About: Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan 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	Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan
Creator	Gomez-Tames, Jose Hirata, Akimasa Kodera, Sachiko Rashed, Essam
topic	covid:78974fc5a98da4e4cb2368ad42d224ae750520b6#this
Source	ArXiv; Medline; PMC
abstract	This study analyzed the spread and decay durations of the COVID-19 pandemic in different prefectures of Japan. During the pandemic, affordable healthcare was widely available in Japan and the medical system did not suffer a collapse, making accurate comparisons between prefectures possible. For the 16 prefectures included in this study that had daily maximum confirmed cases exceeding ten, the number of daily confirmed cases follow bell-shape or log-normal distribution in most prefectures. A good correlation was observed between the spread and decay durations. However, some exceptions were observed in areas where travelers returned from foreign countries, which were defined as the origins of infection clusters. Excluding these prefectures, the population density was shown to be a major factor, affecting the spread and decay patterns, with R(2) = 0.39 (p < 0.05) and 0.42 (p < 0.05), respectively, approximately corresponding to social distancing. The maximum absolute humidity was found to affect the decay duration normalized by the population density (R(2) > 0.36, p < 0.05). Our findings indicate that the estimated pandemic spread duration, based on the multivariate analysis of maximum absolute humidity, ambient temperature, and population density (adjusted R(2) = 0.53, p-value < 0.05), could prove useful for intervention planning during potential future pandemics, including a second COVID-19 outbreak.
has issue date	2020-07-24(xsd:dateTime)
bibo:doi	10.3390/ijerph17155354
bibo:pmid	32722294
has license	cc-by
sha1sum (hex)	78974fc5a98da4e4cb2368ad42d224ae750520b6
schema:url	https://doi.org/10.3390/ijerph17155354
resource representing a document's title	Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan
has PubMed Central identifier	PMC7432865
has PubMed identifier	32722294
schema:publication	Int J Environ Res Public Health
resource representing a document's body	covid:78974fc5a98da4e4cb2368ad42d224ae750520b6#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/78974fc5a98da4e4cb2368ad42d224ae750520b6
is schema:about of	named entity 'estimate' named entity 'clusters' named entity 'prefectures' named entity 'number' named entity 'defined' named entity 'daily' named entity 'population density' named entity 'decay' named entity 'DEFINED' named entity 'ESTIMATED' named entity 'USEFUL' named entity 'COUNTRIES' named entity '28P' named entity 'FOUND' named entity 'AREAS' named entity 'BEING' named entity 'MULTIVARIATE ANALYSIS' named entity 'PLANNING' named entity 'FOLLOW' named entity 'RETURNED' named entity 'FACTOR' named entity 'INFLUENCE' named entity 'ABSOLUTE HUMIDITY' named entity 'COVID-19' named entity 'DECAY' named entity 'MULTI' named entity 'temperature' named entity 'maximum' named entity 'prefectures' named entity 'disease' named entity 'provide' named entity 'pandemics' named entity 'environmental factors' named entity 'evaluate' named entity 'multivariate analysis' named entity '16 prefectures' named entity 'decay' named entity 'population density' named entity 'estimated' named entity 'exceptions' named entity 'conducted' named entity 'Japan' named entity 'infection' named entity 'correlation' named entity 'fitting model' named entity 'wind speed' named entity 'population density' named entity 'multivariate analysis' named entity 'COVID-19 pandemic' named entity 'social distancing' named entity 'COVID-19' named entity 'ten' named entity 'absolute humidity' named entity 'environmental factors' named entity 'Statistical significance' named entity 'nosocomial infections' named entity 'Fukuoka' named entity 'Wuhan' named entity 'Aichi' named entity 'Japan' named entity 'population density' named entity 'mortality rates' named entity 'COVID-19' named entity 'Japan' named entity 'Japan' named entity 'mortality rate' named entity 'Aichi' named entity 'Hyogo' named entity 'life-threatening' named entity 'Aichi' named entity 'absolute humidity' named entity 'statistical analysis' named entity 'environmental factors' named entity 'mortality rates' named entity 'China' named entity 'linear regression'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software