TY - JOUR
T1 - Collaboration between government and research community to respond to covid-19
T2 - Israel’s case
AU - Peleg, Mor
AU - Reichman, Amnon
AU - Shachar, Sivan
AU - Gadot, Tamir
AU - Tsadok, Meytal Avgil
AU - Azaria, Maya
AU - Dunkelman, Orr
AU - Hassid, Shiri
AU - Partem, Daniella
AU - Shmailov, Maya
AU - Yom-Tov, Elad
AU - Cohen, Roy
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/12
Y1 - 2021/12
N2 - Triggered by the COVID-19 crisis, Israel’s Ministry of Health (MoH) held a virtual data-thon based on deidentified governmental data. Organized by a multidisciplinary committee, Israel’s research community was invited to offer insights to help solve COVID-19 policy challenges. The Datathon was designed to develop operationalizable data-driven models to address COVID-19 health policy challenges. Specific relevant challenges were defined and diverse, reliable, up-to-date, deidentified governmental datasets were extracted and tested. Secure remote-access research envi-ronments were established. Registration was open to all citizens. Around a third of the applicants were accepted, and they were teamed to balance areas of expertise and represent all sectors of the community. Anonymous surveys for participants and mentors were distributed to assess usefulness and points for improvement and retention for future datathons. The Datathon included 18 multi-disciplinary teams, mentored by 20 data scientists, 6 epidemiologists, 5 presentation mentors, and 12 judges. The insights developed by the three winning teams are currently considered by the MoH as potential data science methods relevant for national policies. Based on participants’ feedback, the process for future data-driven regulatory responses for health crises was improved. Participants expressed increased trust in the MoH and readiness to work with the government on these or future projects.
AB - Triggered by the COVID-19 crisis, Israel’s Ministry of Health (MoH) held a virtual data-thon based on deidentified governmental data. Organized by a multidisciplinary committee, Israel’s research community was invited to offer insights to help solve COVID-19 policy challenges. The Datathon was designed to develop operationalizable data-driven models to address COVID-19 health policy challenges. Specific relevant challenges were defined and diverse, reliable, up-to-date, deidentified governmental datasets were extracted and tested. Secure remote-access research envi-ronments were established. Registration was open to all citizens. Around a third of the applicants were accepted, and they were teamed to balance areas of expertise and represent all sectors of the community. Anonymous surveys for participants and mentors were distributed to assess usefulness and points for improvement and retention for future datathons. The Datathon included 18 multi-disciplinary teams, mentored by 20 data scientists, 6 epidemiologists, 5 presentation mentors, and 12 judges. The insights developed by the three winning teams are currently considered by the MoH as potential data science methods relevant for national policies. Based on participants’ feedback, the process for future data-driven regulatory responses for health crises was improved. Participants expressed increased trust in the MoH and readiness to work with the government on these or future projects.
KW - COVID-19
KW - Data
KW - Datathon
KW - Emergency management
KW - Evidence-based regulation
KW - Hackathon
KW - Health policy
KW - Innovative regulation, privacy
KW - Open innovation
KW - Public confidence
KW - Public engagement
KW - Public-private interface
KW - Trust of experts
UR - http://www.scopus.com/inward/record.url?scp=85117225681&partnerID=8YFLogxK
U2 - 10.3390/joitmc7040208
DO - 10.3390/joitmc7040208
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AN - SCOPUS:85117225681
SN - 2199-8531
VL - 7
JO - Journal of Open Innovation: Technology, Market, and Complexity
JF - Journal of Open Innovation: Technology, Market, and Complexity
IS - 4
M1 - 208
ER -