Suppr超能文献

评估 COVID-19 干预措施对北京和香港流感样疾病的影响:一项观察性和建模研究。

Assessing the impact of COVID-19 interventions on influenza-like illness in Beijing and Hong Kong: an observational and modeling study.

机构信息

School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100073, China.

Beijing Centre for Disease Prevention and Control, Beijing, 100013, China.

出版信息

Infect Dis Poverty. 2023 Feb 16;12(1):11. doi: 10.1186/s40249-023-01061-8.

Abstract

BACKGROUND

The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China.

METHODS

We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011-2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020-2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020-2021.

RESULTS

The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011-2019, with an obvious winter-spring seasonality in Beijing. During the 2020-2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, "Cancelling public events" and "Restrictions on internal travel" measures played an important role in the reduction of ILI in Beijing, while the "restrictions on international travel" was statistically most associated with ILI reductions in the Hong Kong SAR.

CONCLUSIONS

Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future.

摘要

背景

在存在其他已知季节性驱动因素的情况下, 2019 年冠状病毒病(COVID-19)相关非药物干预措施(NPIs)对流感活动的影响尚不清楚,尤其是在市级层面。本研究旨在评估 NPIs 对北京和中国香港特别行政区(SAR)门诊流感样疾病(ILI)就诊的影响。

方法

我们描述性地分析了 2011 年至 2021 年每周 ILI 计数、9 项 NPI 指标、平均温度、相对湿度和绝对湿度的时间特征。分别建立 2011-2019 年数据的广义加性模型(GAM),以预测 2020-2021 年北京和香港 SAR 在没有 COVID-19 干预情况下的每周 ILI 计数。在 2020-2021 年的上述情况下,GAM 模型进一步用于评估在其他季节性驱动因素存在的情况下,每个单独或联合 NPI 对每周 ILI 计数的潜在影响。

结果

2011-2019 年,北京和香港 SAR 的每周 ILI 计数在各年和各月波动,北京呈明显的冬春季季节性。在 2020-2021 赛季,北京和香港 SAR 的观察到的每周 ILI 计数均明显低于过去 9 个流感季节,分别下降了 47.5%(95%置信区间(CI):42.3%,52.2%)和 60.0%(95%CI:58.6%,61.1%)。这两个城市的观察结果也仅分别占 COVID-19 无 NPI 情况下 GAM 模型估计值的 40.2%(95%CI:35.4%,45.3%)和 58.0%(95%CI:54.1%,61.5%)。我们的研究表明,“取消公共活动”和“限制内部旅行”措施在北京降低 ILI 方面发挥了重要作用,而“限制国际旅行”与香港 SAR 的 ILI 减少具有统计学上的最大相关性。

结论

我们的研究表明,2020-2021 年,COVID-19 非药物干预措施在存在其他季节性驱动因素的情况下,降低了北京和香港 SAR 的门诊 ILI 就诊率。在具有不同地方情况的城市中,可能需要针对不同的严格程度采取一些非药物干预措施,以减轻未来严重流感株或其他呼吸道感染引起的 ILI 负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fc3/9933365/80502ad61c82/40249_2023_1061_Fig1_HTML.jpg

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