About: The association between the seasonality of pediatric pandemic influenza virus outbreak and ambient meteorological factors in Shanghai

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About: The association between the seasonality of pediatric pandemic influenza virus outbreak and ambient meteorological factors in Shanghai Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The association between the seasonality of pediatric pandemic influenza virus outbreak and ambient meteorological factors in Shanghai
Creator	Chen, Jie Zhou, Ji Li, Yanbo Ye, Xiaofang Zhai, Feng
Source	PMC
abstract	BACKGROUND AND OBJECTIVES: The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM(1) concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors. METHODS: We recruited pediatric patients aged from 0 to 18 years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children’s Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson’s r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM). RESULTS: Pearson’s r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P < 0.001), and PM(1) (P < 0.01). While the weekly number of influenza B outpatients was statistically significantly correlated with weekly mean, maximum and minimum temperature (P < 0.001), barometric pressure and PM(1) (P < 0.01), and minimum Rh (P < 0.05). Mean temperature and PM(1) were demonstrated to be the statistically significant variables in the DLNM with influenza A and B outpatients through time-series Poisson regression analysis. A U-shaped curve relationship was noted between the mean temperature and influenza A cases (below 15 °C and above 20 °C), and the risks increased for influenza B with mean temperature below 10 °C. PM(1) posed a risk after a concentration of 23 ppm for both influenza A and B. High PM(1), low and the high temperature had significant effects upon the number of influenza A cases, whereas low temperature and high PM(1) had significant effects upon the number of influenza B cases. CONCLUSION: This study indicated that mean temperature and PM(1) were the primary factors that were continually associated with the seasonality of pediatric pandemic influenza A and B and the recurrence in the transmission and spread of influenza viruses.
has issue date	2020-06-17(xsd:dateTime)
bibo:doi	10.1186/s12940-020-00625-7
has license	cc-by
sha1sum (hex)	0a66661884da5db7e7f0be5ab2be9ee8c1132cdb
schema:url	https://doi.org/10.1186/s12940-020-00625-7
resource representing a document's title	The association between the seasonality of pediatric pandemic influenza virus outbreak and ambient meteorological factors in Shanghai
has PubMed Central identifier	PMC7298927
schema:publication	Environ Health
resource representing a document's body	covid:0a66661884da5db7e7f0be5ab2be9ee8c1132cdb#body_text
is schema:about of	named entity 'influenza' named entity 'meteorological' named entity 'meteorological' named entity 'curve' named entity 'Results' named entity 'meteorological' named entity 'influenza B' named entity 'Pearson' named entity 'collected' named entity 'correlation' named entity 'data' covid:arg/0a66661884da5db7e7f0be5ab2be9ee8c1132cdb named entity 'regression analysis' named entity 'high' named entity 'demonstrated' named entity 'factors' named entity 'subsequent' named entity 'The onset' named entity 'The' named entity 'maximum' named entity 'number' named entity 'non-linear' named entity 'effects' named entity 'statistically' named entity 'pandemic' named entity 'barometric pressure' named entity 'Poisson regression' named entity 'influenza' named entity 'SMS' named entity 'influenza' named entity 'Poisson regression' named entity 'time-series' named entity 'pandemic influenza' named entity 'seasonality' named entity 'influenza' named entity 'influenza' named entity 'Shanghai' named entity 'influenza' named entity 'influenza' named entity 'Shanghai' named entity 'influenza' named entity 'wind speed' named entity 'influenza' named entity 'influenza' named entity 'morbidity' named entity 'influenza' named entity 'influenza viruses' named entity 'seasonal influenza' named entity 'influenza' named entity 'guinea pig' named entity 'climate change' named entity 'influenza' named entity 'influenza' named entity 'British Columbia' named entity 'subtropical monsoon' named entity '95th percentile' named entity 'influenza' named entity 'Shanghai' named entity 'Shanghai' named entity 'PM 2.5' named entity 'high-pressure' named entity 'pediatric' named entity 'influenza' named entity 'distributed lag' named entity 'time-series' named entity 'simple correlation' named entity 'influenza' named entity 'barometric pressure' named entity 'meteorological data' named entity 'risk factors' named entity 'morbidity' named entity 'positive correlation' named entity 'non-linear' named entity 'confounding variable' named entity 'outpatient' named entity 'temperate region' named entity 'virus' named entity 'pediatric patients' named entity 'seasonal influenza'

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