The Impact of Weather and Air Pollution on Viral Infection and Disease Outcome Among Pediatric Pneumonia Patients in Chongqing, China, from 2009 to 2018: A Prospective Observational Study

Author:

Wang Zhi-Bo1,Ren Luo2,Lu Qing-Bin3ORCID,Zhang Xiao-Ai1,Miao Dong1,Hu Yuan-Yuan1,Dai Ke1,Li Hao1,Luo Zheng-Xiu2,Fang Li-Qun1,Liu En-Mei2,Liu Wei1

Affiliation:

1. Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing, People’s Republic of China

2. Department of Respiratory Medicine, Children’s Hospital, Chongqing Medical University, Chongqing, People’s Republic of China

3. Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, People’s Republic of China

Abstract

Abstract Background For pediatric pneumonia, the meteorological and air pollution indicators have been frequently investigated for their association with viral circulation but not for their impact on disease severity. Methods We performed a 10-year prospective, observational study in 1 hospital in Chongqing, China, to recruit children with pneumonia. Eight commonly seen respiratory viruses were tested. Autoregressive distributed lag (ADL) and random forest (RF) models were used to fit monthly detection rates of each virus at the population level and to predict the possibility of severe pneumonia at the individual level, respectively. Results Between 2009 and 2018, 6611 pediatric pneumonia patients were included, and 4846 (73.3%) tested positive for at least 1 respiratory virus. The patient median age was 9 months (interquartile range, 4‒20). ADL models demonstrated a decent fitting of detection rates of R2 > 0.7 for respiratory syncytial virus, human rhinovirus, parainfluenza virus, and human metapneumovirus. Based on the RF models, the area under the curve for host-related factors alone was 0.88 (95% confidence interval [CI], .87‒.89) and 0.86 (95% CI, .85‒.88) for meteorological and air pollution indicators alone and 0.62 (95% CI, .60‒.63) for viral infections alone. The final model indicated that 9 weather and air pollution indicators were important determinants of severe pneumonia, with a relative contribution of 62.53%, which is significantly higher than respiratory viral infections (7.36%). Conclusions Meteorological and air pollution predictors contributed more to severe pneumonia in children than did respiratory viruses. These meteorological data could help predict times when children would be at increased risk for severe pneumonia and when interventions, such as reducing outdoor activities, may be warranted.

Funder

China Mega-Project for Infectious Diseases

Natural Science Foundation of China

Central Universities & Peking University Medicine Seed Fund for Interdisciplinary Research

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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