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Workshop “Data-driven solutions for containing the spreading of COVID-19”
Feb 12, 2021, 14:00 - 16:00
The aim of this workshop is to bring together researchers and companies in the Netherlands interested in or already working on data-driven solutions for reducing the spread of COVID-19.
We are a consortium of four universities (TU Eindhoven, UMC Leiden, University of Utrecht, University of Twente) and two data science companies (Mezuro, Ilionx) that aims to develop a predictive dashboard for local corona outbreaks, funded by ZonMw grant 10430 03291 001 `Mobility and behavior-based early-warning system after the first wave of COVID-19’.
On behalf of the consortium:
Martijn Schoot Uiterkamp
Why this workshop?
From the very start of the outbreak of COVID-19, many researchers and companies in the Netherlands took initiative to offer solutions and tools for combatting the crisis. With this workshop we want to provide a platform for all interested parties in order to promote, consolidate and boost Dutch developments in the area of monitoring and reducing the spread of COVID-19.
How to participate/present?
Please let us know as soon as possible if you wish to attend the workshop and if you would like to give a (short) presentation. You can do so by sending an e-mail to Martijn Schoot Uiterkamp (email@example.com). If you want to give a presentation, please also include the title and a short summary of your talk. Approximately two weeks before the event, we will send all participants the organizational details, schedule, and video conference link of the workshop.
How to extend the invitation to other parties?
If you know of other parties that might be interested in participating, please let us know, we will be happy to extend this invitation to them.
Please contact us if you have any questions, remarks, or suggestions regarding the workshop.
We are looking forward to hearing from you and hope that together we can make this a productive and inspiring event!
Mikhail Sirenko (TU Delft) - From national policies to local impact: Simulating COVID-19 in the artificial city of The Hague
COVID-19 have shown unequal spread in many dimensions: space, time, but also population-wise. What are the city hotspots? When most people get infected? Who spreads the virus the most? To answer these questions, we built a large-scale agent-based model - an artificial city of The Hague. We tested a set of national policies under different virus parameters and evaluated their impact.
Mark Dekker (Utrecht University)
Demographic and geographic modelling of epidemics in the Netherlands
We investigate the role of different age groups in the spreading and outcome of epidemic scenarios by linking mobile phone mobility data to detailed Dutch demographic data in a Monte-Carlo simulation. The results can have implications on interventions, vaccination strategies and prediction.
Mehrnoosh Vahdat (IBM)
Emergent Alliance: How Data Science helps to understand the impact of Covid-19 pandemic
Due to the Covid-19 outbreak, it is critical to assess the impact of pandemic on our society. Governments and businesses are looking to determine the implications of Covid-19 and how the economy and our societies will recover from the pandemic. Attend this session to learn how data scientists from IBM Data Science & AI Elite and Rolls Royce R² Data Labs are working together as part of the Emergent Alliance to analyze a broad set of health, economic, behavioral data to provide new insights and practical applications for the global Covid-19 response.
Jetty Komrij (Ilionx)
Early Warning decision support System COVID-19
A demonstration of the predictive dashboard for local corona outbreaks. An interactive tool that presents the results of the epidemiological models - developed within the COVID-EWS consortium - in a clear visual format for policy makers.
Richard van de Werken (Hastig)
Let's discover all activities!
There has been a lot of attention for mobility patterns and proven mobility data to get a grip on the effects of the corona-crisis. Some of those methods seem to be able to describe changes in mobility. Some are able to show changes in certain activities. Only few are able to capture all activities and therefore the impact of covid measures on people’s activity. In our presentation we would like to share some results of such a method. A method that can be used across the globe, cross borders and that is completely GDPR proof.
Nic Saadah (Leiden UMC)
COVID Radar smartphone based symptom/behavior-reporting app for prediction of emerging CoViD-19 hot-spots
COVID Radar is a smart-phone app-based tool with which users can voluntarily report CoViD-19-related symptoms and behavior via a questionnaire filled in voluntarily, up to once a day. The principal behind the app is that certain symptoms and behavior should be associated with Corona-related outcomes (e.g. case count, hospital admissions, mortality) and can be used in a predictive fashion for the purposes of public policy decisions. The app has been active as of 2 April, 2020 and as of 16 December has more than 280,000 unique users who have submitted almost 6 million completed questionnaires.
Wim Steenbakkers (Mezuro)
Making the unknown known
Mezuro (www.mezuro.com) is founded in 2011 by couple of entrepreneurs with backgrounds in data-analytics, ICT, telecom, privacy and geospatial analytics. Mezuro is operational since 2013 and we developed an unique privacy by design concept IT platform, generating mobility and dwelling information based on individual 24-hour mobility pattern. Based on this information an intelligence platform to predict the spread of Covid-19 outbreaks on regional level (between cities) is being created together with our IT partner ilionx (www.ilionx.nl) and a large group of Dutch scientists lead by the TU/e.
Remco Bron (Resono)
How Amsterdam and Rotterdam are using live location data to make better decisions
Early in the COVID-19 response Rotterdam developed and launched a live dashboard showing what parts of the cities were busiest based on Resono location data. Amsterdam followed short thereafter with a similar dashboard. Resono will give a ‘backstage view’ of these projects and explain how their location data is used to make better informed decisions.
|14:00-14:05||Word of welcome|
|14:05-14:40||1st pitch session:
- Mikhail Sirenko (TU Delft)
- Mark Dekker (Utrecht University)
- Mehrnoosh Vahdat (IBM)
- Jetty Komrij (Ilionx)
|15:05-15:40||2nd pitch session:
- Richard van de Werken (Hastig)
- Nic Saadah (Leiden UMC)
- Wim Steenbakkers (Mezuro)
- Remco Bron (Resono)