About: A spatial model to optimise predictions of COVID-19 incidence risk in Belgium using symptoms as reported in a large-scale online survey

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About: A spatial model to optimise predictions of COVID-19 incidence risk in Belgium using symptoms as reported in a large-scale online survey Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A spatial model to optimise predictions of COVID-19 incidence risk in Belgium using symptoms as reported in a large-scale online survey
Creator	Beutels, Philippe Hens, Niel Van Damme, Pierre Faes, Christel Aerts, Jan Molenberghs, Geert Neyens, Thomas Pepermans, Koen Vranckx, Maren
Source	MedRxiv
abstract	Although COVID-19 has been spreading throughout Belgium since February, 2020, its spatial dynamics in Belgium remain poorly understood, due to the limited testing of suspected cases. We analyse data of COVID-19 symptoms, as self-reported in a weekly online survey, which is open to all Belgian citizens. We predict symptoms' incidence using binomial models for spatially discrete data, and we introduce these as a covariate in the spatial analysis of COVID-19 incidence, as reported by the Belgian government during the days following a survey round. The symptoms' incidence predictions explain a significant proportion of the variation in the relative risks based on the confirmed cases, and exceedance probability maps of the symptoms' incidence and the confirmed cases' relative risks pinpoint the same high-risk region. We conclude that these results can be used to develop public monitoring tools in scenarios with limited lab testing capacity, and to supplement test-based information otherwise.
has issue date	2020-05-21(xsd:dateTime)
bibo:doi	10.1101/2020.05.18.20105627
has license	medrxiv
sha1sum (hex)	89ae9a05fe3ef72edc18a7dfd46498093f7dab3c
schema:url	https://doi.org/10.1101/2020.05.18.20105627
resource representing a document's title	A spatial model to optimise predictions of COVID-19 incidence risk in Belgium using symptoms as reported in a large-scale online survey
resource representing a document's body	covid:89ae9a05fe3ef72edc18a7dfd46498093f7dab3c#body_text
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