In March 2020, at the beginning of the pandemic, most data in the literature came from cases in hospitals & healthcare facilities. Little information was available about the characteristics of people infected with mild or low disease severity (Why did they not develop more severe forms?) and on potential biomarkers associated with COVID-19 severity.
Video – PREDI-COVID: Can we predict COVID-19 prognosis?
The “Predi-COVID” cohort study aims to identify important risk factors and biomarkers associated with COVID-19 severity, long-term health consequences of the disease and viral escaping natural or induced COVID-19 immunity.
FNR-grant number: 14716273
The main objective of Predi-COVID is to identify clinical, epidemiological and omics characteristics associated with the severity of COVID-19, which will then be used to further stratify the study population into clusters of disease severity with similar pattern and disease course.
to study the long term health consequences of COVID-19
to describe the trajectories of symptoms after being positively diagnosed with COVID-19
to identify vocal biomarkers associated with respiratory syndrome and fatigue related to COVID-19, which could then further be used for easy remote monitoring of Covid-19 patients
to monitor symptoms and disease outbreak in the high-risk population : household members
The Predi-COVID study was approved by the Luxembourgish Ministry of Health and by the National Committee for Research Ethic on April 23rd, 2020 and has been registered on Clinicaltrials.gov (NCT04380987)
The study design
Predi-COVID is a prospective hybrid cohort study composed of people positively tested for COVID-19 in Luxembourg.
All COVID-19 positive individuals diagnosed in Luxembourg can participate in the study. Initially, only adults were eligible to take part in the study, but as of February 2021, enrollment has been extended to include children.
Participation consists of monitoring symptoms and collecting general health data through e-questionnaires over 24 months (daily monitoring of symptoms and health status over 14 days, then weekly questionnaires at week 3 and 4, followed by monthly questionnaires until month 12, then at month 15 and 24). In addition, clinical and epidemiological data are collected by phone by study nurses or from the patient’s record at the hospital in case of hospitalisation.
A sub-sample of a minimum of 200 adult participants and 100 child participantsare invited to participate in the deep-phenotyping sub-study (biological sampling and additional clinical and digital data collection).
The Predicovid-H ancillary study is composed of household members of positive cases included in Predi-COVID. All adults and children in the household of Predi-COVID participants are invited to participate in this study.
Participation entails the monitoring of daily symptoms and the evaluation of the health status over 14 days, as well as the evaluation of clinical and socioeconomic characteristics collected upon inclusion in the study. Biological sample collection (optional) is also foreseen (for more info : “Biobank”).
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
5 months 27 days
This cookie is set by the Google recaptcha service to identify bots to protect the website against malicious spam attacks.
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category .
The cookie is set by the GDPR Cookie Consent plugin to record the user consent for the cookies in the category "Functional".
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Necessary" category .
Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Others".
Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Performance".
Records the default button state of the corresponding category & the status of CCPA. It works only in coordination with the primary cookie.
The JSESSIONID cookie is used by New Relic to store a session identifier so that New Relic can monitor session counts for an application.
This cookie is native to PHP applications. The cookie is used to store and identify a users' unique session ID for the purpose of managing user session on the website. The cookie is a session cookies and is deleted when all the browser windows are closed.
Analytical cookies are used to understand how visitors interact with the website. These cookies provide information on metrics such as number of visitors, bounce rate, traffic source, etc.
The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.
This cookie is installed by Google Analytics.
Set by Google to distinguish users.
Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.
Linkedin set this cookie to store information about the time a sync took place with the lms_analytics cookie.
YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.