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2017年至2022年意大利北部医院针对新冠疫情的非药物干预措施对儿科住院情况的影响:一项中断时间序列分析的准实验研究

Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric hospital admissions in North Italian hospitals, 2017 to 2022: a quasi-experimental study interrupted time-series analysis.

作者信息

Maglietta Giuseppe, Puntoni Matteo, Caminiti Caterina, Pession Andrea, Lanari Marcello, Caramelli Fabio, Marchetti Federico, De Fanti Alessandro, Iughetti Lorenzo, Biasucci Giacomo, Suppiej Agnese, Miceli Andrea, Ghizzi Chiara, Vergine Gianluca, Aricò Melodie, Stella Marcello, Esposito Susanna

机构信息

Clinical and Epidemiological Research Unit, University Hospital of Parma, Parma, Italy.

Pediatric Clinic, IRCCS Azienda Ospedaliera Universitaria di Bologna, Bologna, Italy.

出版信息

Front Public Health. 2024 Apr 18;12:1393677. doi: 10.3389/fpubh.2024.1393677. eCollection 2024.

Abstract

BACKGROUND

The use of Non-Pharmaceutical Interventions (NPIs), such as lockdowns, social distancing and school closures, against the COVID-19 epidemic is debated, particularly for the possible negative effects on vulnerable populations, including children and adolescents. This study therefore aimed to quantify the impact of NPIs on the trend of pediatric hospitalizations during 2 years of pandemic compared to the previous 3 years, also considering two pandemic phases according to the type of adopted NPIs.

METHODS

This is a multicenter, quasi-experimental before-after study conducted in 12 hospitals of the Emilia-Romagna Region, Northern Italy, with NPI implementation as the intervention event. The 3 years preceding the beginning of NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (up to September 2020) and a subsequent mitigation measures phase with less stringent restrictions. School closure was chosen as delimitation as it particularly concerns young people. Interrupted Time Series (ITS) regression analysis was applied to calculate Hospitalization Rate Ratios (HRR) on the diagnostic categories exhibiting the greatest variation. ITS allows the estimation of changes attributable to an intervention, both in terms of immediate (level change) and sustained (slope change) effects, while accounting for pre-intervention secular trends.

RESULTS

Overall, in the 60 months of the study there were 84,368 cases. Compared to the pre-pandemic years, statistically significant 35 and 19% decreases in hospitalizations were observed during school closure and in the following mitigation measures phase, respectively. The greatest reduction was recorded for "Respiratory Diseases," whereas the "Mental Disorders" category exhibited a significant increase during mitigation measures. ITS analysis confirms a high reduction of level change during school closure for Respiratory Diseases (HRR 0.19, 95%CI 0.08-0.47) and a similar but smaller significant reduction when mitigation measures were enacted. Level change for Mental Disorders significantly decreased during school closure (HRR 0.50, 95%CI 0.30-0.82) but increased during mitigation measures by 28% (HRR 1.28, 95%CI 0.98-1.69).

CONCLUSION

Our findings provide information on the impact of COVID-19 NPIs which may inform public health policies in future health crises, plan effective control and preventative interventions and target resources where needed.

摘要

背景

针对新冠疫情采用的非药物干预措施(NPIs),如封锁、社交距离措施和学校关闭等,存在争议,尤其是考虑到这些措施可能对包括儿童和青少年在内的弱势群体产生负面影响。因此,本研究旨在量化与前3年相比,在两年疫情期间NPIs对儿科住院趋势的影响,并根据所采用的NPIs类型考虑两个疫情阶段。

方法

这是一项在意大利北部艾米利亚 - 罗马涅地区的12家医院进行的多中心、准实验性前后对照研究,以NPIs的实施作为干预事件。NPIs实施开始前的3年(2020年3月)构成疫情前阶段。随后的2年进一步细分为学校关闭阶段(截至2020年9月)和随后限制较宽松的缓解措施阶段。选择学校关闭作为划分依据,是因为它对年轻人影响尤为显著。应用中断时间序列(ITS)回归分析来计算在变化最大的诊断类别上的住院率比(HRR)。ITS能够估计干预导致的变化,包括即时(水平变化)和持续(斜率变化)影响,同时考虑干预前的长期趋势。

结果

总体而言,在研究的60个月中有84,368例病例。与疫情前几年相比,在学校关闭期间和随后的缓解措施阶段,住院人数分别有35%和19%的显著下降。“呼吸系统疾病”的降幅最大,而“精神障碍”类别在缓解措施阶段出现显著增加。ITS分析证实,呼吸系统疾病在学校关闭期间水平变化大幅下降(HRR 0.19,95%CI 0.08 - 0.47),在实施缓解措施时也有类似但较小的显著下降。精神障碍在学校关闭期间水平变化显著下降(HRR 0.50,95%CI 0.30 - 0.82),但在缓解措施阶段增加了28%(HRR 1.28,95%CI 0.98 - 1.69)。

结论

我们的研究结果提供了有关新冠NPIs影响的信息,这可能为未来健康危机中的公共卫生政策提供参考,规划有效的控制和预防干预措施,并在需要的地方分配资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db09/11064846/960f967c7596/fpubh-12-1393677-g001.jpg

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