SARS-CoV-2传播速度的影响。其估计,6月1日,Rt仅在23个州低于1。研究人员还估计美国总人口的3.7%[3.4%-4.0%]已被感染,各州之间差异较大,约0.01%的人口具有传染性。

该研究展示了良好的3周死亡模型预测,误差较小,可信区间覆盖率很高。

 

原始出处:

H. Juliette T. Unwin et al. State-level tracking of COVID-19 in the United States. Nature Communications (2020). 

 

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    2020-12-29 liye789132251
  2. [GetPortalCommentsPageByObjectIdResponse(id=1884835, encodeId=a20a18848350f, content=<a href='/topic/show?id=3b2112532d8' target=_blank style='color:#2F92EE;'>#Nat#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=66, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=12532, encryptionId=3b2112532d8, topicName=Nat)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=2e6f107, createdName=liye789132251, createdTime=Tue Dec 29 22:15:39 CST 2020, time=2020-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=2087849, encodeId=962d208e849b3, content=<a href='/topic/show?id=490750196b' target=_blank style='color:#2F92EE;'>#COMMUN#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=66, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=5019, encryptionId=490750196b, topicName=COMMUN)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=7931272, createdName=liuli5079, createdTime=Mon Mar 01 05:15:39 CST 2021, time=2021-03-01, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=905121, encodeId=f336905121b1, content=言简意赅,特别受用, beContent=null, objectType=article, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20201204/049b07eb9838407a9de80d92834eede1/04596ea802e342bfaba196f9604cb91c.jpg, createdBy=11325430649, createdName=ms3000001340106445, createdTime=Sat Dec 05 09:57:26 CST 2020, time=2020-12-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=904986, encodeId=079d904986c9, content=嗯。。, beContent=null, objectType=article, channel=null, level=null, likeNumber=109, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a0e42452810, createdName=挖挖机, createdTime=Fri Dec 04 21:50:11 CST 2020, time=2020-12-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1028850, encodeId=2618102885088, content=新冠肺炎,疫情何时才能消失, beContent=null, objectType=article, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=公卫新人, createdTime=Fri Dec 04 18:15:39 CST 2020, time=2020-12-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=904896, encodeId=cef89048964d, content=这是下一个受影响最严重国家报告死亡人数的两倍多。。。。, beContent=null, objectType=article, channel=null, level=null, likeNumber=99, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20201120/5008534db22c474a844fbd107ff83af2/d3e20fc133b542208ff15e7f2b575329.jpg, createdBy=c7015311102, createdName=Jessie Zhang, createdTime=Fri Dec 04 16:31:27 CST 2020, time=2020-12-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=904873, encodeId=d09c9048e303, content=<a href='/topic/show?id=46ce580e865' target=_blank style='color:#2F92EE;'>#新冠肺炎#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=110, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=58078, encryptionId=46ce580e865, topicName=新冠肺炎)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=fbc45433548, createdName=ms5000001266883663, createdTime=Fri Dec 04 15:23:55 CST 2020, time=2020-12-04, status=1, ipAttribution=)]
    2021-03-01 liuli5079
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    2020-12-05 ms3000001340106445

    言简意赅,特别受用

    0

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    2020-12-04 挖挖机

    嗯。。

    0

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    2020-12-04 公卫新人

    新冠肺炎,疫情何时才能消失

    0

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    2020-12-04 Jessie Zhang

    这是下一个受影响最严重国家报告死亡人数的两倍多。。。。

    0

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