Forecasting of influenza activity and associated hospital admission burden and estimating the impact of COVID-19 pandemic on 2019/20 winter season in Hong Kong.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2024-07-31 eCollection Date: 2024-07-01 DOI:10.1371/journal.pcbi.1012311
Yiu-Chung Lau, Songwei Shan, Dong Wang, Dongxuan Chen, Zhanwei Du, Eric H Y Lau, Daihai He, Linwei Tian, Peng Wu, Benjamin J Cowling, Sheikh Taslim Ali
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Abstract

Like other tropical and subtropical regions, influenza viruses can circulate year-round in Hong Kong. However, during the COVID-19 pandemic, there was a significant decrease in influenza activity. The objective of this study was to retrospectively forecast influenza activity during the year 2020 and assess the impact of COVID-19 public health social measures (PHSMs) on influenza activity and hospital admissions in Hong Kong. Using weekly surveillance data on influenza virus activity in Hong Kong from 2010 to 2019, we developed a statistical modeling framework to forecast influenza virus activity and associated hospital admissions. We conducted short-term forecasts (1-4 weeks ahead) and medium-term forecasts (1-13 weeks ahead) for the year 2020, assuming no PHSMs were implemented against COVID-19. We estimated the reduction in transmissibility, peak magnitude, attack rates, and influenza-associated hospitalization rate resulting from these PHSMs. For short-term forecasts, mean ambient ozone concentration and school holidays were found to contribute to better prediction performance, while absolute humidity and ozone concentration improved the accuracy of medium-term forecasts. We observed a maximum reduction of 44.6% (95% CI: 38.6% - 51.9%) in transmissibility, 75.5% (95% CI: 73.0% - 77.6%) in attack rate, 41.5% (95% CI: 13.9% - 55.7%) in peak magnitude, and 63.1% (95% CI: 59.3% - 66.3%) in cumulative influenza-associated hospitalizations during the winter-spring period of the 2019/2020 season in Hong Kong. The implementation of PHSMs to control COVID-19 had a substantial impact on influenza transmission and associated burden in Hong Kong. Incorporating information on factors influencing influenza transmission improved the accuracy of our predictions.

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预测流感活动及相关入院负担,并估计COVID-19大流行对香港2019/20年冬季的影响。
與其他熱帶和亞熱帶地區一樣,流感病毒可全年在香港流行。然而,在 COVID-19 大流行期間,流感活動顯著減少。本研究旨在回顾性地预测2020年的流感活动,并评估COVID-19公共卫生社会措施对香港流感活动和入院人数的影响。利用2010年至2019年香港流感病毒活动的每周监测数据,我们建立了一个统计模型框架,以预测流感病毒活动和相关的入院人数。我们对2020年进行了短期预测(提前1-4周)和中期预测(提前1-13周),假设没有针对COVID-19实施PHSM措施。我们估算了这些公共健康和安全措施导致的传播率、峰值、发病率和流感相关住院率的下降。在短期预测中,平均环境臭氧浓度和学校假期有助于提高预测性能,而绝对湿度和臭氧浓度则提高了中期预测的准确性。我们观察到,在香港2019/2020年冬春季节期间,流感传播率最高降低了44.6% (95% CI: 38.6% - 51.9%),发病率最高降低了75.5% (95% CI: 73.0% - 77.6%),高峰期最高降低了41.5% (95% CI: 13.9% - 55.7%),累计流感相关住院率最高降低了63.1% (95% CI: 59.3% - 66.3%)。实施PHSM以控制COVID-19对香港的流感传播和相关负担产生了重大影响。纳入影响流感传播因素的信息提高了我们预测的准确性。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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