Suppr超能文献

新冠疫情防控措施对戊型肝炎发病率模式的间接影响:基于时间序列模型的中国案例研究。

Collateral effects of COVID-19 countermeasures on hepatitis E incidence pattern: a case study of china based on time series models.

机构信息

Department of Hepatobiliary Surgery, The Second Hospital Affiliated to Chongqing Medical University, Chongqing, P.R. China.

出版信息

BMC Infect Dis. 2024 Mar 27;24(1):355. doi: 10.1186/s12879-024-09243-x.

Abstract

BACKGROUND

There are abundant studies on COVID-19 but few on its impact on hepatitis E. We aimed to assess the effect of the COVID-19 countermeasures on the pattern of hepatitis E incidence and explore the application of time series models in analyzing this pattern.

METHODS

Our pivotal idea was to fit a pre-COVID-19 model with data from before the COVID-19 outbreak and use the deviation between forecast values and actual values to reflect the effect of COVID-19 countermeasures. We analyzed the pattern of hepatitis E incidence in China from 2013 to 2018. We evaluated the fitting and forecasting capability of 3 methods before the COVID-19 outbreak. Furthermore, we employed these methods to construct pre-COVID-19 incidence models and compare post-COVID-19 forecasts with reality.

RESULTS

Before the COVID-19 outbreak, the Chinese hepatitis E incidence pattern was overall stationary and seasonal, with a peak in March, a trough in October, and higher levels in winter and spring than in summer and autumn, annually. Nevertheless, post-COVID-19 forecasts from pre-COVID-19 models were extremely different from reality in sectional periods but congruous in others.

CONCLUSIONS

Since the COVID-19 pandemic, the Chinese hepatitis E incidence pattern has altered substantially, and the incidence has greatly decreased. The effect of the COVID-19 countermeasures on the pattern of hepatitis E incidence was temporary. The incidence of hepatitis E was anticipated to gradually revert to its pre-COVID-19 pattern.

摘要

背景

有大量关于 COVID-19 的研究,但关于其对戊型肝炎影响的研究较少。我们旨在评估 COVID-19 对策对戊型肝炎发病率模式的影响,并探索时间序列模型在分析这种模式中的应用。

方法

我们的核心思想是使用 COVID-19 爆发前的数据拟合 COVID-19 前模型,并使用预测值与实际值之间的偏差来反映 COVID-19 对策的效果。我们分析了 2013 年至 2018 年中国戊型肝炎的发病率模式。我们评估了 COVID-19 爆发前 3 种方法的拟合和预测能力。此外,我们还使用这些方法构建了 COVID-19 前的发病率模型,并将 COVID-19 后的预测与实际情况进行了比较。

结果

在 COVID-19 爆发之前,中国戊型肝炎的发病率模式总体上是稳定的和季节性的,峰值出现在 3 月,低谷出现在 10 月,冬季和春季的水平高于夏季和秋季,每年都是如此。然而,COVID-19 前模型的 COVID-19 后预测在某些时段与实际情况非常不同,但在其他时段则一致。

结论

自 COVID-19 大流行以来,中国戊型肝炎的发病率模式发生了重大变化,发病率大幅下降。COVID-19 对策对戊型肝炎发病率模式的影响是暂时的。预计戊型肝炎的发病率将逐渐恢复到 COVID-19 前的模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5beb/10967115/691fb0fcc0fb/12879_2024_9243_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