Utilizing and Sharing Data in the COVID-19 Crisis
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Prof. Dr. Niel Hens
Acknowledgements: Sciensano,
EpiPose
consortium
Funding: H2020 EpiPose project; ERC
Consolidator grant TransMID; FWO
COVID-19 projects
1
Open Access Week @UHasselt
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
Becker (1989)
Held et al. (2019)
2
The Belgian COVID-19 pandemic
First
wave
Early
May
Early
June
3
Late
October
Data collected by Sciensano:
(open data after criticism in the media)
•
Confirmed cases data
•
Hospital data
•
Data about deaths
Federal task force: Data Against Corona:
•
Barometer data
•
Mobile phone data
•
Weather data
•
Absenteism data
•
…
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
Estimating the generation interval for COVID-19 based on
symptom onset data
Tapiwa Ganyani, Cécile 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 Cécile
,
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
Own data collection initiatives
•
Social contact data
collection initiative (ERC TransMID)
•
Large Corona Study
(U
A
ntwerpen – U
H
asselt – KU Leuven – ULB)
•
CoMIX study
(H2020 EpiPose)
•
Serological data
collections (Handgift U
A
ntwerpen)
6
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
www.socialcontactdata.org
www.socialcontactdata.org
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
Timing
All:
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)
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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)
Closing remarks
●
Discussion
○
Open data
○
On
preprints
○
Open software
○
Ethics & privacy
●
Conclusion
○
Extremely valuable
○
Need to remove hurdles or
expedite processes
in a crisis
●
New initiative
○
I
nfectieradar.be
16
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.
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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
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)
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
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
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
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
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
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
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)
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 -
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)
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
