2020
DOI: 10.1101/2020.05.18.20105627
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

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

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… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
5
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
3
1

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(5 citation statements)
references
References 14 publications
0
5
0
Order By: Relevance
“…This is an notable outcome because the youth are predominantly more mobile, asymptomatic and perhaps also more carefree, considering the earlier reports that they were least affected by the virus [35]. The youth has been observed to be the slowest to adherence to social distancing measures [36]. Eswatini has a predominantly young population, 37% of which is within the ages of 15-40 years [37].…”
Section: Discussionmentioning
confidence: 99%
“…This is an notable outcome because the youth are predominantly more mobile, asymptomatic and perhaps also more carefree, considering the earlier reports that they were least affected by the virus [35]. The youth has been observed to be the slowest to adherence to social distancing measures [36]. Eswatini has a predominantly young population, 37% of which is within the ages of 15-40 years [37].…”
Section: Discussionmentioning
confidence: 99%
“…At the same time, it can be a component of an early warning system (Section 3.2) if the occurrence of symptoms is queried. One such example is the “Big Corona Study” (see also [ 93 ]), an online survey that can be filled in by all members of the public on every Tuesday since March 17, 2020; from June 2, 2020 onwards, the survey shifted to a bi-weekly frequency. It collects data about public adherence to measures taken by the government, contact behavior, mental and socio-economic distress, and spatio-temporal dynamics of COVID-19 symptoms' incidences.…”
Section: Prevalence Determination and Other Surveysmentioning
confidence: 99%
“…
Fig. 1 Predicted probabilities for a citizen to experience at least one key COVID-19 symptom per municipality, based on extensions of a shared latent process model that corrects for preferential sampling [ 93 ] .
…”
Section: Prevalence Determination and Other Surveysmentioning
confidence: 99%
“…A growing body of international research shows a global decrease in mental wellbeing and an increase in psychopathology at the population level and an increased risk for especially adolescents and college students (e.g., Naser et al, 2020 ; Varga et al, 2021 ). For example, in Belgium, rates for severe psychopathology increased from 1.5% at the beginning of the first lockdown in March 2020 to 6% 3 months later ( Neyens et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…Several national and international studies have also highlighted an increase in psychological distress since the COVID-19 outbreak, especially in student populations (e.g., Naser et al, 2020 ; Neyens et al, 2020 ; Mack et al, 2021 ). Symptoms of anxiety and depression are most visible in 18–25-year-old ( Vijfde COVID-19-gezondheidsenquête, 2020 ; Mack et al, 2021 ).…”
Section: Introductionmentioning
confidence: 99%