A Waze-Like Way of Navigating Infectious Disease with Personalized Epidemiology

A platform with Waze’s design simplicity and reliance on personalized data sources could help us detect and prevent infectious disease outbreaks. By Bryan Hill

A Waze-Like Way of Navigating Infectious Disease with Precision Epidemiology

Waze provides the model for a simple and widely adopted approach to collecting and navigating our personal and collective health journeys.

Thanks to a convergence of technology and scientific developments, we’re on the frontier of predicting, treating and mitigating infectious disease at an individual level, as well as across broad mass demographics. Key advancements in realizing this future state include immersive visualization techniques and personalization technologies, open scientific collaboration and data on everything from genomic sequencing to individual health.

Achieving this vision of precision epidemiology is a gargantuan exercise, no doubt, particularly considering the disparate systems and regional regulations involved. Getting there will require a highly coordinated approach of first collecting, managing and sharing layers of public health and location data, and then applying AI and big-data analytics to more accurately predict how, where and when infectious disease will percolate and spread within and across specific localities worldwide.

Underlying this new level of precision epidemiology is a triad of ongoing research, treatment and policy-making. Each of these is already taking advantage of these digital advances across many sectors:

Disease and treatment research: GISAID, Nextstrain and tellic graph.C19 are representative initiatives for highly visual techniques used to share scientific data about disease, mutations and vectors of transmission.

Health and therapy development: This area involves the syndication of real-world data/evidence (RWD/RWE) to inform treatment protocols via platforms like MedScape and ePocrates, virtual trials and remote monitoring from Verily’s Project Baseline and Apple Research app, along with tracking vitals, symptoms and outbreaks such as Iqvia’s FluSTAR.

Progression and mitigation policy: Population health policy and individual risk exposure are being transformed by contact tracing methods using Bluetooth and location history such as MIT’s SafePaths, as well as a potential consumer-grade screening application that could leverage technology such as that being developed by Luminostics in partnership with Sanofi.

Navigating the Options
While these point solutions are truly transforming the speed and accuracy of outcomes in their respective areas of focus, a greater opportunity exists. These vast data pools could form the foundation of an API-enabled platform that would feed an ecosystem of apps to help individuals, healthcare providers, researchers and regulators make real-time decisions and take preventative actions in advance of infectious disease outbreaks and throughout the battle to contain them.

Inspired partially by the design simplicity and layers of travel and personalization data contained in Waze, the popular navigation app, such a platform would help organizations and individuals more proactively predict where infectious disease is likely to strike before it hits our radar screens.This platform concept shares four key aspects of Waze’s approach:

Data highways: The platform would be built around far-ranging integrated data highways, blending trusted location, social, EMR/EHR, disease information and treatment research data. This single source of truth would support a rich health topography to drive individual health decisions, treatment research and government policy.

Visual cues: It would also offer a rich and easily navigable visual experience. Just as Waze depicts a changing landscape as users drive the open road, we can better understand infectious disease by visualizing spatial relationships and complex concepts. For the general public, this can make health information and risks easier to understand, while also illuminating vulnerabilities.

Personalization: Through personalization, the platform would assess individual risk factors based on proximity and data gleaned through social media and other digital services. This includes social-graph-derived affiliations of known infections gleaned through social media posts, as well as exposure to unknown individuals via OpenTable reservations or social networking “check-ins.” Healthcare providers and researchers could reach suspected individuals for testing and study participation, and inform precision mitigation strategies for governments at the global, regional and community levels.

Real-time feedback: The system would issue real-time alerts to ever-changing individual and public health conditions. Individual notifications of risk could include geographical “hot zones” or an instance of close proximity to an infected person during a prior incubation timeframe. These alerts would happen with the timeliness of a Waze warning of an upcoming pothole or speed trap. Healthcare providers and researchers could benefit from alerts of treatment options and benefits/risk factors. Government agencies could then be notified about shifts in resource needs.

A Precise and Personal Approach

By combining these capabilities with wearables and other personal health apps – and making them available to a wide range of individuals – we could generate game-changing insights into where and when infectious disease outbreaks occur. Government contract-tracing apps, as well as device data gleaned from Apple and Google services, could add new capabilities to track confirmed infections. Doing so would reinforce the need and opportunity for the simplicity and widespread adoption of a Waze-like experience populated with public health data to navigate a future global pandemic.

Apple and Google would play a significant role in the overall solution, as their current contact-tracing approach decentralizes the collection of data on suspected infected individuals via public APIs, and they drive adoption through consumer access. However, their approach lacks the ability to advance research, treatment and mitigation.

Our platform, on the other hand, would provide the necessary tools to advance research and clinical development. In addition to providing a better understanding of the disease, it would use population data to more precisely identify potential clinical trial participants (i.e., those who were infected by a disease and may have antibodies – or not). Moreover, RWD/RWE amassed through the platform via internet-instrumented wearables, EMR/EHR, etc. would offer valuable insights into the best treatment options for an individual’s health situation given any preexisting conditions they may have (i.e., compromised immune systems, diabetes, asthma, etc.).Prying vs. Privacy
Because the methods described above require access to personal data for authorized medical and regulatory personnel, they naturally raise privacy concerns. Our proposed platform concept and app ecosystem would need to deliver a high degree of transparency to users in terms of the health, location and other data it uses, and make clear what users get in return in terms of advancing research, ensuring personal health and safeguarding society.

Such transparency sets the solution apart from the mass data capture and GPS surveillance via personal mobile phones done in other parts of the world. While this approach has proved effective in initially curbing COVID-19’s spread in places like Singapore, South Korea and Israel, other areas, like the Europe and the U.S., have been slow to leverage such techniques during the pandemic, highlighting a conflict in the regionality and design of privacy safeguards.

But while global and local regulatory bodies have placed a premium on protecting personal information, compromises to privacy do exist today; consider the use of geofencing warrants, which allow legal authorities to sift through location data to identify people of interest in criminal cases.

Notions of data privacy are also evolving. Younger generations have grown up in a world where privacy carries little if any weight in their consumption of social media or online transactions. Going by online behavior alone, many people indeed seem willing to trade a substantial amount of privacy for convenience and enjoyment, a trend that has led to a strongly reinforced bonding effect between people and technology.

Our proposed platform concept and app ecosystem would need to deliver a high degree of transparency to users.

Privacy vs. the Greater Good
The drive for greater health-data empowerment for the population will only grow in intensity in the face of future outbreaks or pandemics. The devastating public health impact and economic catastrophe unleashed by COVID-19 makes this abundantly clear. It’s too soon to say where the parameters of privacy vs. transparency will fall, and how much regional variability will arise, but international cooperation is vital.

Much will be revealed by the ongoing push for contact tracing, the accelerated development of novel therapies and extreme quarantining that have emerged in COVID-19’s wake. Pandemics are global by nature, so successfully navigating our personal and collective health journeys is critical to securing health for all – when another outbreak of infectious disease occurs.This article was written by Bryan Hill, Vice President, Digital Health & Innovation in Cognizant’s Life Sciences Practice. Read more about Bryan.