Haala Rokadia MD, Anna Andoni MD, Ben Rosner MD PhD, Shayann Ramedani in conjunction with NODE.Health.
BACKGROUND:
The process of awakening America’s communities and businesses from their hiatus during the COVID-19 pandemic requires public health coordination to ensure reopening in the safest manner possible. The Centers for Disease Control suggests a multi-pronged approach, with contact tracing at the forefront. Like no time in the past, contact tracing may be substantially enhanced by digital health tools, but is there evidence that such approaches will work?
CONTACT TRACING
What is contact tracing? According to the definition by the Centers for Disease Control and Prevention (1), contact tracing is a core disease control measure that has been used for decades by local and state health departments to limit the spread of infection. Contact tracing identifies and warns people who have potentially come into contact with someone infected. Historically, contact tracing has used methods such as in-person and telephonic surveys of patients known to have infection in order to identify potential contacts throughout the incubation and infectious periods of a transmittable disease. Both of these methods rely on large numbers of contact tracers. While disease transmission is often exponential, scalability of analog contact tracing using humans is only linear. However, digital health tools give public health departments the opportunity to match exponential transmission with exponential contact tracing.
THE EVIDENCE:
The data behind the use of contact tracing has evolved as technology has offered digital options to what were previously a high-resource-utilization form of manual tracing. Manual contact tracing with quarantine was effective as part of a control strategy of the highly infectious outbreaks of SARS in 2003, Ebola in 2014, and the eradication of smallpox.(2–4) Follow up mathematical models of manual contact tracing based on 2009 H1N1 data noted that, if contact tracing is used early, it can double the likelihood of avoiding an outbreak.(5) The nuances of COVID-19 transmission, such as a high latency period and a large cohort of asymptomatic carriers, make contact tracing more important in this pandemic than in those before it.
However, the logistical burden of contact tracing is high. Digital health tools may be able to alleviate this burden. In order to be highly accurate, an average of 36.1 individuals would need to be traced for each positive case.(6) Data from the Shenzhen Center for Disease Control directly address the feasibility of contact tracing in the COVID-19 pandemic. Household members have a secondary infection rate of 11.2% and traveling or sharing a home with an infected individual increases risk of getting infected by 6–7 fold. Importantly though, the use of digital contact tracing reduced the time that a positive individual transmitted the infection to the community by 1.9 days on average (reduced from 4.6 days to 2.7 days).(7) With widespread use (>90%), contact tracing can almost cut transmission in half. However, with under-utilization, its impact quickly dwindles to <10% reduction in transmission.(8)
DIGITAL CONTACT TRACING FOR COVID-19
At a high level, digital contact tracing toggles between index case identification and proximity tracking with instantaneous notification of potential contact exposures. In its simplest form, it requires that public health authorities have access to a large portion of the population’s individual health and location data to identify, track, and notify them of exposures. Digital and/or manual infrastructure is then used to send notifications to encourage self-isolation, offer quarantining resources, and record and monitor downstream contacts iteratively. Optional self-reporting augments the efficacy, yet makes the system susceptible to misinformation.
In epidemiologic terms, the R0 (basic reproduction number) of an infectious disease describes how many individuals are infected secondarily by one infected case. In the case of COVID-19, the R0 “in the wild” approximates 2.5 — meaning, on average 2.5 individuals are infected by each seed case.(9) For epidemic disease control, the R0 needs to be reduced to < 1, corresponding to a downward curve of transmission, which equates to preventing 50–70% of possible transmissions.(10)
Four main pitfalls of digital contact tracing exist:
- Requires widespread adoption. Contact tracing needs a critical mass of the at-risk population to be engaged — either by mandate or voluntarily — for it to be effective. Oxford researchers estimate a 56% opt-in rate in the general population, or more specifically 80% of all smartphone users, for a digital contact tracing app to be effective.(11) Simply put, the prevalence of a digital contact tracing phone app needs to be greater than the prevalence of the disease.
- Requires trust. Many individuals have concerns related to maintaining a continuous feed of individuals’ health and location data. Polls show that many Americans lack trust in the institutions of private tech companies and government authorities to be transparent and secure with their data.(12–13)
- Privacy risk. Inter-user privacy is generally maintained; however, assuring privacy from the company or government authority that is tracking individuals or from hackers/scammers that obtain access to centralized data is an ongoing concern.
- Vulnerable to misinformation. Contact tracing, which starts with identification of patients with infection, relies on the honesty of self-reporting of infection.
INTERNATIONAL EFFORTS TO CONTAIN AND CONTROL SPREAD OF COVID-19:
Use Case #1: In February 2020, when COVID-19 cases exceeded 1,000, South Korea quickly implemented widespread testing and government-run digital contact tracing, in lieu of severe lockdowns. High surveillance contact tracing, including data from GPS locations, closed-circuit public cameras and monitoring of credit card transactions, was utilized and the data were stored centrally.(14) Within a month, South Korea recorded a dramatic drop in cases and reduced community spread.(15)
Use Case #2: Singapore’s opt-in TraceTogether app uses a bluetooth-enabled, anonymous, token-sharing digital contact tracing program that was meant to protect anonymity between users but allowed open access to data for the Singaporean Ministry of Health. Within one month, TraceTogether had been downloaded by only 20% of the population, with the low adoption rate attributed to battery drain that can be associated with the app continuously running in the background, and privacy issues.(16)
Use Case #3: The day after the WHO declared COVID-19 a pandemic on January 30th, Iceland assembled broad testing and contact tracing even before having evidence of domestic community transmission. Large group gatherings were restricted but elementary schools and non-essential businesses that conformed to small group restrictions were allowed to stay open. These techniques limited transmission and associated deaths. The Rakning C-19 app, which tracks GPS location data, was made available for voluntary use on April 2; however, it achieved a disappointing 38% penetration in a population of 364,000 despite being a socially-cohesive population. Fifty four percent of all COVID-19 cases were diagnosed in quarantine, suggesting that the accuracy of identifying at risk individuals was good and that quarantining those individuals reduced further community transmission. (17–18)
POTENTIAL FOR ADOPTION AND EFFICACY IN THE U.S.:
In an effort to roll out contact tracing quickly involving both industry and public institutions, there has been an uncoordinated effort in the U.S. that has developed silos of information with varied levels of surveillance and data security. MIT Technology Review’s COVID Tracing Tracker has created a rolling database of international, national government-backed apps and scored them based on 5 key questions to consider: 1. Is it voluntary? 2. Are there limitations on how the data is used? 3. Will data be destroyed after a period of time? 4. Is data collection minimized? 5. Is the effort transparent?(19) Despite multiple efforts, privacy concerns continue to be a weak link in the potential efficacy of contact tracing. In order to prioritize individual privacy and avoid continuous GPS tracking, Bluetooth technology is being leveraged for proximity tracking with random, rolling ID number sharing. This information is stored locally on one’s phone, with instantaneous notification to contacts if an individual associated with a random ID is found to be positive for COVID-19. The CovidWatch nonprofit developed an open-source mobile app for digital contact tracing with this technology with teams at Stanford and Waterloo Universities, on the basis of privacy as a first priority.(20)
In a major effort to preserve privacy, on April 10, Google and Apple jointly launched an Application Programming Interface (API) for a privacy-preserving exposure notification system utilizing similar Bluetooth technology that would be the infrastructure on which to support locally-built, opt-in digital contact tracing apps run by public health authorities only. (21–22) This offers the most secure system to date for digital contact tracing because it does not track location data. The evidence behind of the Apple-Google digital contact tracing system has been developed by the Private Automated Contact Tracing (PACT) (23) research collaboration led by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT Internet Policy Research Initiative, Massachusetts General Hospital Center for Global Health and MIT Lincoln Laboratory. PACT research ensures that the Apple-Google contact tracing system is provably effective and private. The first real pilot app, SwissCovid, a decentralized Apple-Google API was launched in Switzerland on May 20th with the possibility of full-scale public deployment by mid-June. What data is collected, how it is stored and for how long these data are used has not been made fully transparent and no current regulations exist on the subject.
Unlike many international efforts of nation-wide digital contact tracing apps, the U.S. has deliberately made digital contract tracing a state-led endeavor. Further, in the U.S., businesses are under strong economic pressure to reopen. Some manufacturing companies are looking to digital contact tracing to control community spread within their factories and workplaces and, unlike public institutions, are making it mandatory for an employee to be screened and tracked in order to return to work.(24) Utah’s HealthyTogether app and North and South Dakota’s Care19 were the first voluntary state-specific digital contact tracing apps that were launched in the U.S. In a few weeks, South Dakota’s Care 19 has been considered the most widely adopted despite only achieving a 2% opt in rate.(25) Further North Dakota has been suspected of leaking data to FourSquare and Google.(26) Many of these state-lead grassroots campaign efforts have fallen short by low adoption and concerns of privacy, and struggle additionally with interoperability when nationwide data will need to be aggregated from state data storage systems.(27) Below is a representation of both national and international efforts on creating COVID-19 apps using different technologies (GPS, Bluetooth, WiFi) and data systems (centralized vs decentralized) as well as the current status of their adoption.
TABLE OF INTERNATIONAL CONTACT TRACING EFFORTS:
KEY TAKEAWAYS:
Extrapolating from the evidence for manual contact tracing and the early data on international digital contact tracing efforts, digital contact tracing could be a lower-resource and lower-friction format for implementation of contact tracing given the following caveats: .
- That digital contact tracing can be used in concert with manual contact tracing, widespread testing, and quarantining infrastructure. Absence of any of these pillars renders the others ineffective.
- That adequate penetration of digital contact tracing throughout the at-risk population is essential for effectiveness.
- That the public can be reassured that individual privacy is preserved and protected from use by alternative motives
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NODE.Health is pleased to cross post this article giving examples of digital health solutions for contact tracing. NODE.Health encourages its readers to be diligent with selecting such tools and understand the evidence. As more evidence comes out on the use of such tools for COVID-19 and beyond, NODE.Health will keep its readers informed about the latest developments. Interested in learning more about the Network of Digital Evidence (NODE.Health)? Click here
References
1. Center for Disease Control and Prevention. Case Investigation and Contact Tracing : Part of a Multipronged Approach to Fight the COVID-19 Pandemic. Accessed 1 June 2020. https://www.cdc.gov/coronavirus/2019-ncov/php/principles-contact-tracing.html#:~:text=Contact%20tracing%20is%20part%20of,stop%20chains%20of%20transmission
2. Riley S, Fraser C, Donnelly CA, Ghani AC, Abu-Raddad LJ, et al.Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions. Science, 300 (2003), 1961–6.
3. Saurabh S, Prateek S. Role of contact tracing in containing the 2014 Ebola outbreak: a review. Afr Health Sci, 17 (2017), 225–36.
4. Eames KT, Keeling MJ. Contact tracing and disease control. Proc Biol Sci, 270 (2003), 2565–2571.
5. Ross JV, Black AJ. Contact tracing and antiviral prophylaxis in the early stages of a pandemic: the probability of a major outbreak. Math Med Biol. 2015 Sep;32(3):331–43.
6. Keeling MJ, Hollingsworth TD, Read JM. The efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19). Posted 17 Feb 2020. Preprint. https://www.medrxiv.org/content/10.1101/2020.02.14.20023036v1
7. Bi Q, Wu Y, Mei S, Ye C, Zou X, Zhang Z, et al. Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. Lancet Infect Dis. 2020 Apr 27;S1473–3099(20)30287–5. doi: 10.1016/S1473–3099(20)30287–5. Online ahead of print.
8. Bilinski A, Mostashari F, Salomon JA. Contact tracing strategies for COVID-19 containment with attenuated physical distancing. Posted 20 May 2020. Preprint. https://www.medrxiv.org/content/10.1101/2020.05.05.20091280v2
9. Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Euro Surveill. 2020;25(4).
10. Hellewell J, Abbott S, Gimma A, Bosse NI, Jarvis CI, Russell TW, et al.; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob Health. 2020;8(4):E488–96.
11. Kelion L. “Coronavirus: NHS contact tracing app to target 80% of smartphone users” BBC News. 16 April 2020. https://www.bbc.com/news/technology-52294896
12. Kirzinger A, Hamel L, Munana C, Kerney A, Bodie M. KFF health tracking poll — Late April 2020: Coronavirus, Social Distancing, and Contact Tracing. 24 April 2020. https://www.kff.org/global-health-policy/issue-brief/kff-health-tracking-poll-late-april-2020/
13. Timberg C, Harwell D, Safarpour A. Most Americans are not willing or able to use an app tracking coronavirus infections. Thats a problem for Big Tech’s plan to slow the pandemic. Washington Post. 29 April 2020. https://www.washingtonpost.com/technology/2020/04/29/most-americans-are-not-willing-or-able-use-an-app-tracking-coronavirus-infections-thats-problem-big-techs-plan-slow-pandemic/
14. Show evidence that apps for COVID-19 contact tracing are secure and effective. Nature. 2020 April;580(7805):563.
15. Park S, Choi GJ, Ko H. Information Technology–Based Tracing Strategy in Response to COVID-19 in South Korea — Privacy Controversies. JAMA. Published online April 23, 2020.
16. Lee, M. Given the low adoption rate of TraceTogether, experts suggest merging with SafeEntry or other apps. TodayOnline. 8 May 2020. https://www.todayonline.com/singapore/given-low-adoption-rate-tracetogether-experts-suggest-merging-safeentry-or-other-apps
17. Johnson B. Nearly 40% of Icelanders are using a covid app — and it hasn’t helped much. MIT Technology Review. 11 May 2020. https://www.technologyreview.com/2020/05/11/1001541/iceland-rakning-c19-covid-contact-tracing/
18. Potter C. Lessons from Iceland. Outbreak Observatory. 16 April 2020. https://www.outbreakobservatory.org/outbreakthursday-1/4/16/2020/the-success-of-iceland
19. O’Neill PH, Ryan-Mosley T, Johnson B. A flood of coronavirus apps are tracking us. Now it’s time to keep track of them. MIT Technology Review. 7 May 2020. https://www.technologyreview.com/2020/05/07/1000961/launching-mittr-covid-tracing-tracker/
20. CovidWatch. https://covid-watch.org/ Accessed 30 May 2020.
21. Exposure Notifications: using technology to help public health authorities fight COVID-19. https://www.google.com/covid19/exposurenotifications/. Accessed 30 May 2020.
22. Privacy-preserving contact tracing. https://www.apple.com/covid19/contacttracing. Accessed 30 May 2020.
23. Rivest RL, Weitzner DJ, Ivers LC, Soibelman I, Zissman MA. PACT:Private automated contact tracing. Accessed 1 June 2020. https://pact.mit.edu/wp-content/uploads/2020/05/PACT-Mission-and-Approach-2020-05-19-.pdf
24. Haskins C. Workers around the world are already being monitored by digital contact tracing apps. Accessed 1 June 2020. https://www.buzzfeednews.com/article/carolinehaskins1/coronavirus-private-contact-tracing
25. Associated Press. Contact tracing apps are off to a slow start in the U.S. 19 May 2020. https://www.nbcnews.com/tech/tech-news/contact-tracing-apps-are-slow-start-u-s-n1210191
26. Melendez S. North Dakota’s COVID-19 app has been sending data to Foursquare and Google. 21 May 2020. https://www.fastcompany.com/90508044/north-dakotas-covid-19-app-has-been-sending-data-to-foursquare-and-google
27. Greenberg A. State-based contact tracing apps could be a mess. 27 May 2020. https://www.wired.com/story/covid-19-contact-tracing-app-fragmentation/
