Developing a prediction model to estimate the true burden of respiratory syncytial virus (RSV) in hospitalised children in Western Australia

• Published in: Scientific reports Vol. 12; no. 1; p. 332
• Main Authors: Gebremedhin, Amanuel Tesfay, Hogan, Alexandra B., Blyth, Christopher C., Glass, Kathryn, Moore, Hannah C.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.01.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 692/699/255/2514; 692/700/478/174; Age Distribution; Age Factors; Bronchopneumonia; Child, Hospitalized; Child, Preschool; Children; Epidemiological Models; Female; Humanities and Social Sciences; Humans; Incidence; Infant; Infant, Newborn; Laboratories; Male; Morbidity; multidisciplinary; Prediction models; Respiratory syncytial virus; Respiratory Syncytial Virus Infections - diagnosis; Respiratory Syncytial Virus Infections - epidemiology; Respiratory Syncytial Virus Infections - virology; Risk Assessment; Risk Factors; Science; Science (multidisciplinary); Time Factors; Western Australia - epidemiology; Western Australia; Australia; Western Australia Australia
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-04080-3

Respiratory syncytial virus (RSV) is a leading cause of childhood morbidity, however there is no systematic testing in children hospitalised with respiratory symptoms. Therefore, current RSV incidence likely underestimates the true burden. We used probabilistically linked perinatal, hospital, and laboratory records of 321,825 children born in Western Australia (WA), 2000–2012. We generated a predictive model for RSV positivity in hospitalised children aged < 5 years. We applied the model to all hospitalisations in our population-based cohort to determine the true RSV incidence, and under-ascertainment fraction. The model’s predictive performance was determined using cross-validated area under the receiver operating characteristic (AUROC) curve . From 321,825 hospitalisations, 37,784 were tested for RSV (22.8% positive). Predictors of RSV positivity included younger admission age, male sex, non-Aboriginal ethnicity, a diagnosis of bronchiolitis and longer hospital stay. Our model showed good predictive accuracy (AUROC: 0.87). The respective sensitivity, specificity, positive predictive value and negative predictive values were 58.4%, 92.2%, 68.6% and 88.3%. The predicted incidence rates of hospitalised RSV for children aged < 3 months was 43.7/1000 child-years (95% CI 42.1–45.4) compared with 31.7/1000 child-years (95% CI 30.3–33.1) from laboratory-confirmed RSV admissions. Findings from our study suggest that the true burden of RSV may be 30–57% higher than current estimates.