Utilizing and Sharing Data in the COVID-19 Crisis

Exploring the significance of data utilization and sharing during the COVID-19 crisis, this content discusses infectious disease data, the Belgian pandemic, international open data initiatives, estimating COVID-19 generation intervals, and various data collection initiatives. The narrative sheds light on the value of data in understanding and combating the pandemic.

• COVID-19 crisis
• Data sharing
• Infectious diseases
• Data collection
• Pandemic management

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1. The need for, and value of, using and sharing data within the COVID-19 crisis Prof. Dr. Niel Hens Acknowledgements: Sciensano, EpiPose consortium Funding: H2020 EpiPose project; ERC Consolidator grant TransMID; FWO COVID-19 projects Open Access Week @UHasselt 1

2. Infectious disease data Difficulties interdepencies incomplete data Observational studies bias association not causation Scientific principles conjecture versus refutation Bradford Hill criteria confidence Robert Koch & microbiology Held et al. (2019) 2 Becker (1989)

3. The Belgian COVID-19 pandemic Data collected by Sciensano: (open data after criticism in the media) Confirmed cases data Hospital data Data about deaths Deaths First wave Severe cases (hospitalized) Early May Late October Early June Federal task force: Data Against Corona: Barometer data Mobile phone data Weather data Absenteism data Mild cases Asymptomatic / pre- symptomatic (PCR+ only, detected) 3

4. International open data initiatives Open data initiatives on incidence etc John Hopkins (https://coronavirus.jhu.edu/map.html) Our world in data (https://ourworldindata.org/) Data from transmission clusters superspreading events: google spreadsheet transmission data: Singapore, Tianjin (China), Data interventions Oxford government response tracker 4

5. Estimating the generation interval for COVID-19 based on symptom onset data Tapiwa Ganyani, C cile Kremer, Dongxuan Chen, Andrea Torneri, Christel Faes, Jacco Wallinga, and Niel Hens Kremer et al. (2020): letter to editor to clarify issues with estimating the generation interval as raised by Bacallado et al. (2020) Hui-Xian et al. (in revision): analysis of Singapore data from Jan - April 2020 Torneri et al. (in revision): biased estiamtes in case of intervention measures Publication: Ganyani Tapiwa, Kremer C cile, Chen Dongxuan, Torneri Andrea, Faes Christel, Wallinga Jacco, Hens Niel. Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020. Euro Surveill. 2020;25(17):pii=2000257. https://doi.org/10.2807/1560- 7917.ES.2020.25.17.2000257

6. Own data collection initiatives Social contact data collection initiative (ERC TransMID) Large Corona Study (UAntwerpen UHasselt KU Leuven ULB) CoMIX study (H2020 EpiPose) Serological data collections (Handgift UAntwerpen) 6

7. SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 Lander Willem, Thang Van Hoang, Sebastian Funk, Pietro Coletti, Philippe Beutels, Niel Hens Publication: Medrxiv & BMC Research Notes (2020) www.socialcontactdata.org

8. www.socialcontactdata.org

9. www.socialcontactdata.org

10. CoMix: comparing mixing patterns in the Belgian population during and after lockdown Pietro Coletti, James Wambua, Amy Gimma, Lander Willem, Sarah Vercruysse, Bieke Vanhoutte, Christopher I Jarvis, Kevin van Zandvoort, John Edmunds, Philippe Beutels, Niel Hens Publication: Medrxiv & In revision (2020) www.socialcontactdata.org

11. Timing

12. All:

13. Design and analysis of SARS-CoV-2 serological surveys Sereina Herzog, Steven Abrams, Niel Hens Ine Wouters, Jessie De Bie, Esra Ekinci, Heidi Theeten, Pierre Van Damme Publication: Medrxiv & In revision (2020)

14. Serosurvey SARS-CoV-2 aim & planning Aim: Estimating seroprevalence of COVID-19 in Belgium from residual sera collected during routine laboratory testing Collections: Nr Collection period Total number samples (asked for) Total number samples (collected) 1) 30/03 - 05/04 4000 3910 2) 20/04 - 26/04 3000 3397 3) 18/05 - 25/05 3000 3242 4) 01/06 - 07/06 3000 2960 5) 29/06 - 04/07 2000 3023 6) 07/09 - 12/09 3000 3047 7) 17/09 - 12/10 3000 -

15. Serosurvey SARS-CoV-2 results Figure legend Weighted seroprevalence (A, B, C) Weighted seroincidence (D, E, F) - overall (panel A+D), - by 10-year age bands (panel B+E), - by gender (panel D+F) (updated 28.09.2020)

16. Closing remarks Conclusion Discussion Extremely valuable Open data Need to remove hurdles or expedite processes in a crisis On preprints Open software New initiative Ethics & privacy Infectieradar.be flawed reasoning: not sharing because of possible misinterpretation 16