About: Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis

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About: Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis Goto Sponge NotDistinct Permalink

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis
Creator	Huang, Jian Zhang, J He, Yi He, Zonglin Ming, Wai-Kit Akinwunmi, Babatunde Casper, Mbbs Chin, Yiqiao Yu, Shinning
source	MedRxiv
abstract	AIM To investigate the associations of meteorological factors and the daily new cases of coronavirus disease (COVID-19) in nine Asian cities. METHOD Pearson correlation and generalized additive modeling were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. RESULTS The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, P<0.01), Shanghai (r=-0.471, P<0.01), and Guangzhou (r=-0.530, P<0.01) , yet in contrast, positively correlated with that in Japan (r=0.441, P<0.01). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), generalized additive modeling analysis showed the number of daily new confirmed cases was positively associated with both average temperature and relative humidity, especially in lagged 3d model, where a positive influence of temperature on the daily new confirmed cases was discerned in 5 cities except in Beijing, Wuhan, Korea, and Malaysia. Nevertheless, the results were inconsistent across cities and lagged time, suggesting meteorological factors were unlikely to greatly influence the COVID-19 epidemic. CONCLUSION The associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and lagged time. Large-scale public health measures and expanded regional research are still required until a vaccine becomes available and herd immunity is established.
has issue date	2020-04-18(xsd:dateTime)
bibo:doi	10.1101/2020.04.15.20066613
has license	medrxiv
sha1sum (hex)	474ca7efed4716ad8a63d31036c7a7dafe104fcd
schema:url	https://doi.org/10.1101/2020.04.15.20066613
resource representing a document's title	Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis
resource representing a document's body	covid:474ca7efed4716ad8a63d31036c7a7dafe104fcd#body_text
is schema:about of	named entity 'cities' named entity 'ASIAN' covid:arg/474ca7efed4716ad8a63d31036c7a7dafe104fcd named entity 'coronavirus' named entity 'Asian' named entity 'COVID' named entity 'Hong Kong' named entity 'relative humidity' named entity 'Singapore' named entity 'Malaysia' named entity 'infection rate' named entity 'COVID' named entity 'Korea' named entity 'nuclei' named entity 'Beijing' named entity 'viruses' named entity 'COVID-19' named entity 'preprint' named entity 'COVID' named entity 'Singapore' named entity 'infectivity' named entity 'Shanghai' named entity 'PACF' named entity 'public health' named entity 'relative humidity' named entity 'Malaysia' named entity 'viral transmission' named entity 'virus' named entity 'Guangzhou' named entity 'COVID-19' named entity 'MERS-CoV' named entity 'physiology' named entity 'kurtosis' named entity 'Singapore' named entity 'common ancestor' named entity 'relative humidity' named entity 'Tokyo' named entity 'influenza virus' named entity 'relative humidity' named entity 'genetics' named entity 'aerosols' named entity 'infectivity' named entity 'quarantine' named entity 'virus' named entity 'Singapore' named entity 'relative humidity' named entity 'epidemiologic' named entity 'coronavirus disease' named entity '95% confidence interval' named entity 'virus' named entity 'virus' named entity 'Malaysia' named entity 'virus' named entity 'incubation period' named entity 'preprint' named entity 'Singapore' named entity 'aerosol' named entity 'pneumococcus' named entity 'Department of Health' named entity 'influenza transmission' named entity 'pathogens' named entity 'relative humidity' named entity 'Beijing' named entity 'Hong Kong' named entity 'Wuhan' named entity 'Wuhan' named entity 'Seoul' named entity 'Shanghai' named entity 'influenza' named entity 'Shanghai' named entity 'Respiratory Syncytial Virus' named entity 'phylogenetic analysis' named entity 'relative humidity' named entity 'Japan' named entity 'Shanghai' named entity 'significance levels' named entity 'coronavirus'

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