Quantifying changes in respiratory syncytial virus-associated hospitalizations among children in Texas during COVID-19 pandemic using records from 2006 to 2021.
Quantifying changes in respiratory syncytial virus-associated hospitalizations among children in Texas during COVID-19 pandemic using records from 2006 to 2021.
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DOI：
10.3389/fped.2023.1124316
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发表时间：
2023
影响因子：
2.6
通讯作者：
中科院分区：
文献类型：
--
作者：
利用常规获得的住院记录，量化2019冠状病毒病大流行期间德克萨斯州州和县4岁及以下儿童RSV相关住院情况的变化。我们使用州公共服务部（DSHS）的德克萨斯州公共使用数据文件（PUDF）来获取2006年至2021年的住院和医疗保健结果。我们使用2006-2019年期间来估计长期趋势，并预测2020-2021年的期望值。实际值和预测值用于量化住院人数和平均住院时间的季节性趋势变化。此外，我们计算了住院率，并评估了其与RSV住院监测网络（RSV- net）报告的住院率的相似性。2020年住院人数异常低，随后在2021年第三季度达到了不同寻常的高峰。2021年的住院人数大约是典型年份的两倍。在COVID-19之前，平均住院时间通常遵循季节性趋势，但在大流行期间增加了约6.5倍。住院率的空间分布揭示了COVID-19期间当地卫生保健基础设施负担过重。RSV相关的住院率平均比RSV- net高两倍。住院数据可用于估计长期的时空趋势，并在诸如流行病等加剧医疗系统的事件期间量化变化。利用住院率计算的住院率与RSV-NET获得的住院率之间的平均差值，我们推测2022年的国家级住院率可能至少是前两年的两倍，并且是过去17年来的最高水平。
To quantify changes on RSV- associated hospitalizations during COVID-19 pandemic, among children four years of age or younger at the state and county levels of Texas using routinely acquired hospital admission records. We used the Texas Public Use Data Files (PUDF) of the Department of State Human Services (DSHS) to obtain hospital admissions and healthcare outcomes from 2006 to 2021. We used the 2006–2019 period to estimate a long-term temporal trend and predict expected values for 2020–2021. Actual and predicted values were used to quantify changes in seasonal trends of the number of hospital admissions and mean length of hospital stay. Additionally, we calculated hospitalization rates and assessed their similarity to rates reported in the RSV Hospitalization Surveillance Network (RSV-NET). An unusually low number of hospitalizations in 2020 was followed by an unusual peak in the third quarter of 2021. Hospital admissions in 2021 were approximately twice those in a typical year. The mean length of hospital stay typically followed a seasonal trend before COVID-19, but increased by a factor of ∼6.5 during the pandemic. Spatial distribution of hospitalization rates revealed localized healthcare infrastructure overburdens during COVID-19. RSV associated hospitalization rates were, on average, two times higher than those of RSV-NET. Hospital admission data can be used to estimate long-term temporal and spatial trends and quantify changes during events that exacerbate healthcare systems, such as pandemics. Using the mean difference between hospital rates calculated with hospital admissions and hospital rates obtained from RSV-NET, we speculate that state-level hospitalization rates for 2022 could be at least twice those observed in the two previous years, and the highest in the last 17 years.
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DOI：
10.1093/infdis/jiab315
发表时间：
2022-04-01
期刊：
The Journal of infectious diseases
影响因子：
--
作者：
Koivisto K;Nieminen T;Mejias A;Capella Gonzalez C;Ye F;Mertz S;Peeples M;Ramilo O;Saxén H
通讯作者：
Saxén H
DOI：
10.1016/s0140-6736(22)00478-0
发表时间：
2022-05-28
期刊：
Lancet (London, England)
影响因子：
--
作者：
Li Y;Wang X;Blau DM;Caballero MT;Feikin DR;Gill CJ;Madhi SA;Omer SB;Simões EAF;Campbell H;Pariente AB;Bardach D;Bassat Q;Casalegno JS;Chakhunashvili G;Crawford N;Danilenko D;Do LAH;Echavarria M;Gentile A;Gordon A;Heikkinen T;Huang QS;Jullien S;Krishnan A;Lopez EL;Markić J;Mira-Iglesias A;Moore HC;Moyes J;Mwananyanda L;Nokes DJ;Noordeen F;Obodai E;Palani N;Romero C;Salimi V;Satav A;Seo E;Shchomak Z;Singleton R;Stolyarov K;Stoszek SK;von Gottberg A;Wurzel D;Yoshida LM;Yung CF;Zar HJ;Respiratory Virus Global Epidemiology Network;Nair H;RESCEU investigators
通讯作者：
RESCEU investigators
影响因子：
56.3
作者：
Bardsley, Megan;Morbey, Roger A.;Hughes, Helen E.;Beck, Charles R.;Watson, Conall H.;Zhao, Hongxin;Ellis, Joanna;Smith, Gillian E.;Elliot, Alex J.
通讯作者：
Elliot, Alex J.
影响因子：
7.2
作者：
Shi T;Balsells E;Wastnedge E;Singleton R;Rasmussen ZA;Zar HJ;Rath BA;Madhi SA;Campbell S;Vaccari LC;Bulkow LR;Thomas ED;Barnett W;Hoppe C;Campbell H;Nair H
通讯作者：
Nair H
DOI：
10.1073/pnas.2008814118
发表时间：
2021-04-20
影响因子：
11.1
作者：
Yan, Youpei;Malik, Amyn A.;Omer, Saad B.
通讯作者：
Omer, Saad B.