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

ABSTRACT: 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.

SUBMITTER: Gebremedhin AT

PROVIDER: S-EPMC8748465 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Respiratory Syncytial Virus (RSV) is the most common cause of respiratory tract infection in infants and children and shows increasing trend among elderly people worldwide. In many developing country settings, population and household structures have gone through some significant changes in the past decades, namely fewer births, more elderly population, and smaller household size but more RSV high-risk individuals. These dynamics have been captured in a mathematical model with RSV transmission dynamics to predict the disease burden on the detailed population for future targeted interventions. The population and disease dynamics model was constructed and tested against the hospitalization data for Acute Lower Respiratory Tract Infection due to RSV in rural Thai settings between 2005 and 2011. The proportion of extended families is predicted to increase by about 10% from 2005 to 2020, especially for those with elderly population, while the classic nuclear family type (with adults and children) will decline by about 10%. For RSV, infections from extended family type (approximately 60% of all household types) have majorly contributed to the force of infection (FOI). While the model predicted the increase of FOI from the extended family by 15% from 2005 to 2020, the FOI contributed by other household types would be either stable or decrease in the same time period. RSV incidence rate is predominantly high among babies (92.2%) and has been predicted to decrease slightly over time (from 940 to 864 cases per 100,000 population by 2020), while the incidence rates among children and elderly people may remain steadily low over the same period. However, the estimated incidence rates among elderly people were twice than those in children. The model predicts that approximately 60% of FOI for RSV will come from members of the extended family type. The incidence rate of RSV among children and elderly in extended families was about 20 times lower than that in infants and the trend is steady. Targeted intervention strategies, such as health education in some specific groups and targeted vaccination, may be considered, with the focus on extended family type. Target interventions on babies can lessen the transmission to children and elderly especially when transmission within households of extended family type is high.

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

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