The COVID-19 pandemic posed an unprecedented global challenge, exposing vulnerabilities in policymaking and healthcare systems that led to shortcomings in crisis management. However, some countries resorted to innovative approaches that helped mitigate the impact of the crisis and proved their worth in becoming part of mechanisms to support preparedness for future health emergencies. Canada was one such country, embracing big data to track population movement to inform decision-making in the face of COVID-19.
With the widespread use of smartphones, big data from their applications has become a rich source of information about the behaviour and movement of various population groups, even allowing for some prediction. This can help authorities make informed policies and decisions, especially during crises. However, dealing with non-traditional data like big data comes with its own challenges, as the Public Health Agency of Canada (PHAC) discovered when it looked to leverage this data for tracking population movement during the COVID-19 pandemic.
To address the challenges of utilizing big data for population movement tracking, PHAC assembled a team of experts in communications, IT, epidemiology, and public policy. Initially, a small group of enthusiastic agency employees spearheaded the initiative, conducting research and coordinating with external stakeholders to determine the best approach to managing the vast amount of data. Two primary sources were identified for obtaining the required big data: 1) mobile network operators, who provided data based on user phone connections to the nearest cell towers during movement or when making/receiving calls, messages, or emails; and 2) crowdsourcing applications, which offered geolocation data from users' phones using the Global Positioning System (GPS).
Recognizing the limitations of its internal expertise in non-traditional data, PHAC faced challenges in making timely and comprehensive decisions. Constant consultation with external experts and policymakers became necessary. To bridge this gap, the agency established a dedicated team. Comprised of specialists in non-traditional data handling, policy, and data privacy, this team spearheads efforts to strengthen PHAC's internal capacity for effective processing and analysis of such data.
The newly established team assumed specialized responsibilities, including providing data acquisition support, evaluating diverse non-traditional data sources, designing and developing systems for data collection and storage, and integrating data into analytical tools and visualizations to aid decision-making by relevant officials. Guided by research, consultations, and information privacy requirements, the team prioritized data analysis aligned with public health priorities in Canada. This framework guided the team's assessment of the agency's data needs, informing their operational processes, establishing the rationale for non-traditional data use, and facilitating stakeholder and public engagement.
The new team prioritized assessing the potential of non-traditional data for public health, focusing on areas it could illuminate while acknowledging its limitations. Population movement data was their primary target, but they also considered other sources to create a holistic picture during the pandemic. Throughout, PHAC upheld its values and ethical principles, ensuring data collection protected both public health and individual privacy, adhering to established information security policies.
Mobile network and crowdsourced data, while not without limitations, offered the team valuable population-level insights. These included general movement patterns during the crisis, mobility between neighbourhoods, and how frequently people visited key locations like shops and hospitals. However, the accuracy of this spatial data varied depending on the source.
Overall, PHAC's experience with using near-real-time non-traditional data improved decision-making and crisis management during the COVID-19 pandemic, albeit not to the initial aspirations. More importantly, it highlighted the potential for future big data applications in public health and beyond, whether for crisis management, prediction, or mitigation. The experience also revealed promising applications for big data analytics, both in conjunction with traditional surveillance methods and at the provincial and regional levels in Canada.
PHAC's experience underscores the importance of transparency and clarity in public communication, handling personal data legally and ethically, collaborating with experts and stakeholders, and establishing a robust big data management system.
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