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Mitigation of the spread of infection relies on targeted approaches aimed at preventing nonhousehold interactions. Contact tracing in the form of digital proximity tracing apps has been widely adopted in multiple countries due to its perceived added benefits of tracing speed and breadth in comparison to traditional manual contact tracing. Assessments of user responses to exposure notifications through a guided approach can provide insights into the effect of digital proximity tracing app use on managing the spread of SARS-CoV-2.
The aim of this study was to demonstrate the use of Venn diagrams to investigate the contributions of digital proximity tracing app exposure notifications and subsequent mitigative actions in curbing the spread of SARS-CoV-2 in Switzerland.
We assessed data from 4 survey waves (December 2020 to March 2021) from a nationwide panel study (COVID-19 Social Monitor) of Swiss residents who were (1) nonusers of the SwissCovid app, (2) users of the SwissCovid app, or (3) users of the SwissCovid app who received exposure notifications. A Venn diagram approach was applied to describe the overlap or nonoverlap of these subpopulations and to assess digital proximity tracing app use and its associated key performance indicators, including actions taken to prevent SARS-CoV-2 transmission.
We included 12,525 assessments from 2403 participants, of whom 50.9% (1222/2403) reported not using the SwissCovid digital proximity tracing app, 49.1% (1181/2403) reported using the SwissCovid digital proximity tracing app and 2.5% (29/1181) of the digital proximity tracing app users reported having received an exposure notification. Most digital proximity tracing app users (75.9%, 22/29) revealed taking at least one recommended action after receiving an exposure notification, such as seeking SARS-CoV-2 testing (17/29, 58.6%) or calling a federal information hotline (7/29, 24.1%). An assessment of key indicators of mitigative actions through a Venn diagram approach reveals that 30% of digital proximity tracing app users (95% CI 11.9%-54.3%) also tested positive for SARS-CoV-2 after having received exposure notifications, which is more than 3 times that of digital proximity tracing app users who did not receive exposure notifications (8%, 95% CI 5%-11.9%).
Responses in the form of mitigative actions taken by 3 out of 4 individuals who received exposure notifications reveal a possible contribution of digital proximity tracing apps in mitigating the spread of SARS-CoV-2. The application of a Venn diagram approach demonstrates its value as a foundation for researchers and health authorities to assess population-level digital proximity tracing app effectiveness by providing an intuitive approach for calculating key performance indicators.
In recent efforts to limit the number of COVID-19 infections, a respiratory disease caused by SARS-CoV-2, digital proximity tracing apps have been deployed in multiple countries [
There has been a surge of interest in evaluating the effectiveness of digital proximity tracing apps in mitigating the spread of SARS-CoV-2. Particular interest is placed on the added benefit of exposure notifications from digital proximity tracing apps relative to manual contact tracing in containing nonhousehold spread [
An approach based on Venn diagrams can be used to assess the effectiveness of digital proximity tracing apps in mitigating the spread of the SARS-CoV-2 infection. The use of Venn diagrams enables a structured approach to count outcomes across several subpopulations and for each period cross-sectionally. Very importantly, a Venn diagram approach also provides an intuitive framework for assessing generalizability and missing population segments of study data. Hence, when applied to population-level data, the approach enables the identification and construction of appropriate indicators in a reproducible manner, given the available data, to evaluate the impact of digital proximity tracing apps on users taking mitigative actions. The aim of this study was to demonstrate the use of Venn diagrams in assessing key indicators for exposure notification performance and effectiveness in mitigating the spread of SARS-CoV-2. We hope to guide health researchers and authorities in collecting relevant population-level data.
We applied a Venn diagram approach on data from COVID-19 Social Monitor, a nationwide panel study [
The Swiss digital proximity tracing app (SwissCovid app) was launched on June 25, 2020. The adoption of the app in the Swiss health care system and pandemic mitigation response has been described extensively in previous studies [
This approach makes use of Venn diagrams to visualize the co-occurrence of SARS-CoV-2 outcomes of interest based on digital proximity tracing app use [
Descriptive attributes of Venn diagram subpopulations.
Group | Tested for SARS-CoV-2 | Positive test for SARS-CoV-2 | Exposure notification (exposure notification) | Quarantine | Remarks |
A | True | True | False | False | N/Aa |
B | True | True | True | False | N/A |
C | True | True | True | True | Tested positive; received exposure notification; quarantined |
D | True | True | False | True | Tested positive; did not receive exposure notification; quarantined |
E1 | True | False | True | False | Tested negative; received exposure notification; not quarantined |
E2 | False | False | True | False | Not tested; received exposure notification; not quarantined |
F1 | True | False | True | True | Tested negative; received exposure notification; quarantined |
F2 | False | False | True | True | Not tested; received exposure notification; quarantined |
G1 | True | False | False | True | Tested negative; did not receive exposure notification; quarantined |
G2 | False | False | False | True | Not tested; did not receive exposure notification; quarantined |
T | True | False | False | False | Tested negative; did not receive exposure notification; not quarantined |
N | False | False | False | False | Not tested; did not receive exposure notification, not quarantined |
aN/A: not applicable to the applied scope; all individuals who tested positive were immediately placed in isolation.
The allocation of individuals to each subsection, and their resulting overlap, enabled a more thorough definition of subpopulations. Once the subpopulations were identified, they were labeled according to the Venn diagram allocation. These labels facilitated the calculation of key digital proximity tracing effectiveness indicators by identifying relevant numerators and denominators (eg, the number of app users who received exposure notifications and entered into quarantine versus the number of app users who received exposure notifications but did not enter into quarantine). Furthermore, the data visualizations through Venn diagrams enabled an overview of available data, time horizons, as well as missing and available populations for analyses. A Venn diagram approach thereby provides a general methodology to facilitate the formulation of research hypotheses, aid the selection of suitable databases, and help to define key performance indicators by referencing to specific, labeled diagram segments. For our study, we defined a priori guiding criteria and definitions (
Data from COVID-19 Social Monitor [
Our study used data from 4 survey waves: December 14 to December 23, 2020 (December survey); January 25 to February 4, 2021 (January survey); February 22 to March 3, 2021 (February survey); and March 29 to 08 April 8, 2021 (March survey). The December survey was used as the baseline for this study due to high SARS-CoV-2 incidence in Switzerland at that time, which averaged approximately 4000 newly detected COVID-19 cases daily and a test positivity rate of 16% [
Descriptive statistics were calculated for survey respondent demographics and to assess mitigative actions taken by the participants within the study period. Analyses were performed on the full study sample, as well as across the 3 subgroups of digital proximity tracing app nonusers and digital proximity tracing app users who did or did not receive an exposure notification.
Performance measures were constructed on the basis of labeled Venn segments representing subpopulations with the attributes shown in
We assessed the mitigative actions taken by individuals who received an exposure notification. These actions included (1) calling an information hotline to obtain advice on appropriate actions, (2) getting tested after receiving an exposure notification, and (3) entering into quarantine, including entering into quarantine as recommended by health care professionals or ordered by health authorities. The assessed key indicators are derived from the subpopulations observed in the Venn diagram based on digital proximity tracing app use.
We report 95% confidence intervals based on an exact binomial test for proportions for the estimation of subpopulation sizes and key indicators. Analyses were performed in Stata (version 16.1; StataCorp LLC). Continuous variables were represented as median (interquartile range), and categorical variables were represented as count (percentage) with corresponding 95% confidence intervals.
For the COVID-19 Social Monitor project, the Ethics Committee of the Canton of Zurich confirmed that it does not fall under the Swiss Human Research Law (BASEC-Nr Req-2020-00323). This exemption was granted due to the fact that data were collected and treated anonymously throughout the project.
As per the decision of the Cantonal Ethics Commission of Zurich, explicit informed consent was not needed from participants for this particular study. However, participants gave their general permission to be part of research studies when accepting the invitation to the panel from which we sampled our respondents. Participation in the study was voluntary, and participants could withdraw from the study at any time.
We included 12,525 assessments from 2403 participants in the final study cohort (
From the study cohort, 319 (319/2403, 13.3%) respondents reported having at least one of the following chronic illnesses: asthma, chronic obstructive pulmonary disease, diabetes, hypertension, cardiovascular disease, stroke, and cancer.
At the baseline survey (December 2020), 19.3% (236/1222) of app nonusers, 28.2% (325/1152) of app users who did not receive an exposure notification, and 34.5% (10/29) of app users who received an exposure notification reported an average monthly household income greater than 10,000 CHF (approximately US $10,886.43).
Flowchart of assessed panel survey data and associated SARS-CoV-2 incidence values. For the national daily case numbers, the values represent the daily average of SARS-CoV-2 cases in each month, with the values in parentheses representing their respective standard deviations. EN: exposure notification.
Respondent demographics, self-reported health risks, and mitigative actions.
Characteristic | Full sample (n=2403) | Nonusers (n=1222) | App users (n=1152) | App users and received exposure notifications (n=29) | |
Age (in years), median (IQR) | 49 (35-59) | 49 (35-58) | 49 (36-59) | 40 (29-52) | |
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Female | 1171 (48.7) | 593 (48.5) | 566 (49.1) | 12 (41.4) |
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Male | 1232 (51.3) | 629 (51.5) | 586 (50.9) | 17 (58.6) |
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No partner | 668 (27.8) | 353 (28.9) | 310 (26.9) | 5 (17.2) |
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Living with partner | 1518 (63.2) | 755 (61.8) | 739 (64.1) | 24 (82.8) |
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Not living with partner | 217 (9.0) | 114 (9.3) | 103 (8.9) | 0 (0.0) |
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Has children | 245 (10.2) | 123 (10.1) | 116 (10.1) | 6 (20.7) |
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Does not have children | 2158 (89.8) | 1099 (89.9) | 1036 (89.9) | 23 (79.3) |
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Swiss | 2173 (90.4) | 1095 (89.6) | 1051 (91.2) | 27 (93.1) |
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Swiss and other | 132 (5.5) | 72 (5.9) | 59 (5.1) | 1 (3.4) |
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Non-Swiss | 98 (4.1) | 55 (4.5) | 42 (3.6) | 1 (3.4) |
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German | 1964 (81.7) | 973 (79.6) | 965 (83.8) | 26 (89.7) |
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French | 274 (11.4) | 160 (13.1) | 113 (9.8) | 1 (3.4) |
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Ticino | 165 (6.9) | 89 (7.3) | 74 (6.4) | 2 (6.9) |
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Only mandatory schooling | 64 (2.7) | 42 (3.4) | 22 (1.9) | 0 (0.0) |
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Completed professional education | 1737 (72.3) | 901 (73.7) | 811 (70.4) | 25 (86.2) |
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University or university of applied sciences | 602 (25.1) | 279 (22.8) | 319 (27.7) | 4 (13.8) |
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Not working | 721 (30.0) | 370 (30.3) | 344 (29.9) | 7 (24.1) |
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Currently working | 1682 (70.0) | 852 (69.7) | 808 (70.1) | 22 (75.9) |
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≤6000 | 657 (27.3) | 392 (32.1) | 260 (22.6) | 5 (17.2) |
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6000-10,000 | 783 (32.6) | 391 (32.0) | 381 (33.1) | 11 (37.9) |
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>10,000 | 571 (23.8) | 236 (19.3) | 325 (28.2) | 10 (34.5) |
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No answer | 392 (16.3) | 203 (16.6) | 186 (16.1) | 3 (10.3) |
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Smoker | 507 (21.1) | 287 (23.5) | 211 (18.3) | 9 (31.0) |
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Self-reported chronic illnessc | 319 (13.3) | 169 (13.8) | 149 (12.9) | 1 (3.4) |
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Always used protective masks when recommended | 2335 (97.2) | 1167 (95.5) | 1140 (99.0) | 28 (96.6) |
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Always stayed at home except for essential tasks | 1561 (65.0) | 738 (60.4) | 804 (69.8) | 19 (65.5) |
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Always kept recommended distance | 2225 (92.6) | 1103 (90.3) | 1097 (95.2) | 25 (86.2) |
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Always refrained from visits | 1583 (65.9) | 743 (60.8) | 824 (71.5) | 16 (55.2) |
Number of physical contacts, median (IQR) | 3 (1-5) | 3 (2-5) | 3 (1-5) | 3 (2-4) |
aCHF: Swiss franc; At the time of publication, the exchange rate was approximately US $1=0.92 CHF.
bMore than one or no answer is possible; therefore, percentages in this category do not add to 100%.
cAt least one of the following chronic illnesses: asthma, chronic obstructive pulmonary disease, diabetes, hypertension, cardiovascular disease, stroke, or cancer.
During the high-incidence period in December 2020 (ie, baseline), most participants reported consistent adherence, as opposed to occasional or no adherence, to wearing protective masks (2335/2403, 97.2%) and maintaining appropriate distance (2225/2403, 92.6%) (
On average, 76.8% (938/1222) of app nonusers, 83.9% (966/1152) of app users who did not receive an exposure notification, and 75.9% (22/29) of app users who received an exposure notification reported adherence to at least one of the 4 mitigative measures (
Baseline respondent mitigative actions based on reported SwissCovid app use with 95% confidence intervals. DPT: digital proximity tracing; EN: exposure notifications.
Based on outcomes reported across the 4 survey waves from December 2020 to March 2021, the respondent sample is visualized in a Venn diagram according to 4 categories (
Overall (of the 2403 respondents), 46 (1.9%) respondents tested positive for SARS-CoV-2 in the follow-up period, 29 (1.2%) received exposure notifications, and 130 (5.4%) were placed into quarantine. In segment C, 6 (6/46, 13%) respondents who tested positive for SARS-CoV-2 reported having received an exposure notification. In segments E1 and F1 (14/29, 48.3%) were respondents who received exposure notifications and who tested negative for SARS-CoV-2, of whom 7 (7/29, 24.1%) respondents in segment F1 were placed into quarantine after having received exposure notifications. By contrast, in segments E2 and F2, 9 (9/29, 31%) respondents who received exposure notifications were not tested for SARS-CoV-2; the respondent in F2 was still placed into quarantine (
Venn diagram representation of mitigative actions taken by 4 survey subpopulations (in bold) after follow-up: (1) respondents who were tested for SARS-CoV-2 in the past 4 weeks (white circle), (2) respondents who tested positive for SARS-CoV-2 (yellow circle), (3) respondents who received exposure notifications (red circle), and (4) respondents who were placed in quarantine by Swiss cantonal health services or by a physician (blue circle). Sample sizes of specific segments are indicated in the diagram, with the values in [square brackets] reflecting the number of DPT app users in a given segment. Each (non)overlap represents a subpopulation of the survey respondents.
Subpopulation cumulative mitigative actions and outcomes from the Venn diagram based on SwissCovid app use after respondent follow-up.
Groupa | Nonusers, n | App users, n | All (n=2403), n | Percentage of entire sample (95% CI) | |
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No notifications | Received exposure notification |
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C | 0 | 0 | 6 | 6 | 0.2 (0.1-0.5) |
D | 19 | 21 | 0 | 40 | 1.7 (1.2-2.3) |
E1 | 0 | 0 | 7 | 7 | 0.3 (0.1-0.6) |
E2 | 0 | 0 | 8 | 8 | 0.3 (0.1-0.7) |
F1 | 0 | 0 | 7 | 7 | 0.3 (0.1-0.6) |
F2 | 0 | 0 | 1 | 1 | 0.04 (0.001-0.02) |
G1 | 23 | 23 | 0 | 46 | 1.9 (1.4-2.5) |
G2 | 17 | 13 | 0 | 30 | 1.2 (0.8-1.8) |
N | 992 | 875 | 0 | 1867 | 77.7 (76.0-79.3) |
T | 171 | 220 | 0 | 391 | 16.3 (14.8-17.8) |
aThe letters correspond to the subpopulations in the Venn diagram in
Denominators of subpopulations were selected to assess key indicators of SwissCovid app performance in reducing the spread of SARS-CoV-2 based on the mitigative actions taken and outcomes of interest by respondent groups (
Overall, 49.2% (95% CI 47.1%-51.2%) of all participants reported using the SwissCovid app in at least one follow-up survey. App users contributed to 57.1% (95% CI 52.7%-61.5%) of SARS-CoV-2 tests taken, 58.7% (95% CI 43.2%-73%) of positive SARS-CoV-2 tests and 54.6% (95% CI 45.7%-63.4%) of respondents who entered into quarantine in our sample.
Test positivity among those who sought SARS-CoV-2 testing was 8.9% (95% CI 5.5%-13.6%) among app nonusers, 8% (95% CI 5%-11.9%) among app users who did not receive exposure notifications, and 30% (95% CI 11.9%-54.3%) among app users who received exposure notifications.
Entering into quarantine was reported by 4.8% (95% CI 3.7%-6.2%) of the app nonusers, 5% (95% CI 3.8%-6.4%) of the app users who did not receive exposure notifications, and 48.3% (95% CI 29.5-67.5%) of the app users who received exposure notifications. Similarly, entering into quarantine following testing for SARS-CoV-2 was reported by 19.7% (95% CI 14.6%-25.7%) of the app nonusers, by 16.7% (95% CI 12.4%-21.7%) of the app users who did not receive exposure notifications, and by 65% (95% CI 40.8%-84.6%) of the app users who received exposure notifications.
The percentage of respondents who received exposure notifications among those who tested positive (22.2%, 95% CI 8.6%-42.3%) for SARS-CoV-2 at a later point in time was higher than app users who tested negative (5.5%, 95% CI 3%-9%).
Selection of appropriate numerators and denominators from a Venn diagram based on SwissCovid digital proximity tracing app use after respondent follow-up. Letters in square brackets—[]—reflect subpopulations (Venn segments) of app users and those in curly brackets—{}— reflect the subset of individuals who did not use the app.
Indicator | Numerator | Denominator | % (95% CI) | ||||
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All | [C,D,E1,E2,F1,F2,G1,G2,N,T] | C,D,E1,E2,F1,F2,G1,G2,N,T | 49.15 (47.13-51.17) | |||
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Tested | [C,D,E1,F1,G1,T] | C,D,E1,F1,G1,T | 57.14 (52.66-61.54) | |||
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Tested positive | [C,D] | C,D | 58.70 (43.23-73.00) | |||
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Quarantined | [C,D,F1,F2,G1,G2] | C,D,F1,F2,G1,G2 | 54.62 (45.65-63.36) | |||
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Nonuser | {D,G1,T} | {D,G1,G2,N,T} | 17.43 (15.34-19.68) | |||
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App user | [D,G1,T] | [D,G1,G2,N,T] | 22.92 (20.52-25.45) | |||
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App user and received exposure notifications | [C,E1,F1] | [C,E1,E2,F1,F2] | 68.97 (49.17-84.72) | |||
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Nonuser | {D} | {D,G1,T} | 8.92 (5.46-13.58) | |||
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App user | [D] | [D,G1,T] | 7.95 (4.99-11.90) | |||
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App user and received exposure notifications | [C] | [C,E1,F1] | 30.00 (11.89-54.28) | |||
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Nonuser | {D,G1,G2} | {D,G1,G2,N,T} | 4.83 (3.70-6.18) | |||
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App user | [D,G1,G2] | [D,G1,G2,N,T] | 4.95 (3.77-6.36) | |||
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App user and received exposure notifications | [C,F1,F2] | [C,E1,E2,F1,F2] | 48.28 (29.45-67.47) | |||
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Nonuser | {D,G1} | {D,G1,T} | 19.72 (14.60-25.70) | |||
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App user | [D,G1] | [D,G1,T] | 16.67 (12.38-21.72) | |||
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App user and received exposure notifications | [C,F1] | [C,E1,F1] | 65.00 (40.78-84.61) | |||
App users who received an exposure notification who later tested positive | [C] | [C,D] | 22.22 (8.62-42.26) | ||||
App users who received an exposure notification who later tested negative | [E1,F1] | [E1,F1, G1,T] | 5.45 (3.01-8.97) |
Recommended mitigative actions taken among respondents who received an exposure notification (segments C, E1, E2, F1, F2, n=29) are reported in
Most respondents (17/29, 58.6%) who received exposure notifications sought SARS-CoV-2 testing and 7 (7/29, 24.1%) respondents called the federal information hotline. From these respondents, 22 (22/29, 75.9%) who received an exposure notification undertook at least one recommended mitigative action, while 5 (5/29, 17.2%) respondents explicitly stated to have ignored the exposure notification (
In group C, all 6 individuals reported to have sought testing after receiving an exposure notification: 4 (4/6, 66.7%) respondents reported having symptoms, and 2 (2/6, 33.3%) respondents reported entering into quarantine in response to the exposure notifications, even though one of these respondents reported not having symptoms.
Having contact with positive tested individuals or household members was almost always cited as a quarantine reason in groups C, F1, and F2 (with 1 exception). However, 5 (71.4%) out of 7 individuals in group E1 did not report possible contacts to positive tested individuals as a quarantine reason and yet still sought testing for SARS-CoV-2.
Tree diagram of subpopulation mitigative actions after follow-up in response to exposure notifications from the SwissCovid app. MCT: manual contact tracing.
We were able to isolate subpopulations of interest and define performance indicators for digital proximity tracing app effectiveness. From our assessment, we found that a greater proportion of digital proximity tracing app users who received an exposure notification tested positive, in comparison to digital proximity tracing app users who did not receive an exposure notification and digital proximity tracing app nonusers. Our findings also suggest that the receipt of exposure notifications may contribute to SARS-CoV-2 transmission mitigation, as observed with most users from our cohort who voluntarily sought testing or called the federal information hotline, while half of these users received recommendations to self-isolate or quarantine as a result of manual contact tracing. Possible transmission mitigation was also observed in respondents who sought testing and who tested positive after receiving exposure notifications.
A previous cross-sectional analysis [
Subpopulations visible in segments E1 (ie, individuals who tested negative, did not enter into quarantine and received an exposure notification) and E2 (ie, individuals who did not get tested, did not enter into quarantine and received an exposure notification) are currently not captured by any official statistics in Switzerland. Tracking responses to exposure notifications is challenging in Switzerland, since no data are systematically collected on individuals seeking testing after they have received exposure notifications, such as recording the reason for testing [
Positive test results for SARS-CoV-2 among app users who did not receive exposure notifications (8%, 95% CI 5%-11.9%) nonusers were similar (8.9%, 95% CI 5.5-13.6%) and of comparable magnitude to the officially reported test positivity values in Switzerland [
Our study also illustrates the usability and value of a Venn diagram approach to contextualize population- or survey-based evaluations of exposure notifications. We find that this method, and the extensive database used in this approach, provide a visual and analytical basis for assessing digital proximity tracing app effectiveness. Despite being based on over 12,500 follow-up surveys, our outcomes of interest such as SARS-CoV-2 infections (46/2403, 1.9%) and exposure notifications (29/2403,1.2%) were relatively rare. Nevertheless, the sample is likely well reflective of the population of app users as the sociodemographic characteristics associated with a higher propensity for electronic survey participation and SwissCovid app use likely overlap [
Our study has some limitations. Due to the scarcity of relevant digital proximity tracing–related exposure notification outcomes, our study had limited statistical power. Owing to the mode of data collection (web-based panel surveys), the respondents in our sample may reflect subpopulations with above-average literacy and, possibly, higher adherence to recommended preventive actions against the SARS-CoV-2 infection. Therefore, our results might not be generalizable to the broader Swiss population. Also, while survey respondents are provided full anonymity, partial non- or overreporting of having received exposure notifications, of SARS-CoV-2 testing and positivity, as well as of nonadherence to measures, might have occurred. Furthermore, considering the small sample size of participants who received an exposure notification, findings of possible associated mitigative responses should be viewed as preliminary. Nevertheless, given the privacy-preserving nature of digital proximity tracing app design, survey-based exposure notification studies are among the few sources of data available to make assessments on their effectiveness in mitigating the spread of infection. As such, despite the limitations presented by surveys in including participants who received exposure notifications, our results are some of the first available to provide quantitative insights on the contribution of exposure notifications in digital proximity tracing app users taking mitigative actions. Lastly, the panel data did not provide enough granularity to recreate the full cascade sequence of risk exposure. Rather, the panel survey focused on gathering information on digital proximity tracing usage and associated mitigative actions yet not information on the premise surrounding any possible exposure notifications. Therefore, our data cannot univocally demonstrate causality of exposure notifications and SARS-CoV-2 transmission prevention.
In our paper, we presented the Venn diagram as a tool to facilitate and streamline the evaluation of the role of digital proximity tracing apps in curbing the spread of the SARS-CoV-2 virus. By isolating subpopulations through a Venn diagram approach, a higher proportion of digital proximity tracing app users who tested positive after receiving an exposure notification was observed in comparison to digital proximity tracing app users who did not receive an exposure notification or digital proximity tracing app nonusers. Our findings also revealed that more than 3 out of 4 digital proximity tracing app users who received exposure notifications performed at least one recommended mitigative action, such as seeking SARS-CoV-2 testing or calling a federal information hotline, while half of these users received a recommendation to self-isolate or quarantine. An assessment, using a Venn diagram approach, of a larger population than the one presented in our study would allow the opportunity to assess the effectiveness of digital proximity tracing apps on users taking mitigative actions and their associated exposure risk with greater statistical power. This could, in turn, assist health authorities and researchers in identifying possible areas of improvement for digital proximity tracing apps alone, or in combination with manual contact tracing, by assessing effectiveness in curbing the spread of infection in a reproducible manner.
Subpopulation mitigative actions, Venn diagram analysis, and standardized questions on SwissCovid app use.
Swiss franc
This study was partially funded by the Digital Society Initiative. The COVID-19 Social Monitor project was funded by the Federal Office of Public Health and Health Promotion Switzerland.
PD wrote the first draft of the manuscript, analyzed data, and approved the final manuscript. VN analyzed data and revised and approved the final manuscript. AM and MH collected and analyzed data and revised and approved the final manuscript. VvW designed the study, interpreted data, wrote the first draft, and approved the final manuscript.
VvW had a mandate by the Swiss Federal Office of Public Health to evaluate the SwissCovid App; however, this study was planned and executed independently, without any involvement of the Swiss Federal Office of Public Health.