To accomplish any of these goals, however, we need consistent citizen participation. Citizen science can range from contribution to collaboration or co-creation with the citizens, and this often oscillates even across a single project. It's a very fluid mechanism, I don't look at it as a rigid process. Often there is overlap between citizen science and community-based participatory research, and there are frameworks integrating these two processes. The key for us is to ethically engage citizens and translate their knowledge.
But why should citizens care about citizen science? Why should they be citizen scientists? And how should we engage them as citizen scientists, and not just take the data for our own research projects? Our experiences with citizen science at the Digital Epidemiology and Population Health Laboratory illustrate some key insights on these questions.
I am very interested in advancing citizen science with smartphones and other digital tools i.e., digital citizen science. I see these as promising pathways to equity. Some of the best work I do in this field is through partnerships with Indigenous communities, where Indigenous citizens participate in our projects as citizen scientists and become owners of the data. There's a general misperception that Indigenous communities are not receptive to technology. My experience is the opposite.
How can we use digital citizen science to decentralize technology and facilitate self-governance and self-determination, which is so important to Indigenous communities? This is a challenge. To start, it wasn’t easy to get everyone on board—funding agencies needed some persuading about the systemic issues that can be addressed with citizen science. Now that we've overcome that barrier, we are able to do citizen science based work for a number of projects focused on food insecurity, climate change and mental health.
Our agenda was scrambled when COVID-19 hit. How to use citizen science to respond to the pandemic? I started having conversations with an Indigenous community in northern Saskatchewan about using citizen science to build a digital health platform that enables the community decision-makers to respond to the needs of its citizens, almost in real time.
As we were having these conversations, we were all seeing how reactive government policies were. This begs the question: how do you come up with a proactive platform that enables Indigenous communities to take ownership of not just the data, but also of the decisions in their jurisdictions. For instance, this particular community received its COVID numbers from a health region seven days or eight days after the actual testing, which hampered local decision-making.
Our solution was building a digital health platform. The front end of this platform was a smartphone application for citizen scientists. It was more than a data entry application; the AI-informed virtual care tool enabled citizens to make better decisions about their health. The big data is anonymized and encrypted and goes into a digital dashboard that is housed at the decision-maker’s office.
So, why should citizen scientists care about participating? There has to be a value in return if they are going to participate in any project from a research perspective. We had a few key learnings in this regard.
First, keep citizens informed 24/7 and provide real-time advice and adapt the application to citizen needs. This learning could also apply to the realm of precision medicine and precision prevention. Going back to the question of why citizens should care about and participate in citizen science, the value of real-time data stands out.
Second, if you're building digital infrastructure, evaluate its applicability for other issues in the community. The infrastructure is going to stay in its place, but how do you make sure it’s durable? We built a governance model where we have a Citizen Scientist Advisory Council that actually works with my data science team and helps us develop tools that are of importance to them and that address their needs.
There are incredible opportunities for citizen science to address community health challenges, particularly in communities that are neglected or disadvantaged. Decentralized technologies are widely available, so let’s apply them locally, allow the communities to take ownership of big data, and make better decisions for themselves.
Learn more about the Digital Epidemiology and Population Health Laboratory.