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As governments deal with an intensifying crisis and plan for post-peak management of the pandemic, many are looking to digital surveillance networks. Digital surveillance enables near real-time contact tracing to quickly identify and manage outbreaks at the local level, predict medical resource needs to preemptively allocate them accordingly, and measure adherence to national emergency directives and policies. The South Korean government is leveraging smartphone location tracking, CCTV footage, and credit card transaction data to map chains of transmission, releasing public notifications and anonymized logs of movement history for individuals testing positive. Israel has enabled mobile carriers to share smartphone location data and track movement history of patients who test positive. China’s Alipay has rolled out a platform that captures smartphone location history at certain “check-points”, assigns color codes to identify citizens with suspected risk of carrying the virus, and shares information with local law enforcement. Russia followed suit with similar initiatives to trace smartphone geolocation data. Following the White House’s recent conversations with 7 tech giants regarding establishment of a national digital surveillance system, CDC Director Robert Redfield urged the importance of implementing “very aggressive” contact tracing, noting government efforts to evaluate “modern”, “tech-savvy” ways to make surveillance “more efficient and effective”. While U.S. plans to establish a digital surveillance system are underway, researchers and tech companies are investigating location tracking approaches that do not rely on using direct and continuous location geolocation data.
Last Friday, Apple and Google announced a partnership to jointly develop nation-wide contact tracing APIs, with an expected release in May. The APIs plan to leverage Bluetooth transmission data to determine proximity between phones without gathering physical location data. Users’ phones will exchange anonymous identifier beacons (referred to as “chirps” or “keys”), which change every ~15 minutes to prevent a static identifier that may be traceable to any particular individual. Phones locally store contact data for ~14 days, logging all interactions with other app users. If a user tests positive for COVID-19, they may opt-in to allow their locally-stored list of anonymous contacts to be shared with the cloud, which would then notify contacted individuals of exposure. Apple and Google plan to eventually incorporate these functionalities directly into iOS and Android software so that individuals can opt in without downloading an app.
Source: MIT Media Lab
MIT was the first to deploy Bluetooth-based contact tracing technology last month through its SafePaths app, followed by the COVID Watch app from Stanford. A consortium of research institutions in the EU has also formed to set software standards for Bluetooth-based tracing, dubbed Pan-European Privacy-Preserving Proximity Tracing. Last week, MIT launched the PACT protocol initiative in hopes to share their open-source, privacy-preserving protocol with industry partners, urging tech giants to pick it up. Shortly after, Google and Apple announced that they were entering a co-development partnership to bring the technology to life through integrated iOS / Android API solutions.
The proposed method of digital contact tracing offers several key advantages over traditional contact tracing and alternative forms of digital surveillance being used globally. Digital tracing provides a more scalable approach to traditional contact tracing, which relies on patients’ memories of recent exposure to others. As the coronavirus spreads rapidly across the U.S., traditional contact tracing efforts are unlikely to keep up and would require an “army” of public health workers. The system’s opt-in participation, rotating keys and short-term data storage offers more privacy than systems deployed internationally. In South Korea, government surveillance efforts leverage smartphone location data, credit card records, and surveillance camera footage to track infected patients and predict hotspots. The Chinese government is requiring adoption of software, with the help of law enforcement authorities, that determines individual contagion risk level and authorizes individuals to go out in public spaces. In countries where racial disparities in law enforcement exist, such intense surveillance measures would likely be met with distrust and resisted adoption. Apple and Google’s digital system is poised to spur nationwide adoption while preserving greater privacy than currently seen in other digital surveillance systems internationally. With operating systems in ~100% of smartphones sold, Apple and Google have the best shot of scaling any digital tracing tool across the >80% of Americans and nearly 50% of global citizens who own a smartphone. Insights derived from the system will only be shared with public health authorities to facilitate pandemic management. Contact tracing data could play a valuable role in informing local and state-level policy-making, and monitoring their effectiveness.
While Apple and Google’s contact tracing solution holds great promise compared to existing approaches, perceived data privacy and security risks remain significant challenges to political acceptance and opt-in usership rates. Some are comparing digital tracing efforts as a similar surrender of privacy to the government as seen under the Patriot Act after 9/11, when the government boosted surveillance power. In the case of COVID-19 tracing systems, re-identification of anonymous identifier beacons represents a key privacy threat. Should the anonymity of tracing data be compromised, individuals may be traced longitudinally. Cloud-based storage of anonymous identifier beacons may also threaten security, given that any centralized list of identifiers could theoretically be hacked and re-identified. Further, while the technology is designed to be opt-in, governments could attempt to enforce adoption of such tools. Beyond data privacy, data accuracy and actionability are cited as key concerns for the system’s success. Potential gaps in data capture that could cause “false positive” alerts include accurate detection of distance between devices, duration of exposure and cases in highly dense buildings where individuals are separated by walls. False negatives could also theoretically occur should someone’s phone fail to transmit a Bluetooth signal due to a glitch in transmission or failure to detect a brief interaction. Mitigating both privacy concerns and unnecessary panic will likely be crucial to promoting adoption of the new system, whose impact relies heavily on population-level adoption to drive meaningful behavioral change.
The COVID pandemic has uniquely catalyzed wide-scale adoption of digital health solutions, leapfrogging barriers to adoption that have gated market success of viable technologies for years. Digital health’s buzz has seen rapid translation into real-world utilization as top-down initiatives from national governments promote virtual visits, remote patient monitoring, digital clinical trials, and now digital biomarker surveillance to meet the urgency of the crisis. For some of these technologies, increased awareness, newly adopted infrastructure, and realized benefits for value-based care will likely create pressure on regulatory agencies and payors to “keep a good thing going.” Spillover effects are bound to benefit adjacent digital health solutions in the post-pandemic future. But what role will digital biomarker surveillance play in the post-COVID world? Digital biomarkers have demonstrated tremendous value in generating epidemiological surveillance data (e.g., proximal encounters with infected patients) that relay information at scale. Digital biomarkers provide speed, continuity, and cost benefits that instrument-and-reagent solutions cannot accomplish, providing improved overall diagnostic value. This is sure to translate into more digital diagnostic solutions for therapeutic areas like cardiovascular disease and mental health that would benefit from similar value propositions. However, repurposing these solutions as long-term epidemiological or public health surveillance tools is less certain. One could easily envision smartphone manufacturers adding a “Public Health Alert” feature, similar to the Public Safety and AMBER Alert notifications, that local governments could use to issue heightened vigilance notices or health recommendations for citizens in budding outbreak clusters for seasonal pathogens like influenza, future epidemics (e.g., SARS, H1N1, MERS, Zika, Ebola), or even pandemics. Digital surveillance tools could also be leveraged for basic epidemiological research to better estimate disease incidence and prevalence, characterize transmission rates and patterns, and refine disease models. While MIT, Google, and Apple’s technology and future digital biomarker surveillance technologies hold great promise for a new age of public health, they come with the responsibilities to protect personal privacy, obtain patient consent on a use-case level, and prioritize transparency of use.
For more DeciBio Insights on COVID-19’s impact on digital health and diagnostics, see below:
Chris focuses on digital diagnostic, therapeutic, and remote patient monitoring technologies and their impact on personalized medicine and population health. Chris has led market analysis and strategy engagements across the diagnostics and health tech spaces. Connect with him on LinkedIn or reach out at [email protected]
Fanny Anderson is an Associate at DeciBio, with experience in strategy development across the healthcare IT space, including clinical decision support, real-world evidence and digital health. Connect with her on LinkedIn to learn more about her expertise in health technology consulting.
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