Digital SARS-CoV-2 Detection Among Hospital Employees: Participatory Surveillance Study.

ABSTRACT:

Background

The implementation of novel techniques as a complement to traditional disease surveillance systems represents an additional opportunity for rapid analysis.

Objective

The objective of this work is to describe a web-based participatory surveillance strategy among health care workers (HCWs) in two Swiss hospitals during the first wave of COVID-19.

Methods

A prospective cohort of HCWs was recruited in March 2020 at the Cantonal Hospital of St. Gallen and the Eastern Switzerland Children's Hospital. For data analysis, we used a combination of the following techniques: locally estimated scatterplot smoothing (LOESS) regression, Spearman correlation, anomaly detection, and random forest.

Results

From March 23 to August 23, 2020, a total of 127,684 SMS text

SUBMITTER: Leal-Neto O 

PROVIDER: S-EPMC8610449 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature