Map – Mapping Open Science Systems in Contact Tracing for COVID-19. Note: the map and a service list will be updated and will be linked from this blog and on GitHub.
As part of the GenR theme ‘Innovating Open Science Systems for COVID-19’ we will look at how Open Science can improve ‘collaboration and communication’ in R&D communities working on Contact Tracing for C-19. GenR will carry out a mapping of applicable Open Science systems in consultation with the public health community.
The preprint article ‘Open Science Saves Lives’ examined key aspects of the research workflow of ‘data collection, publishing, and science communications’ in recent COVID-19 research. A number of recommendations were made for Open Science practices to improve research in the future — study registration; using Open Data and open-source; open peer review; preregistration, and statistical reviews.
Figure: From preprint Open Science Saves Lives. Caption: Outline of the publication process with its potential issues and our proposed solutions.
For ‘Contact Tracing for COVID-19’ the idea is to look at the area of ‘R&D in public health’ and how Open Science practices and systems can improve ‘collaboration and communication’ between researchers, clinicians, and public health professionals.
The choice of collaboration and communication in R&D for ‘Contact Tracing for COVID-19’ is for the purpose of narrowing the area of investigation into the use of Open Science systems and to be able to look at the use of research in a professional working context outside of research per se. Choosing a specific part of the research workflow and looking for ways Open Science can improve research is what this consultation has in common with the preprint paper ‘Open Science Saves Lives’ which focused on ‘research publishing and science communication. But this is where the two studies depart in their methods, with the paper being a verifiable and rigorous study of literature from a given period and this Contact Tracing consultation and mapping which is anecdotal.
The German contact tracing mobile app ‘CORONA WARN-APP’ has already shown the way for adopting Open Science practices for the use of digital technologies as part of a tracking and tracing strategy by posting publicly on GitHub the programming assumptions underlying how transmission risk levels are calculated. In terms of contact tracing Apps are only one part of the picture as for example they are not applicable to elderly vulnerable people where mobile use is low. In addition any contact tracing system is contingent on many factors being comprehensively covered and so needs to be part of a wider integrated system.
Knowledge management is a key challenge on a local and international level for public health and tracking and tracing. Public health offices are having to upscale systems from analogue to digital records while running live systems. Internationally countries and regions desperately need to share and compare ideas and learning, while at the same time having problems of information overload.
Integrating research into clinical practice is a long standing issue in many areas of chronic disease treatments as can be attested by research projects such as BigMedilytics or the Scientific Data Management (SDM) group which contributed to the #EUvsVirus hackathon both of which looks to use AI to match research and clinical findings.
The GenR consultation will run over the Autumn and produce a graphical mapping of collaboration and communication in R&D for ‘Contact Tracing for COVID-19’ and point to key Open Science systems that can help with improving the use of related research.