AttributesValues
type
value
  • 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.
subject
  • Zoonoses
  • Viral respiratory tract infections
  • COVID-19
  • Decision-making
  • Conceptual models
  • Occupational safety and health
  • Unsolved problems in neuroscience
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
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