期刊
JOURNAL OF MEDICAL VIROLOGY
卷 92, 期 8, 页码 1316-1321出版社
WILEY
DOI: 10.1002/jmv.25636
关键词
acute respiratory infection; Brazil; epidemiology; real-time polymerase chain reaction; respiratory tract infections; slum; viruses
类别
资金
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [02/08460-6]
- European Union's Horizon 2020 program through the ZIKAlliance project [734548]
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [02/08460-6] Funding Source: FAPESP
Host population size, density, immune status, age structure, and contact rates are critical elements of virus epidemiology. Slum populations stand out from other settings and may present differences in the epidemiology of acute viral infections. We collected nasopharyngeal specimens from 282 children aged <= 5 years with acute respiratory tract infection (ARI) during 2005 to 2006 in one of the largest Brazilian slums. We conducted real-time reverse transcription-polymerase chain reaction (RT-PCR) for 16 respiratory viruses, nested RT-PCR-based typing of rhinoviruses (HRVs), and collected clinical symptoms. Viruses were common causes of respiratory disease; with >= 1 virus being detected in 65.2% of patients. We detected 15 different viruses during 1 year with a predomidnance of HRV (33.0%) and human respiratory syncytial virus (hRSV, 12.1%) infections, and a high rate of viral coinfections (28.3%). We observed seasonality of hRSV, HRV and human coronavirus infections, more severe symptoms in hRSV and influenza virus (FLU) infections and prolonged circulation of seven HRV clusters likely representing distinct serotypes according to genomic sequence distances. Potentially unusual findings included the absence of human metapneumovirus detections and lack of typical FLU seasonal patterns, which may be linked to the population size and density of the slum. Nonetheless, most epidemiological patterns were similar to other studies globally, suggesting surprising similarities of virus-associated ARI across highly diverse settings and a complex impact of population characteristics on respiratory virus epidemiology.
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