About: Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications

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

About: Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications 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
title	Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications
Creator	Santos, Antônio, José Dantas, Allan Andrade, Lucas Alves, Barreto Aurélio De Oliveira Góes, Marco Cabral, Daniela Conceição, Karina Feitosa De Souza, Simone Machado De Araújo, Gomes Nunes, Jordan Soares Gomes, Dharliton Teixeira, Pizzi
source	Medline; PMC
abstract	INTRODUCTION: Coronavirus disease 2019 (COVID-19) has become a global public health emergency with lethality ranging from 1% to 5%. This study aimed to identify active high-risk transmission clusters of COVID-19 in Sergipe. METHODS: We performed a prospective space-time analysis using confirmed cases of COVID-19 during the first 7 weeks of the outbreak in Sergipe. RESULTS: The prospective space-time statistic detected %22active%22 and emerging spatio-temporal clusters comprising six municipalities in the south-central region of the state. CONCLUSIONS: The Geographic Information System (GIS) associated with spatio-temporal scan statistics can provide timely support for surveillance and assist in decision-making.
has issue date	2020-06-01(xsd:dateTime)
bibo:doi	10.1590/0037-8682-0287-2020
bibo:pmid	32491098
has license	cc-by
sha1sum (hex)	ed30ca4e8df74476f7c9d9e43c8ae7648050b9e1
schema:url	https://doi.org/10.1590/0037-8682-0287-2020
resource representing a document's title	Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications
has PubMed Central identifier	PMC7269533
has PubMed identifier	32491098
schema:publication	Revista da Sociedade Brasileira de Medicina Tropical
resource representing a document's body	covid:ed30ca4e8df74476f7c9d9e43c8ae7648050b9e1#body_text
is schema:about of	named entity 'ranging' named entity 'public health' named entity 'prospective' named entity 'Medicina' named entity 'GLOBAL' named entity 'TEMPORAL' named entity 'clusters' named entity 'statistics' named entity 'Results' named entity 'Coronavirus disease 2019' named entity 'outbreak' named entity 'This' named entity 'support' named entity 'provide' named entity 'global public health' named entity 'Sergipe' named entity 'space-time' named entity 'public health emergency' named entity 'null hypothesis' named entity 'time dissemination' named entity 'SARS-CoV-2' named entity 'epidemiological surveillance' named entity 'global public health' named entity 'decision-making processes' named entity 'RT-qPCR' named entity 'p-values' named entity 'Aracaju' named entity 'public health' named entity 'mechanisms of disease' named entity 'Brazilian state' named entity 'COVID' named entity 'log likelihood' named entity 'evolution' named entity 'relative risk' named entity 'alternative hypothesis' named entity 'Sergipe' named entity 'interstitial pneumonia' named entity 'Brazil' named entity 'Aracaju' named entity 'GIS' named entity 'China' named entity 'technological devices' named entity 'virus' named entity 'Aracaju' named entity 'COVID-19' named entity 'socioeconomic' named entity 'India' named entity 'big data' named entity 'high-risk' named entity 'COVID-19 pandemic' named entity 'Aracaju' named entity 'public policy' named entity 'negative results' named entity 'health service' named entity 'SARS-CoV-2' named entity 'COVID' named entity 'health workers' named entity 'null hypothesis' named entity 'virologic' named entity 'COVID' named entity 'Northeast region' named entity 'COVID' named entity 'respiratory disease' named entity 'heart disease' named entity 'COVID' named entity 'COVID-19' named entity 'Sergipe' named entity 'Coronavirus disease 2019' named entity 'probability distribution'

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 © 2009-2025 OpenLink Software