Published in


COVID-19 virtual Study-a-thon: global scientific collaboration effort


As of March 31, 2020, 787,438 people have been confirmed with severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection from more than 200 countries and territories, and the total death toll reached 37,846 globally. The Coronavirus disease 2019 (COVID-19) pandemic is expected to continue spreading, so it is crucial for all nations to take timely measures to combat the looming crisis The disease is not only claiming thousands of lives, but also threatens the world with an economic crisis: in the median economy, the output might decline by 25%.


Despite all the efforts of physicians, epidemiologists, and scientists, there is not enough evidence from real-world clinical data available. To generate evidence that can improve healthcare decisions and flatten the curve of COVID-19 outbreak worldwide, the Sciforce Medical Team, as a collaborator of The Observational Health Data Sciences and Informatics (OHDSI) international community, has taken part in COVID-19 virtual Study-a-thon (March 26–29).


During the Study-a-thon, the participants performed a large-scale characterization of COVID, conducted the largest study ever on the safety of hydroxychloroquine, and created three prediction models externally validated on COVID patients. In just 88 hours, 351 participants were brought together from 30 countries to review over 10,000 publications, draft nine protocols, release 13 study packages and design 355 cohort definitions.

This four-day global collaboration spanned across three studies:

  1. The first large-scale characterization of COVID-19 patients with six databases with COVID-19 patients located in both the U.S. and South Korea;
  2. The largest study ever conducted on the overall safety profile of hydroxychloroquine, a drug currently being evaluated as a potential treatment for COVID-19. This study of more than 130,000 patients from the USA, England, Germany and South Korea.
  3. The first prediction model externally validated on COVID-19 patients to support triage decisions in an effort to ‘flatten the curve’.

The Sciforce medical team contributed to building cohorts for prediction models.

Characteristics of the prediction model for the likelihood of hospitalization at the first outpatient visit with CoViD-19/flu-like symptoms.


It may look like all borders are closed and all nations are left to fight the deadly virus alone. Yet, in reality, the most crucial work continues to be spread over countries and to unite specialists from all over the world. Working as a global team and at the intersection of medicine and data science, we’ll be able to find hidden data that can help reduce the incidence and unfavorable clinical and economic outcomes of the Coronavirus disease 2019.

Feel free to add everything you want in the comments!

Interesting further reading



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store


Ukraine-based IT company specialized in development of software solutions based on science-driven information technologies #AI #ML #IoT #NLP #Healthcare #DevOps