Background The COVID-19 pandemic has reiterated the need for cohesive, collective, and deliberate societal efforts to address inherent inefficiencies in our health systems and overcome decision-making gaps using real-time data analytics. To achieve this, decision makers need independent and secure digital health platforms that engage citizens ethically to obtain big data, analyze and convert big data into real-time evidence, and finally, visualize this evidence to inform rapid decision-making. Objective The objective of this study is to develop replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration beyond health care. Methods The primary approach in the development of the digital health dashboard was the use of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish an 8-member Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory’s community partnerships. Based on the consultation with the council, three critical needs of citizens were prioritized: (1) management of household risk of COVID-19, (2) facilitation of food security, and (3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access to these PWA services are set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making, that is, the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The digital health dashboard and the PWA are hosted on the Amazon Elastic Compute Cloud server. The digital health dashboard’s interactive statistical navigation was designed using the Microsoft Power Business Intelligence tool, which creates a secure connection with the Amazon Relational Database server to regularly update the visualization of jurisdiction-specific, anonymized, and aggregated data. Results The development process resulted in a replicable and scalable digital health dashboard for decision-making. The big data relayed to the dashboard in real time reflect usage of the PWA that provides households the ability to manage their risk of COVID-19, request food when in need, and report difficulties and issues in accessing public services. The dashboard also provides (1) delegated community alert system to manage risks in real time, (2) bidirectional engagement system that allows decision makers to respond to citizen queries, and (3) delegated access that provides enhanced dashboard security. Conclusions Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision makers to enable rapid decision-making. Digital health dashboards provide decision makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm-changing approach, that is, inverting innovation by prioritizing community needs, and advancing digital health for equity. International Registered Report Identifier (IRRID) RR1-10.2196/46810

BACKGROUND The timely accessibility of big data that are readily usable by decision-makers can transform decision-making processes across health systems. OBJECTIVE This study enumerates the development of replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration i.e., going beyond health systems. METHODS The primary approach in the development of the digital health dashboard was the utilization of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish a Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory’s community partnerships. Based on the consultation with the Council, three critical needs of citizens were prioritized: 1) management of household risk of COVID-19, 2) facilitation of food security, 3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access of these services is set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making i.e., the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The data flow begins with citizens’ interaction with the services on the PWA, with data in transit being encrypted and protected with Cloudflare server ECDHE-RSA-AES128-GCM SHA256, and stored on Amazon Relational Database cloud servers. The digital health dashboard and the PWA are both hosted on the Amazon Elastic Compute Cloud server. The PWA is coded using Flutter Framework, whereas the digital health dashboard is coded using Hypertext Preprocessor scripting programming language. The digital health dashboard’s interactive statistical navigation was designed using Microsoft Power Business Intelligence visualization tool, which creates a secure connection with Amazon Relational Database server to regularly update visualization of jurisdiction-specific, anonymized, and aggregated data. RESULTS At the end of the development process, a dynamic digital health dashboard for decision-making was created to meet the needs identified by the Citizen Scientists Advisory Council. This digital health dashboard displays community health risks, as well as citizen needs in near real-time to facilitate rapid decision-making using jurisdiction-specific big data. More importantly, the key decision-makers who have secure access to the dashboard, can send delegated alerts (urgent vs. non-urgent) to the citizens within their jurisdiction to manage potential risks in near real-time. CONCLUSIONS Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision-makers to enable rapid-decision-making. Digital health dashboards also provide decision-makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm changing approach i.e., inverting innovation by prioritizing community needs, and advancing digital health for equity. CLINICALTRIAL N/A

Background The role of physical activity (PA) in minimizing non-communicable diseases is well established. Measurement bias can be reduced via ecological momentary assessments (EMAs) deployed via citizen-owned smartphones. This study aims to engage citizen scientists to understand how PA reported digitally by retrospective and prospective measures varies within the same cohort. Methods  This study used the digital citizen science approach to collaborate with citizen scientists, aged 13-21 years over eight consecutive days via a custom-built app. Citizen scientists were recruited through schools in Regina, Saskatchewan, Canada in 2018 (August 31 - December 31). Retrospective PA was assessed through a survey, which was adapted from three validated PA surveys to suit smartphone-based data collection, and prospective PA was assessed through time-triggered EMAs deployed consecutively every day, from day 1 to day 8, including weekdays and weekends. Data analyses included t-test to understand the difference in PA reported retrospectively and prospectively, and linear regressions to assess contextual and demographic factors associated with PA reported retrospectively and prospectively. Result  Findings showed a significant difference between PA reported retrospectively and prospectively (p = 0.001). Ethnicity (visible minorities: β = - 0.911, 95% C.I.= -1.677, -0.146), parental education (university: β = 0.978, 95% C.I.= 0.308, 1.649), and strength training (at least one day: β = 0.932, 95% C.I.= 0.108, 1.755) were associated with PA reported prospectively. In contrast, the number of active friends (at least one friend: β = 0.741, 95% C.I.= 0.026, 1.458) was associated with retrospective PA. Conclusion   Physical inactivity is the fourth leading cause of mortality globally, which requires accurate monitoring to inform population health interventions.  In this digital age, where ubiquitous devices provide real-time engagement capabilities, digital citizen science can transform how we measure behaviours using citizen-owned ubiquitous digital tools to support prevention and treatment of non-communicable diseases.