PMID- 32668459
OWN - NLM
STAT- MEDLINE
DCOM- 20210804
LR  - 20210804
IS  - 1537-6591 (Electronic)
IS  - 1058-4838 (Linking)
VI  - 73
IP  - 2
DP  - 2021 Jul 15
TI  - 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.
PG  - e513-e522
LID - 10.1093/cid/ciaa997 [doi]
AB  - 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.
CI  - (c) The Author(s) 2020. Published by Oxford University Press for the Infectious 
      Diseases Society of America. All rights reserved. For permissions, e-mail: 
      journals.permissions@oup.com.
FAU - Wang, Zhi-Bo
AU  - Wang ZB
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Ren, Luo
AU  - Ren L
AD  - Department of Respiratory Medicine, Children's Hospital, Chongqing Medical 
      University, Chongqing, People's Republic of China.
FAU - Lu, Qing-Bin
AU  - Lu QB
AUID- ORCID: 0000-0002-2804-0827
AD  - Department of Laboratorial Science and Technology, School of Public Health, 
      Peking University, Beijing, People's Republic of China.
FAU - Zhang, Xiao-Ai
AU  - Zhang XA
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Miao, Dong
AU  - Miao D
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Hu, Yuan-Yuan
AU  - Hu YY
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Dai, Ke
AU  - Dai K
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Li, Hao
AU  - Li H
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Luo, Zheng-Xiu
AU  - Luo ZX
AD  - Department of Respiratory Medicine, Children's Hospital, Chongqing Medical 
      University, Chongqing, People's Republic of China.
FAU - Fang, Li-Qun
AU  - Fang LQ
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
FAU - Liu, En-Mei
AU  - Liu EM
AD  - Department of Respiratory Medicine, Children's Hospital, Chongqing Medical 
      University, Chongqing, People's Republic of China.
FAU - Liu, Wei
AU  - Liu W
AD  - Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of 
      Pathogen and Biosecurity, Beijing, People's Republic of China.
LA  - eng
PT  - Journal Article
PT  - Observational Study
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Clin Infect Dis
JT  - Clinical infectious diseases : an official publication of the Infectious Diseases 
      Society of America
JID - 9203213
SB  - IM
MH  - *Air Pollution/adverse effects/analysis
MH  - Child
MH  - China/epidemiology
MH  - Humans
MH  - Infant
MH  - *Pneumonia/epidemiology/etiology
MH  - Prospective Studies
MH  - *Respiratory Syncytial Virus, Human
MH  - *Respiratory Tract Infections
MH  - *Virus Diseases
MH  - Weather
OTO - NOTNLM
OT  - acute respiratory tract infections
OT  - air pollution
OT  - machine learning
OT  - meteorology
OT  - pediatric pneumonia
EDAT- 2020/07/16 06:00
MHDA- 2021/08/05 06:00
CRDT- 2020/07/16 06:00
PHST- 2019/11/13 00:00 [received]
PHST- 2020/07/16 06:00 [pubmed]
PHST- 2021/08/05 06:00 [medline]
PHST- 2020/07/16 06:00 [entrez]
AID - 5872017 [pii]
AID - 10.1093/cid/ciaa997 [doi]
PST - ppublish
SO  - Clin Infect Dis. 2021 Jul 15;73(2):e513-e522. doi: 10.1093/cid/ciaa997.