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从 2009 年至 2020 年孟加拉国流感哨点监测中严重急性呼吸道感染聚集性病例鉴定中吸取的教训。

Lessons learned from identifying clusters of severe acute respiratory infections with influenza sentinel surveillance, Bangladesh, 2009-2020.

机构信息

Infectious Diseases Division, icddr,b Dhaka Bangladesh.

Nuffield Department of Medicine University of Oxford Oxford UK.

出版信息

Influenza Other Respir Viruses. 2023 Sep 22;17(9):e13201. doi: 10.1111/irv.13201. eCollection 2023 Sep.

Abstract

BACKGROUND

We explored whether hospital-based surveillance is useful in detecting severe acute respiratory infection (SARI) clusters and how often these events result in outbreak investigation and community mitigation.

METHODS

During May 2009-December 2020, physicians at 14 sentinel hospitals prospectively identified SARI clusters (i.e., ≥2 SARI cases who developed symptoms ≤10 days of each other and lived <30 min walk or <3 km from each other). Oropharyngeal and nasopharyngeal swabs were tested for influenza and other respiratory viruses by real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We describe the demographic of persons within clusters, laboratory results, and outbreak investigations.

RESULTS

Field staff identified 464 clusters comprising 1427 SARI cases (range 0-13 clusters per month). Sixty percent of clusters had three, 23% had two, and 17% had ≥4 cases. Their median age was 2 years (inter-quartile range [IQR] 0.4-25) and 63% were male. Laboratory results were available for the 464 clusters with a median of 9 days (IQR = 6-13 days) after cluster identification. Less than one in five clusters had cases that tested positive for the same virus: respiratory syncytial virus (RSV) in 58 (13%), influenza viruses in 24 (5%), human metapneumovirus (HMPV) in five (1%), human parainfluenza virus (HPIV) in three (0.6%), adenovirus in two (0.4%). While 102/464 (22%) had poultry exposure, none tested positive for influenza A (H5N1) or A (H7N9). None of the 464 clusters led to field deployments for outbreak response.

CONCLUSIONS

For 11 years, none of the hundreds of identified clusters led to an emergency response. The value of this event-based surveillance might be improved by seeking larger clusters, with stronger epidemiologic ties or decedents.

摘要

背景

我们探讨了基于医院的监测在发现严重急性呼吸道感染 (SARI) 聚集病例中的作用,以及这些聚集病例中有多少会导致暴发调查和社区缓解措施的实施。

方法

在 2009 年 5 月至 2020 年 12 月期间,14 家哨点医院的医生前瞻性地识别了 SARI 聚集病例(即≥2 例 SARI 病例,且症状出现时间相差≤10 天,居住距离彼此步行<30 分钟或<3 公里)。通过实时逆转录聚合酶链反应(rRT-PCR)对咽拭子和鼻咽拭子进行流感和其他呼吸道病毒检测。我们描述了聚集病例中患者的人口统计学特征、实验室结果和暴发调查情况。

结果

现场工作人员共识别出 464 个聚集病例,共包含 1427 例 SARI 病例(每月 0-13 个聚集病例)。60%的聚集病例有 3 例病例,23%的聚集病例有 2 例病例,17%的聚集病例有≥4 例病例。这些聚集病例的中位年龄为 2 岁(四分位距 [IQR] 0.4-25),其中 63%为男性。在识别出的 464 个聚集病例中,有 464 个实验室结果,中位时间为聚集病例识别后 9 天(IQR=6-13 天)。不到五分之一的聚集病例的检测结果为相同病毒阳性:呼吸道合胞病毒(RSV)阳性 58 例(13%),流感病毒阳性 24 例(5%),人偏肺病毒(HMPV)阳性 5 例(1%),人副流感病毒(HPIV)阳性 3 例(0.6%),腺病毒阳性 2 例(0.4%)。虽然 102/464(22%)例聚集病例有禽类接触史,但没有病例检测出甲型流感病毒(H5N1)或甲型流感病毒(H7N9)阳性。464 个聚集病例中没有一个导致现场部署以应对疫情暴发。

结论

在 11 年的时间里,数百个识别出的聚集病例中没有一个导致紧急应对。通过寻找具有更强流行病学联系或死亡病例的更大规模聚集病例,这种基于事件的监测的价值可能会得到提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863d/10515138/882008c11836/IRV-17-e13201-g003.jpg

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