Development and validation of an individual risk prediction tool for severe respiratory syncytial virus infection among children under five years in China
10.3760/cma.j.cn112150-20231206-00406
- VernacularTitle:中国5岁以下儿童个体呼吸道合胞病毒重症感染风险预测工具开发及验证
- Author:
Bingbing CONG
1
;
Shuyu DENG
;
Shihao MA
;
Yumeng MIAO
;
You LI
Author Information
1. 南京医科大学公共卫生学院国家疫苗研发创新平台，南京 211166
- Keywords:
Children;
Respiratory syncytial virus;
Hospitalisation;
Prediction model
- From:
Chinese Journal of Preventive Medicine
2024;58(8):1135-1142
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a predictive model to assess the risk of severe respiratory syncytial virus infection among children under five years in China, conduct preliminary validation of this model by using external data, and develop an individual risk assessment tool available for their parents.Methods:The admission after RSV infection was used as a marker of severe infection. Based on the evidence of RSV hospitalization-related risk factors and real-world data, such as the prevalence of various risk factors in children under five years old in China, a Monte Carlo-based individual RSV hospitalization risk prediction model for children under five years old was constructed. Taking Suzhou City as an example, the model was externally validated, and an interactive risk prediction tool (RSV HeaRT) was developed on the WeChat mini-program platform.Results:The estimation model showed that in children under five years old in China if the population did not have any risk factors for severe RSV infection, the RSV annual hospitalization rate was 2.2/1 000 (95% CI: 0.9/1 000-7.5/1 000). Based on this baseline hospitalization rate and the prevalence of related risk factors in Suzhou, the model predicted an RSV hospitalization rate of 8.0/1 000 (95% CI: 4.6/1 000-24.4/1 000) for children under five years old annually in Suzhou, which was close to the reported RSV hospitalization rate in literature (10/1 000-20/1 000). In the developed RSV HeaRT WeChat mini-program, target users (such as parents of children) could input basic information, disease history, and social environmental factors of the child into the mini-program, and the tool could provide real-time feedback on the following predicted results: First, the relative risk of hospitalization due to RSV infection in current children compared to general children; Second, the probability of hospitalization due to RSV infection within the next year; Third, the relative risk of adverse outcomes during hospitalization in the event of RSV infection. Conclusion:This study is based on real-world evidence related to RSV hospitalization risk and constructs an RSV hospitalization risk prediction model suitable for Chinese children based on the combination of the current prevalence of risk factors in children under five years old in China. The accuracy of the prediction model results has been preliminarily demonstrated. Based on this design, the RSV HeaRT developed can facilitate parents to evaluate the hospitalization risk of children.
