Datasets
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EpiLPS: A fast and flexible Bayesian tool for estimation of the time-varying reproduction number Hasselt University
In infectious disease epidemiology, the instantaneous reproduction number is a time-varying parameter defined as the average number of secondary infections generated by an infected individual at time t. It is therefore a crucial epidemiological statistic that assists public health decision makers in the management of an epidemic. We present a new Bayesian tool (EpiLPS) for robust estimation of the time-varying reproduction number. The proposed methodology smooths the epidemic curve and allows to obtain (approximate) point estimates and credible intervals of by employing the renewal ...
Cross-country dataset C19 ISWS University of Antwerp
As a large international consortium of 26 countries and 133 higher-education institutions (HEIs), we successfully developed and executed an online student survey during or directly after the initial peak of the COVID-19 pandemic. The COVID-19 International Student Well-being Study (C19 ISWS) is a cross-sectional multicountry study that collected data on highereducation students during the COVID-19 outbreak in the spring of 2020. The dataset allows description of: (1) living conditions, financial conditions, and academic workload before and during the COVID-19 outbreak; (2) the current level ...
COVID19 Rumor Detection Ghent University
The data set contains information about the COVID-19 pandemic. Twitter data has been collected based on the hashtags #CoronaOutbreak, #CoronaVirus, #CoronaVirusOutbreak, #COVID19, #COVID-19, #COVID2019, and #SARSCoV2, between February 12, 2020 and June 15, 2020. The goal of this data set is to detect whether a tweet is identified as a rumor or not (given by the 'label' column). A tweet that is identified as a rumor is labeled as 1, and 0 otherwise. The tweets were labeled by two independent annotators using the following guidelines. Whether a tweet is a rumor or not depends on 3 important ...
Replication Data for Flemish media, history and Covid-19 KU Leuven
The data included in these files offer a preliminary view on how Flemish media used history to analyse the COVID-19 crisis. The goal is to provide basic information on which types of historical examples were prevalent before and at the beginning of the gradual outbreak of a new infectious disease in Flanders. The files contain references to the articles of 3 media outlets (VRT NWS, De Standaard, De Morgen) that used historical information to describe the pandemic, between the period of 1 January 2023 and 13 March 2023.
Pre-lockdown GGM data (first wave) Vrije Universiteit Brussel
5986 persons replied to our online questionnaire. Variables include the Insomnia Severity Index (ISI) and items about mental health.
Lockdown GGM data (second wave) Vrije Universiteit Brussel
2843 persons to our questionnaire. Items include the Insomnia Severity Index (ISI) and items about mental health.
Lockdown GGM data (first wave) Vrije Universiteit Brussel
5986 persons replied to our online questionnaire. Variables include the Insomnia Severity Index (ISI) and items about mental health.
Lockdown DAG data (second wave) Vrije Universiteit Brussel
2843 persons to our questionnaire. Items include the Insomnia Severity Index (ISI) and items about mental health and nightmares.
Pre-lockdown GGM data (second wave) Vrije Universiteit Brussel
2843 persons to our questionnaire. Items include the Insomnia Severity Index (ISI) and items about mental health.