The current Coronavirus crisis shows the importance of international cooperation in global health at large and epidemiology more specifically. New digital health technologies enable faster reactions and analysis in such crisis situations.

In order to go deeper into the topic, we discussed the following questions: Which good practices and global benchmarks in digital epidemiology and other healthcare areas can help to address the current and future global health crises more effectively? Which political framework conditions and ethical considerations are needed to leverage the full potential of new digital health technologies?

We welcomed distinguished speakers:

-Isabelle Hilali, Founder & CEO datacraft, Board member Healthcare Data Institute

-Megan Diamond, Assistant Director, Programs & Innovation, Harvard Global Health Institute

-Christophe Hsu, Consultant in Teledermatology & Artificial Intelligence, University Hospital of Basel, MD JEADV & JAAD Editorial Boards

-Akarsh Venkatasubramanian: Project Manager, International Digital Health and Artificial Intelligence Research Collaborative (I-DAIR); Data Policy Manager, Digital Transformation for UHC 2030 Coalition

1. Digital and AI-driven technologies not only have the potential to facilitate the achievement of the WHO’s triple billion targets, but also more concretely to fight the spread of Covid-19 through various aspects.

2. Yet there are several challenges and dimensions that need to be addressed:

   1. Technological

   2. Legal: What frameworks? Platforms?

   3. Political: What is the political buy in? Do policy makers agree to this?

   4. Ethical: Health data as a public good for equitable access?; need to value privacy, ownership, safety of data.

3. There is still a lack of communication between data scientists and health care professionals, notably because there is no institutional support.

4. While a global governance framework is needed, we need to start locally.

5. Learnings from Covid-19 for future epidemics, and beyond:

   1. don’t act too fast, don’t do more damage than status quo just because of urgency

   2. data labelling is an important step if want to use AI-driven technologies

   3. Ensure no bias in data used – inclusiveness.

   4. Data and AI is one solution amongst many other non-digital ones which are crucial and necessary in the fight against the spread of the virus.

   5. Open access of technologies is important, notably for LMICs.