Abstract

Respiratory syncytial virus (RSV) causes seasonal outbreaks of respiratory tract infections in children, leading to increased emergency department visits and hospitalizations. Although the risk of severe illnesses difficult to predict, the sudden surge in RSV may strain the health care system. Therefore, the objective of this study was to examine the utility of Google Trends search activity on RSV to predict changes in RSV-related hospitalizations in children in the United States in 2019. A retrospective cross-sectional analysis of pediatric hospitalization was conducted using the 2019 HCUP-Kids Inpatient Database. Google Trends search activity for "RSV" was abstracted as a monthly relative interest score for 2019. RSV-related hospitalizations were identified using International Classification of Diseases 9/10 codes. We applied finite distributed lag models to estimate the causal effect over time of historical relative search activity and long-run propensity to calculate the cumulative effect of changes in relative search activity on admission rate. Of the total 102 127 RSV-related pediatric hospitalizations, 90% were in those aged ≤2 years. Admissions were common in males (55%), non-Hispanic Whites (50%), and South region (39%). Across 2o successive months, the cumulative effect of a 1-unit score increase in relative interest was associated with an increase of 140.7 (95% confidence interval, 96.2-185.2; P < .05) RSV-related admissions. Historic Google Trends search activity for RSV predicts lead-time RSV-related pediatric hospitalization. Further studies are needed to validate these findings using regional health systems.

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