About: Spatial–Temporal Variations in Atmospheric Factors Contribute to SARS-CoV-2 Outbreak

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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
title	Spatial–Temporal Variations in Atmospheric Factors Contribute to SARS-CoV-2 Outbreak
Creator	Fronza, Raffaele Lucic, Bojana Lusic, Marina Schmidt, Manfred
source	Medline; PMC
abstract	The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) has reached over five million confirmed cases worldwide, and numbers are still growing at a fast rate. Despite the wide outbreak of the infection, a remarkable asymmetry is observed in the number of cases and in the distribution of the severity of the COVID-19 symptoms in patients with respect to the countries/regions. In the early stages of a new pathogen outbreak, it is critical to understand the dynamics of the infection transmission, in order to follow contagion over time and project the epidemiological situation in the near future. While it is possible to reason that observed variation in the number and severity of cases stems from the initial number of infected individuals, the difference in the testing policies and social aspects of community transmissions, the factors that could explain high discrepancy in areas with a similar level of healthcare still remain unknown. Here, we introduce a binary classifier based on an artificial neural network that can help in explaining those differences and that can be used to support the design of containment policies. We found that SARS-CoV-2 infection frequency positively correlates with particulate air pollutants, and specifically with particulate matter 2.5 (PM(2.5)), while ozone gas is oppositely related with the number of infected individuals. We propose that atmospheric air pollutants could thus serve as surrogate markers to complement the infection outbreak anticipation.
has issue date	2020-05-27(xsd:dateTime)
bibo:doi	10.3390/v12060588
bibo:pmid	32471302
has license	cc-by
sha1sum (hex)	d68cb4de91dbf02e703fe8d2db0924db9783bf2f
schema:url	https://doi.org/10.3390/v12060588
resource representing a document's title	Spatial–Temporal Variations in Atmospheric Factors Contribute to SARS-CoV-2 Outbreak
has PubMed Central identifier	PMC7354543
has PubMed identifier	32471302
schema:publication	Viruses
resource representing a document's body	covid:d68cb4de91dbf02e703fe8d2db0924db9783bf2f#body_text
is schema:about of	named entity 'epidemiological' named entity 'particulate matter' named entity 'number' named entity 'correlates' named entity 'frequency' named entity 'serve' named entity 'AIR POLLUTANTS' named entity 'WIDE' named entity 'HIGH' named entity 'INFECTION' named entity 'EPIDEMIOLOGICAL' named entity 'EARLY STAGES' named entity 'CLASSIFIER' named entity 'BINARY' named entity 'COMPLEMENT' named entity 'GROWING' named entity 'SOCIAL' named entity 'LEVEL' named entity 'PATIENTS' named entity 'PARTICULATE MATTER' named entity 'infected' named entity 'introduce' named entity 'air pollutants' named entity 'asymmetry' named entity 'outbreak' named entity 'ozone' named entity 'project' named entity 'individuals' named entity 'infection' named entity 'SARS-CoV-2' named entity 'infection' named entity 'coronavirus disease 2019' named entity 'infection' named entity 'severe acute respiratory syndrome coronavirus 2' named entity 'PM 2.5' named entity 'complement' named entity 'SARS-CoV-2' named entity 'air pollutants' named entity 'binary classifier' named entity 'ozone gas' named entity 'artificial neural network' named entity 'global outbreak' named entity 'particulate matter' named entity 'PM 2.5' named entity 'patients' named entity 'number' named entity 'particulate' named entity 'OBSERVED' named entity 'SEVERE ACUTE RESPIRATORY SYNDROME CORONAVIRUS 2' named entity 'NEAR' named entity 'REASON' named entity 'SITUATION' named entity 'INDIVIDUALS' named entity 'CONFIRMED' named entity 'HEALTHCARE' named entity 'COVID-19' named entity 'infection' named entity 'pathogen' named entity 'epidemiological' named entity 'COVID-19' named entity 'COUNTRIES' named entity 'INITIAL' named entity 'NUMBER' named entity 'OZONE' named entity 'ARTIFICIAL NEURAL NETWORK' named entity 'CONTAGION' named entity 'FREQUENCY' named entity 'DESIGN' named entity 'RELATED' named entity 'FAST RATE' named entity 'ANTICIPATION' named entity 'ASYMMETRY' named entity 'OUTBREAK' named entity 'GAS' named entity 'CRITICAL' named entity '28PM' named entity 'WORLDWIDE' named entity 'SURROGATE MARKERS'

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