Suppr超能文献

探讨 H1N1 季节性与巴西 COVID-19 大流行的关联:一项生态学时间序列分析。

Insights into the association of H1N1 seasonality with the COVID-19 pandemic in Brazil: an ecological time series analysis.

机构信息

Afya Faculdade de Ciências Médicas, Av. Mendonça Furtado, s/n, Vila Nova, 68600-000 Bragança, PA, Brazil.

出版信息

An Acad Bras Cienc. 2024 Jul 29;96(suppl 1):e20230645. doi: 10.1590/0001-3765202420230645. eCollection 2024.

Abstract

During the COVID-19 pandemic, H1N1 seasonality disappeared worldwide. In Brazil, information on how coronavirus impacted this seasonality is scarce. In this study, we aimed to verify whether COVID-19 pandemic was associated with changes in the seasonality of H1N1, modeling the time series of H1N1 between pre-pandemic (2018 and 2019), pandemic (2020 and 2021) and post-pandemic (2022 and 2023) periods. For this purpose, we superimposed on this time series cases of COVID-19 from 2020 to 2023. Our findings highlighted that H1N1 exhibited a consistent seasonal pattern in the pre-pandemic period, with peaks mainly in months with the highest rainfall. However, this seasonality disappeared during the pandemic, with a significant decrease in the number of cases, in contrast with the predicted seasonality of H1N1 for the same period. In addition, the seasonal pattern of H1N1 in the post-pandemic showed a return to that observed in the pre-pandemic period, especially in 2023. We observed that the COVID-19 pandemic was consistently associated with changes in H1N1 seasonality in Brazil, underscoring the relative importance of monitoring patterns of respiratory syndromes to enhance our understanding of how coronavirus is associated with changes in seasonal diseases.

摘要

在 COVID-19 大流行期间,全球范围内 H1N1 的季节性消失了。在巴西,有关冠状病毒如何影响这种季节性的信息很少。在这项研究中,我们旨在验证 COVID-19 大流行是否与 H1N1 季节性的变化有关,通过对 2018 年至 2019 年(大流行前)、2020 年至 2021 年(大流行期间)和 2022 年至 2023 年(大流行后)期间的 H1N1 时间序列进行建模来实现这一目标。为此,我们将 2020 年至 2023 年的 COVID-19 病例叠加在这个时间序列上。我们的研究结果表明,H1N1 在大流行前表现出一致的季节性模式,主要高峰期在降雨量最高的月份。然而,这种季节性在大流行期间消失了,病例数量显著减少,与同期 H1N1 的预测季节性形成鲜明对比。此外,大流行后 H1N1 的季节性模式显示出回归到大流行前观察到的模式,尤其是在 2023 年。我们观察到,COVID-19 大流行与巴西 H1N1 季节性的变化一直存在关联,这突显了监测呼吸道综合征模式的相对重要性,以增强我们对冠状病毒如何与季节性疾病变化相关联的理解。

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