MedPath

Mapping COVID-19 Spread in a Tertiary Hospital

Completed
Conditions
Covid19
Spatial Visualization
Respiratory Disease
Neural Network
Pandemic
Disease Spread
Registration Number
NCT04581096
Lead Sponsor
Hospital General Universitario de Valencia
Brief Summary

One of the major problems in suppressing the spreading of an epidemic resides in understanding and monitoring its propagation patterns, and in evaluating how these are modified by enforced policies. The standard solution requires detailed information at the microscopic scales, e.g. how infected people have moved and whom they came in contact with, which is hardly ever available. The researchers propose a novel approach to the study of the propagation of COVID-19, in which a proxy of this information is derived at macroscopic scales. This will be based on two ingredients: the spatiotemporal study in shiny with mathematical models with aggregated or non aggregated data and the reconstruction of functional networks of spreading patterns, and the development of a supporting software.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
2646
Inclusion Criteria
  • positive test (PCR or serology) for SARS-CoV-2
  • outpatient follow-up
Exclusion Criteria
  • hospitalisation in ward or ICU

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
spatiotemporal spreadFebruary 1, 2020 to September 30, 2020

spatiotemporal spread of COVID-19 patient in our hospital

Secondary Outcome Measures
NameTimeMethod
classification scoreFebruary 1, 2020 to September 30, 2020

risk classification score of each patients with clinical and analytical variables

Trial Locations

Locations (1)

CHGUV

🇪🇸

Valencia, Spain

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