ETSI GR E4P 002 V1.1.1 (2021-02)

Europe for Privacy-Preserving Pandemic Protection (E4P); Comparison of existing pandemic contact tracing systems

DGR/E4P-002

General Information

• Status: Not Published
• Technical Committee: E4P - Europe for Privacy-Preserving Pandemic Protection
• Current Stage: 12 - Completion
• Due Date: 31-Jan-2021
• Completion Date: 01-Feb-2021

Standards Content (Sample)

GROUP REPORT
Europe for Privacy-Preserving Pandemic Protection (E4P);
Comparison of existing pandemic contact tracing systems
Disclaimer
The present document has been produced and approved by the Europe for Privacy-Preserving Pandemic Protection ETSI
Industry Specification Group (ISG) and represents the views of those members who participated in this ISG.
It does not necessarily represent the views of the entire ETSI membership.

2 ETSI GR E4P 002 V1.1.1 (2021-02)

Reference
DGR/E4P-002
Keywords
covid, eHealth, emergency services, identity,
mobility, pandemic, privacy, security, smartphone

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3 ETSI GR E4P 002 V1.1.1 (2021-02)
Contents
Intellectual Property Rights . 5
Foreword . 5
Modal verbs terminology . 5
Introduction . 5
1 Scope . 6
2 References . 6
2.1 Normative references . 6
2.2 Informative references . 6
3 Definition of terms, symbols and abbreviations . 10
3.1 Terms . 10
3.2 Symbols . 11
3.3 Abbreviations . 11
4 Current landscape of pandemic contact tracing . 12
4.1 Overview: a universe of apps . 12
4.2 Manual pandemic contact tracing . 12
4.3 Digital pandemic contact tracing: initiatives per country . 13
4.3.0 General . 13
4.3.1 Austria (project "Stopp Corona") . 13
4.3.2 Estonia (project "Hoia") . 14
4.3.3 Finland (project "Koronavilkku") . 15
4.3.4 France (project "StopCovid") . 19
4.3.5 Germany (project "Corona-Warn-App"). 19
4.3.6 India (project "Aarogya Setu") . 20
4.3.7 Ireland (project "COVID Tracker") . 21
4.3.8 Italy (project "Immuni") . 23
4.3.9 Japan (project "COCOA") . 23
4.3.10 Lithuania (project "Korona Stop LT") . 24
4.3.11 Poland (project "ProteGO Safe") . 25
4.3.12 Singapore (project "Trace Together") . 26
4.3.13 Spain (project "Radar COVID") . 27
4.3.14 Switzerland (project "SwissCovid") . 27
4.3.15 United States (project "CoEpi") . 28
4.3.16 Summary . 30
4.3.17 Other initiatives . 32
5 General approach to digital pandemic contact tracing . 32 ®
5.1 Generic systems using a back-end server, a mobile device & app, and Bluetooth Low Energy . 32
5.1.0 Overview . 32
5.1.1 Systems having possible risk of infection detected by a server . 33
5.1.2 Systems having possible risk of infection detected by a device. 34
5.1.3 Commonalities and differences between systems . 34
5.2 Other systems . 34
5.2.0 Overview . 34
5.2.1 Token-based systems . 35
5.2.2 Acoustic-based systems . 36
6 Existing methods . 37
6.1 Systems having possible risk of infection detected by a server . 37
6.1.1 BlueTrace . 37
6.1.2 DESIRE . 38
6.1.3 ROBERT . 39
6.2 Systems having possible risk of infection detected by a device . 41
6.2.1 Contact Shield . 41
6.2.2 DP-3T . 43
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6.2.3 ENS . 46
6.2.4 IDPT/IDPT-FP . 49
6.2.5 [East Coast] PACT . 50
6.2.6 [West Coast] PACT . 51
6.2.7 Pronto-C2 . 52
6.2.8 TCN . 53
7 Comparison of existing methods . 54
7.1 Epidemiological risk criteria . 54
7.2 Promoters/Level of sponsorship, endorsement by, or involvement of, public health authorities . 55
7.3 Degree of interoperability. 56
7.4 User experience and usability aspects . 56
7.5 Impact on devices and data usage . 57
7.6 Privacy & security aspects. 58
7.7 Data anonymisation/pseudonymisation . 60
7.8 Data retention . 60
7.9 Proximity detection method and technology . 61
7.10 Device platforms supported . 61
7.11 Summary . 62
8 General challenges of digital pandemic contact tracing solutions . 63
8.1 Readiness: overall pandemic mitigation and containment mechanisms . 63
8.2 Adoption . 63
8.3 Effectiveness . 64
8.4 Asynchronous contact tracing . 64
8.5 Ethics . 64
8.6 Privacy . 64
8.7 Digital fragility . 65
8.8 Interoperability . 65
Annex A: Bibliography . 66
Annex B: Change History . 81
History . 82

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5 ETSI GR E4P 002 V1.1.1 (2021-02)
Intellectual Property Rights
Essential patents
IPRs essential or potentially essential to normative deliverables may have been declared to ETSI. The information
pertaining to these essential IPRs, if any, is publicly available for ETSI members and non-members, and can be found
in ETSI SR 000 314: "Intellectual Property Rights (IPRs); Essential, or potentially Essential, IPRs notified to ETSI in
respect of ETSI standards", which is available from the ETSI Secretariat. Latest updates are available on the ETSI Web
server (https://ipr.etsi.org/).
Pursuant to the ETSI IPR Policy, no investigation, including IPR searches, has been carried out by ETSI. No guarantee
can be given as to the existence of other IPRs not referenced in ETSI SR 000 314 (or the updates on the ETSI Web
server) which are, or may be, or may become, essential to the present document.
Trademarks
The present document may include trademarks and/or tradenames which are asserted and/or registered by their owners.
ETSI claims no ownership of these except for any which are indicated as being the property of ETSI, and conveys no
right to use or reproduce any trademark and/or tradename. Mention of those trademarks in the present document does
not constitute an endorsement by ETSI of products, services or organizations associated with those trademarks.
Foreword
This Group Report (GR) has been produced by ETSI Industry Specification Group (ISG) Europe for Privacy-Preserving
Pandemic Protection (E4P).
Modal verbs terminology
In the present document "should", "should not", "may", "need not", "will", "will not", "can" and "cannot" are to be
interpreted as described in clause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of provisions).
"must" and "must not" are NOT allowed in ETSI deliverables except when used in direct citation.
Introduction
The COVID-19 pandemic has generated significant challenges for many countries and their citizens and showed that
digital technologies could play an important role in addressing this and future pandemics. Various applications, services
and systems for contact tracing (identification and notification of those who come in contact with a carrier) have been
developed in different regions.
Despite the similar goal of automated detection of COVID-19 exposure systems as complementary solutions to manual
tracing (interviews with people diagnosed with COVID-19 to track down their recent contacts), their functionality,
technology, scale, required data and limitations are different and may not interoperate.
These systems are currently being deployed in different countries and many more are expected in the near future. In
particular, mobile devices with their contact tracing applications can support public health authorities in controlling and
containing the pandemic. In that purpose, E4P has been created to provide a technical answer to pandemic crises, not
limited to COVID-19, by specifying interoperable contact tracing systems.
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6 ETSI GR E4P 002 V1.1.1 (2021-02)
1 Scope
The present document provides a review of existing pandemic proximity detection methods, applications and other
aspects of a pandemic contact tracing system. The similarities and differences of the various available or upcoming
approaches are examined, particularly concerning but not limited to the degree of interoperability, security aspects, use
of centralized or decentralized approach, use of particular proximity detection methods and technologies, support of
different device platforms, epidemiological value and privacy aspects.
The review includes a grouping of various approaches into several similar types (e.g. centralized or decentralized
system) and provides examples of initiatives to which the approaches apply. The present document is also neutral in
terms of technologies and initiatives; however, the focus is on initiatives involving proximity sensing and networking
using mobile devices, and the applications and other technical enablers which can be installed on the devices.
The present document provides a basis for the analysis of suitable requirements for a standardized solution as specified
in ETSI GS E4P 003 [i.1]. It also relates to ETSI GS E4P 006 [i.2], ETSI GS E4P 007 [i.3] and ETSI GS E4P 008 [i.4].
2 References
2.1 Normative references
Normative references are not applicable in the present document.
2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee
their long term validity.
The following referenced documents are not necessary for the application of the present document but they assist the
user with regard to a particular subject area.
[i.1] ETSI GS E4P 003: "Requirements for pandemic contact tracing systems using mobile devices".
NOTE: Not yet released at the time of publication of the present document.
[i.2] ETSI GS E4P 006: "Device-based mechanisms for pandemic contact tracing systems".
NOTE: Not yet released at the time of publication of the present document.
[i.3] ETSI GS E4P 007: "Pandemic proximity tracing systems: Interoperability framework".
NOTE: Not yet released at the time of publication of the present document.
[i.4] ETSI GS E4P 008: "Back-end mechanisms for pandemic contact tracing systems".
NOTE: Not yet released at the time of publication of the present document.
[i.5] Inter-American Development Bank: "Census of COVID-19 apps"
NOTE: Internal work document, not publicly released.
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[i.6] Klinkenberg D.; Fraser C. and Heesterbeek H. (2006): "The Effectiveness of Contact Tracing in
Emerging Epidemics". PLoS ONE 1(1): e12.
NOTE 1: Available at http://dx.doi.org/10.1371/journal.pone.0000012.
NOTE 2: Available at
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0000012&type=printable.
[i.7] CDC: "Key Information to Collect During a Case Interview". Centers for Disease Control and
Prevention. May 21, 2020.
NOTE: Available at https://www.cdc.gov/coronavirus/2019-ncov/php/contact-tracing/keyinfo.html.
[i.8] CDC: "Notification of Exposure: A Contact Tracer's Guide for COVID-19". Centers for Disease
Control and Prevention. August 27, 2020.
NOTE: Available at https://www.cdc.gov/coronavirus/2019-ncov/php/notification-of-exposure.html.
[i.9] Ho HJ., Zhang ZX., Huang Z., Aung AH., Lim WY., Chow A.: "Use of a Real-Time Locating
System for Contact Tracing of Health Care Workers During the COVID-19 Pandemic at an
Infectious Disease Center in Singapore: Validation Study". J Med Internet Res 2020;
22(5):e19437.
NOTE 1: Available at http://dx.doi.org/10.2196/19437.
NOTE 2: Available at http://www.jmir.org/2020/5/e19437/.
[i.10] Kang C., Lee J., Park Y., Huh I., Ham H., Han J.; Kim, J., Na B.: (2020): "Coronavirus Disease
Exposure and Spread from Nightclubs, South Korea". Centers for Disease Control and Prevention
(CDC). Emerging Infectious Diseases, 26(10), 2499-2501.
NOTE 1: Available at https://dx.doi.org/10.3201/eid2610.202573.
NOTE 2: Available at https://wwwnc.cdc.gov/eid/article/26/10/20-2573_article.
[i.11] Ardron Mitra, Peter Eckersley et alter: "Unified research on privacy-preserving contact tracing and
exposure notification".
NOTE: Available at https://docs.google.com/document/d/16Kh4_Q_tmyRh0-
v452wiul9oQAiTRj8AdZ5vcOJum9Y/edit.
[i.12] European Commission: "Mobile contact tracing apps in EU Member States".
NOTE: Available at https://ec.europa.eu/info/live-work-travel-eu/health/coronavirus-response/travel-during-
coronavirus-pandemic/mobile-contact-tracing-apps-eu-member-states_en.
[i.13] MIT Technology Review: "Covid Tracing Tracker".
NOTE: Available at https://docs.google.com/spreadsheets/d/1ATalASO8KtZMx__zJREoOvFh0nmB-sAqJ1-
CjVRSCOw/edit#gid=1464910624.
[i.14] Wikipedia: "COVID-19 apps".
NOTE: Available at https://en.wikipedia.org/wiki/COVID-19_apps.
th
[i.15] Woodhams Samuel: "COVID-19 Digital Rights Tracker". TOP10VPN. March 20 , 2020.
NOTE: Available at https://www.top10vpn.com/research/investigations/covid-19-digital-rights-tracker/.
[i.16] Woodhams Samuel: "Covid-19 Digital Rights Tracker - Contact Tracing Apps Analysis".
NOTE: Available at https://docs.google.com/spreadsheets/d/1_BCKlMuniEhzvpQ-
ha0jhdksvqdINUAUHA8J9LSr_Dc/edit#gid=0.
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[i.17] Woodhams Samuel: "COVID-19 Digital Rights Tracker Supporting Data".
NOTE: Available at
https://docs.google.com/spreadsheets/d/1enCBRLVCo2Dp2B0AB3tEYvLc279i5LUuoGCzoelz8aQ/edit#
gid=0.
[i.18] ETSI: "E4P Terms of Reference". May 8, 2020.
NOTE: Available at https://portal.etsi.org/Portals/0/TBpages/E4P/Docs/ISG_E4P_ToR_D-
G_APPROVED_20200508.pdf.
[i.19] ETSI: "New ETSI group to develop standardization framework for secure smartphone-based
proximity tracing systems, helping to break COVID-19 transmission chains". Press release. Sophia
Antipolis, May 12, 2020.
NOTE: Available at https://www.etsi.org/newsroom/press-releases/1768-2020-05-new-etsi-group-to-develop-
standardization-framework-for-secure-smartphone-based-proximity-tracing-systems-helping-to-break-
covid-19-transmission-chains.
[i.20] ETSI: "ETSI's new group on COVID-19 tracing apps interoperability moving fast: officials elected
and work programme set up". Press release. Sophia Antipolis, June 11, 2020.
NOTE: Available at https://www.etsi.org/newsroom/press-releases/1780-2020-06-etsi-s-new-group-on-covid-19-
tracing-apps-interoperability-moving-fast-officials-elected-and-work-programme-set-up.
[i.21] Garcia-Menendez Miguel: "ETSI Launches Industry Specification Group: Europe for Privacy-
Preserving Pandemic Protection". CircleID. June 17, 2020.
NOTE: Available at http://www.circleid.com/posts/20200617-etsi-launches-europe-for-privacy-preserving-
pandemic-protection/.
[i.22] EC: "Coronavirus: Commission starts testing interoperability gateway service for national contact
tracing and warning apps". European Commission. Press release. September 14, 2020.
NOTE: Available at: https://ec.europa.eu/commission/presscorner/detail/en/ip_20_1606.
[i.23] EC: "Coronavirus: EU interoperability gateway goes live, first contact tracing and warning apps
linked to the system". European Commission. Press release. October 19, 2020.
NOTE: Available at https://ec.europa.eu/commission/presscorner/detail/en/ip_20_1904.
[i.24] Vaudenay Serge: "Centralized or Decentralized? The Contact Tracing Dilemma". EPFL. May 6,
2020.
NOTE: Available at https://eprint.iacr.org/2020/531.
[i.25] Asher Saira: "TraceTogether: Singapore turns to wearable contact-tracing Covid tech". BBC
News. Singapore, July 4, 2020.
NOTE: Available at https://www.bbc.com/news/technology-53146360.
[i.26] BBC News Services: "Singapore hands out coronavirus tracing devices". BBC.com. June 29,
2020.
NOTE: Available at https://www.bbc.com/news/business-53216450.
[i.27] Lausson Julien: "StopCovid: le gouvernement testera en juillet des objets connectés dédiés au
traçage des contacts". Numerama.com. June 23, 2020.
NOTE: Available at: https://www.numerama.com/tech/632530-stopcovid-le-gouvernement-testera-en-juillet-des-
objets-connectes-dedies-au-tracage-des-contacts.html.
[i.28] EIT Digital: "Joint efforts to develop COVID-19 contact tracing using physical tokens". Press
release. May 5, 2020.
NOTE: Available at https://www.eitdigital.eu/newsroom/news/article/join-efforts-to-develop-covid-19-contact-
tracing-using-physical-tokens/.
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[i.29] EIT: "Anonymous COVID-19 contact tracing using physical tokens". The European Institute of
Innovation & Technology. May 14, 2020.
NOTE: Available at: https://eit.europa.eu/news-events/news/anonymous-covid-19-contact-tracing-using-physical-
tokens.
[i.30] The Simmel Team: "Simmel Project".
NOTE: Available at https://simmel.betrusted.io/.
[i.31] The Simmel Team: "simmel-project". GitHub.com.
NOTE: Available at https://github.com/simmel-project/frontpage.
[i.32] Palakurthi Shranav: "Project Tracer: Confidential Contact Tracing for the Masses!". Hackster.io.
June 23, 2020.
NOTE: Available at: https://www.hackster.io/epicface2304/project-tracer-confidential-contact-tracing-for-the-
masses-a6e2dc.
[i.33] Palakurthi Shranav: "Project Tracer". Hackaday.io. June 23, 2020.
NOTE: Available at: https://hackaday.io/project/173344-project-tracer.
[i.34] Palakurthi Shranav: "project-tracer". GitHub.com.
NOTE: Available at https://github.com/shraiwi/project-tracer.
[i.35] Palakurthi Shranav: "Tracer Demo" (video). June 22, 2020.
[i.36] Bettr: "TraceSigma".
NOTE: Available at: https://sites.google.com/view/tracestick.
[i.37] Bettr: "TraceSigma". GitHub.com.
NOTE: Available at: https://github.com/bettr-xyz.
[i.38] Engineers.SG: "TraceSigma" (see video from July 7, 2020).
[i.39] Conecta Industria: "Una empresa asturiana presenta un producto para el contact tracing en la Feria
del Hogar de Gijón sin el uso de móvil ni geolocalización". August 7, 2020.
NOTE: Available at https://www.conectaindustria.es/tecnologia/002154/una-empresa-asturiana-presenta-un-
producto-para-el-contact-tracing-en-la-feria-del-hogar-de-gijon-sin-el-uso-de-movil-ni-geolocalizacion.
[i.40] SRP: "La tecnología de ADN Mobile Solutions, cerca de ti en la lucha contra el COVID-19".
Sociedad Regional de Promoción del Principado de Asturias. September 16, 2020.
NOTE: Available at https://www.srp.es/la-tecnologia-de-adn-mobile-solutions-cerca-de-ti-en-la-lucha-contra-el-
covid-19/.
[i.41] Arenschield Laura. "Using your phone's microphone to track possible COVID-19 exposure".
TechXplore.com. July 1, 2020.
NOTE: Available at https://techxplore.com/news/2020-07-microphone-track-covid-exposure.html.
[i.42] Luo Yuxiang, Cheng Zhang, Yunqi Zhang, Chaoshun Zuo, Dong Xuan, Zhiqiang Lin, Adam C.
Champion and Ness Shroff: "ACOUSTIC-TURF: Acoustic-based Privacy-Preserving COVID-19
Contact Tracing". Cornell University. arXiv.org. June 23, 2020.
NOTE: Available at https://arxiv.org/abs/2006.13362.
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[i.43] Yunqi Zhang; Luo, Yuxiang; Cheng Zhang; Chaoshun Zuo; Dong Xuan; Zhiqiang Lin; Adam C.
Champion and Ness Shroff. "Technical Report. ACOUSTIC-TURF: Acoustic-based Privacy-
Preserving COVID-19 Contact Tracing". June 23, 2020.
NOTE: Available at https://arxiv.org/pdf/2006.13362.pdf.
[i.44] Novak Ed, Zhuofan Tang and Qun Li: "Ultrasound proximity networking on smart mobile devices
for IoT applications". IEEE Internet of Things Journal 6, 1 (2018), 399-409.
[i.45] Santagati, G. E. and T. Melodia: "A Software-Defined Ultrasonic Networking Framework for
Wearable Devices". IEEE/ACM Transactions on Networking 25, 2, (2017) 960-973.
[i.46] Nandakumar, Rajalakshmi; Krishna Kant Chintalapudi; Venkat Padmanabhan and Ramarathnam
Venkatesan: "Dhwani: secure peer-to-peer acoustic NFC". ACM SIGCOMM Computer
Communication Review 43, 4 (2013), 63-74.
[i.47] Zhang Huanle, Wan Du, Pengfei Zhou, Mo Li and Prasant Mohapatra: "An acoustic-based
encounter profiling system". IEEE Transactions on Mobile Computing 17, 8 (2017), 1750-1763.
[i.48] Loh Po-Shen (n.d.): "NOVID".
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[i.49] Foy Kylie: "Signs of Covid-19 may be hidden in speech signals". MIT News. July 8, 2020.
NOTE: Available at https://news.mit.edu/2020/signs-covid-19-may-be-hidden-speech-signals-
0708?fbclid=IwAR2PAqm347cY_mQwYteCrDuAQENc5odij93RAIygMNmVhxIYu2VpUerPCcE.
[i.50] Quatieri, Thomas F; Tanya Talkar and Jeffrey S. Palmer: "A Framework for Biomarkers of
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NOTE 2: Available at https://ieeexplore.ieee.org/document/9103574.
3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the following terms apply: ®
Bluetooth low energy: low power wireless Personal Area Network (PAN) communication technology that can be used
over a short distance to enable smart devices to communicate
contact tracing: essential measure to fight an ongoing pandemic with the purpose of identifying and managing the
contacts of probable or confirmed cases to rapidly identify secondary cases that may arise after transmission from the
primary known cases in order to intervene and interrupt further onward transmission
NOTE: Contact tracing is the term used to describe the overall public health strategy and actions involved in
tracing and following up contacts. Mobile apps cannot be said to do 'contact tracing', but rather 'proximity
tracking' and 'exposure notification'; i.e. tracking and alerting users who have been in close proximity
with each other, which can support contact tracing.
Curve25519: state-of-the-art cryptographic function designed for use with the Diffie–Hellman key exchange protocol
and suitable for a wide variety of applications
NOTE: It is one of the fastest elliptic curve cryptography (ECC) curves and is not covered by any known patents.
The reference implementation is public domain software.
Diffie-Hellman key exchange protocol: method for safely distributing keys that allows two parties that have no prior
knowledge of each other to jointly establish a shared secret key over an insecure channel
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digital fragility: quality of an entity (organization, system, etc.) that determines its susceptibility to suffer an incident,
of "digital" nature, that disturbs its activity (besides causing other consequences for people, assets or the environment);
and of which possible materialization there is not always consciousness
exposure notification: feature of a mobile app that supports digital contact tracing by notifying to its user an exposure,
above/below thresholds specific to each contact tracing system, to a person later diagnosed as probable or confirmed
case ®
proximity tracking: feature of a mobile app that supports digital contact tracing by measuring Bluetooth signal
strength to determine whether two mobile devices were close enough together for their users to transmit the virus
respectively, to get infected by the virus
SecNumCloud (formerly Secure Cloud): initiative by the French National Cybersecurity Agency (ANSSI), aiming to
improve protection for public authorities and Operators of Vital Importance (OVIs)
NOTE: Launched in 2013, the idea under this quality seal was to create a label that demonstrated the high level of
security met by those cloud solution providers serving strategic business and government agencies.
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
API Application Programming Interface
APK Android application PacKage ®
NOTE: Android is a trademark of Google LLC.
CPU Central Processing Unit
DP-3T Decentralised Privacy-Preserving Proximity Tracing
E4P Europe for Privacy-Preserving Pandemic Protection ®
EBID Ephemeral Bluetooth IDentifier
EMR Electronic Medical Record
ENS Exposure Notification System
ENX Exposure Notification eXpress
EU European Union
FAQ Frequently Asked Questions
GDPR General Data Protection Regulation
GPS Global Positioning System
GR Group Report
GS Group Specification ®
HMS Huawei Mobile Services
ID IDentifier
IDPT Interoperable Digital Proximity Tracing
IDPT-FP Interoperable Digital Proximity Tracing - Full Protocol
I-EBID Interoperable EBID
ISG Industry Specification Group
NFC Near Field Communications
NTP Network Time Protocol
NUS Near Ultra Sound
PACT 1. Private Automated Contact Tracing (East Coast PACT)
2. Privacy-sensitive protocols And mechanisms for mobile Contact Tracing (West Coast PACT)
PIA Privacy Impact Analysis
PII Personally Identifiable Information
QR Quick Response [code]
RFID Radio Frequency IDentification
RSSI Received Signal Strength Indicator
SDK Software Development Kit
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TAN Transaction/Telephone Authentication Number
UI User Interface
UUID Unique User IDentifier
UWB Ultra Wide Band
UX User eXperience
4 Current landscape of pandemic contact tracing
4.1 Overview: a universe of apps
For decades, public health services have promoted contact tracing in communicable disease control. This has made it a
pillar of fight against pandemics. Traditionally, manual contact tracing has attempted to find all contacts of a confirmed
case to test or monitor them for infection with the ultimate goal to save lives by stopping the spread of a disease through
the location and isolation of new possible cases. Indeed, exhaustive manual pandemic contact tracing followed by
isolation of infected individuals and immunization of their surrounding communities may prove to be more effective
than universal immunization; but it is not always exempt of issues that may impact its effectiveness in addressing
infectious diseases. Limitation in number of human monitors (tracers), the need for training, the difficulty to identify
some contacts (e.g. people met in public transportation), etc. could undermine any tracing initiative. Here is where
digital solutions arise as a support service making manual pandemic contact tracing more efficient.
A recent study (see [i.5]) by the Inter-American Development Bank Group's innovation laboratory (IDB Lab) has
produced a census of several hundreds of COVID-19-related apps. Although not all of them are contact tracing apps, it
constitutes a true universe of apps.
4.2 Manual pandemic contact tracing
Contact tracing to identify persons who potentially have been infected by known victims, and to isolate/treat those with
secondary infections, is a proven way to contain an epidemic when full lock-down is not in place and inoculations are
not available. The value in reducing the total number of infections in a given time depends strongly on the latency for
symptoms and the mobility of the disease or people. Some sources (see [i.6]) have showed analytically that if latency is
high (e.g. like 14 days in the average case for COVID-19) then effective contact tracing can be extremely helpful in
containing outbreaks.
However, contact tracing also has resource costs. Conventional means of contact tracing requires interviewing the
infected patient(s) regarding their lifestyle and sustained contacts (e.g. less than 2 metre distance for 15 minutes) using a
long list of questions (see [i.7]) to trigger memories and elicit names/addresses. Many of the questions involve some
invasion of privacy, justified by the medical risks. Persons to carry out the questionnaires are typically themselves put at
higher risk of infection during the interview, and even more so during subsequent secondary and tertiary interviews
where apparently healthy people may be contacted at their homes/workplace. The interviewers also need significant
training to be effective (see [i.8]).
The reliance of conventional tracing on human memory, particularly of people who are sick or extremely worried, also
reduces the completeness of the results. In a direct test within a Singapore hospital (see [i.9]), a comparison was made
over two days between counting contacts of staff (162 persons) with patients (17 persons) based on patient medical
records (EMRs) and a detailed interview of staff the next-day, compared to RFID-tracing of staff. The RFID method
detected 54 contacts missed otherwise, the EMRs showed 99 contacts missed by RFID (but there is some doubt of
accuracy of the records), and all together 257 contacts were found. Self-reporting by staff identified only 36 of those
contacts. The lesson to learn is that, in a busy environment (here a hospital) the memory of contact with others may be
very spotty, even under ideal conditions.
In a real-world example (see [i.10]) in Seoul in early May 2020, an outbreak of Covid-19 was detected in association
with a nightclub district. By late May, using cell phone location data, credit card records, and lists of nightclub visitors,
officials identified and carried out screening of more than 35 000 visitors. They detected 246 new infections: 96 primary
cases, 32 secondary, and others that were 3, 4 and even 5 steps along the transmission chain from actual night club
visitors. This example used some very broad-based location data (cell area) but can mainly be considered
"conventional". The resource cost was obviously very high; however the mobility of the night-club visitors was also
very high: the infected persons returned home to ten different areas across South Korea. Finding and isolating them
rapidly was very important to avoid the need to impose lockdown on large parts of the country.
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The above examples help to make clear that an automated, privacy-preserving method of detecting potential contagion
and warning people to apply for screening could drastically reduce the investigative resource costs compared to
conventional contact tracing and greatly increase the speed and completeness of case discovery. Speedy screening of
persons likely to be infected is crucial to preventing the "chain reaction" of an outbreak (see [i.6]).
4.3 Digital pandemic contact tracing: initiatives per country
4.3.0 General
The following clauses provide a characterization (description) of a series of current digital contact tracing initiatives
(apps), both alive and under development, given by country (in alphabetical order).
The aim to include a representative sample of the European landscape, as well as a few additional and relevant
initiatives from abroad, has been among the very reasons for the final election of projects.
4.3.1 Austria (project "Stopp Corona")
Table 1: Austria's "Stopp Corona" project characterization
App's name
Stopp Corona.
Country
AT (Austria).
Official website (and source of this https://www.stopp-corona.at/ (in German)
characterization) available at https://www.roteskreuz.at/site/meet-the-stopp-corona-app/
Description Stopp Corona utilizes the ENS framework. Therefore, the app mainly
implements the user interface, the risk-score calculation, and the
communication with the backend. The backend is based on the ®
reference implementation provided by Google . The backend regarding
the exchange of the keys is hosted using Microsoft Azure.
There is no external validation regarding the reported state (see below).
To lower the risk of misuse, the reporting user has to provide a mobile
phone number. He will receive a TAN, which he has to provide as a
means for verification of the telephone number. The telephone number
will be stored, to identify the reporting user in case of misuse. The
telephone numbers are stored using an Austrian provider.
One speciality is, that the app introduces three types of keys:
• red keys: These are the usually submitted keys in the ENS
approach, indicating that the reporting user was diagnosed
COVID-19 by a physician. Users informed about a red
exposure are asked to self-quarantine for 14 days.
• yellow keys: In this case, the reporting user might be infected,
but he only did a self-assessment by answering a
questionnaire. This questionnaire is part of the app. The yellow
state was introduced to shorten the time of informing other
users. The reporting user is asked to do a COVID-19 test as
soon as possible. Users informed about a yellow exposure are
asked to self-quarantine for 7 days.
• green keys: This is to indicate, that the reporting user wants to
revoke some previously sent yellow or red keys.
In order to authenticate key-state updates a random value (UUID) is sent
together with the initial key upload. Updates are only accepted if the
same random value is provided.
Type
Exposure notification in support of contact tracing. ®
Technology
Bluetooth Low Energy.
Method ENS.
Voluntary nature Entirely.
A user can freely decide to participate in the system
...