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Time trend and seasonality in medically attended respiratory syncytial virus (RSV) infections in US children aged 0–5 years, January 2010–January 2023

OBJECTIVE: The long-term time trend and seasonality variations of first-time medically attended respiratory syncytial virus (RSV) infections among young children are unknown. We aim to examine the time trend of medically attended first-time RSV infections among young children in the USA from January...

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Detalles Bibliográficos
Autores principales: Wang, Lindsey, Berger, Nathan, Davis, Pamela B, Kaelber, David C, Volkow, Nora, Xu, Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582996/
https://www.ncbi.nlm.nih.gov/pubmed/37844966
http://dx.doi.org/10.1136/fmch-2023-002453
Descripción
Sumario:OBJECTIVE: The long-term time trend and seasonality variations of first-time medically attended respiratory syncytial virus (RSV) infections among young children are unknown. We aim to examine the time trend of medically attended first-time RSV infections among young children in the USA from January 2010 through January 2023. DESIGN: This is a population-based cohort study using electronic health records (EHRs). Monthly incidence rate of medically attended first-time RSV infection (cases per 10 000 000 person-days). A time-series regression model was used to model and predict time trends and seasonality. SETTING: Multicenter and nationwide TriNetX Network in the USA. PARTICIPANTS: The study population comprised children aged 0–5 years who had medical visits during the period of January 2010 to January 2023. RESULTS: The data included 29 013 937 medical visits for children aged 0–5 years (46.5% girls and 53.5% boys) from January 2010 through January 2023. From 2010 through 2019, the monthly incidence rate of first-time medically attended RSV infection in children aged 0–5 years followed a consistent seasonal pattern. Seasonal patterns of medically attended RSV infections were significantly disrupted during the COVID-19 pandemic. In 2020, the seasonal variation disappeared with a peak incidence rate of 20 cases per 1 000 000 person-days, a decrease of 97.4% from the expected peak rate (rate ratio or RR: 0.026, 95% CI 0.017 to 0.040). In 2021, the seasonality returned but started 4 months earlier, lasted for 9 months, and peaked in August at a rate of 753 cases per 1 000 000 person-days, a decrease of 9.6% from the expected peak rate (RR: 0.90, 95% CI 0.82 to 0.99). In 2022, the seasonal pattern is similar to prepandemic years but reached a historically high rate of 2182 cases per 10 000 000 person-days in November, an increase of 143% from the expected peak rate (RR: 2.43, 95% CI 2.25 to 2.63). The time trend and seasonality of the EHR-based medically attended RSV infections are consistent with those of RSV-associated hospitalisations from the Centers for Disease Control and Prevention (CDC) survey-based surveillance system. CONCLUSION: The findings show the disrupted seasonality during the COVID-19 pandemic and a historically high surge of paediatric RSV cases that required medical attention in 2022. Our study demonstrates the potential of EHRs as a cost-effective alternative for real-time pathogen and syndromic surveillance of unexpected disease patterns including RSV infection.