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. 2021 Jul 12;11(7):e050519. doi: 10.1136/bmjopen-2021-050519

Table 2.

Properties of model-based studies

Study Model-related properties Contact- and tracing app related properties Disease-related properties Modifyable properties
Model type Input parameter properties Tracing direction Sequential generations (n) Adoption rate app (%) R Incubation time Infectious period Probability of disease transmission Delay symptom onset and testing Delay testing and feedback app Quarantine effectiveness
Bradshaw 2020 (peer-reviewed) Branching-process model Distributions Bidirectional Infinite generations 53; 80 2.5 5.5 days Fitted to curve, value not specified Fitted to curve, value not specified 1 days 0 days 90%
Bulchandani 2020 (preprint)7 Branching-process model Based on exponential distributions Bidirectional 3-infinite generations 0–100 3.0 N/A* N/A N/R N/A† 0 days 100%
Cencetti 2020 (preprint)8 Continuous weighted temporal network Distributions Forward 1 generation 60; 80; 100 1.2; 1.5; 2.0 Fitted to curve, value not specified Fitted to curve, value not specified Fitted to curve, value not specified 2 days 0 days 0%–100%
Currie 2020 (peer-reviewed)17 ODE compartmental model Based on exponential distributions Forward 1 generation 0; 27; 40; 61; 80 2.5 2.0 days 11 days N/R 3 days N/R 90%
Ferrari 2020 (peer-reviewed) ODE compartmental model Based on exponential distributions Forward 1 generation 0; 25; 50; 75 1.5 5.1 days 10 days 10% 2 days N/R 90%
Ferretti 2020 (peer-reviewed)16 PDE compartmental model Distributions Forward 1 generation 0–100 2.0 5.5 days 12 days Fitted to curve, value not specified 1.6 days 0 days 0%–100%
Grimm 2020 (preprint)9 ODE compartmental model Based on exponential distributions Forward 1 generation 20–80 2.2; 3.0 5.0 days 10;12.5;14;20 days N/R N/R N/R 100%‡
Guttal 2020 (preprint)10 Individual-based network model Based on exponential distributions Bidirectional >1 generation 100 3.0; 4.0 N/A 20 days 0.2% N/R N/R 100%
Kretzschmar 2020 (peer-reviewed)15 Branching-process model Distributions Forward 1 generation 20; 40; 60; 80; 100 2.5 6.4 days 10 days 2%–12% 0 days 0 days 0%; 20%; 40%;
60%; 80%; 100%
Kucharski 2020 (peer-reviewed)14 Individual-based network model Distributions Forward 1 generation 53 2.6 5.0 days 5 days 20% within HH
6% outside HH
50% less for asymptomatic
0 days 0 days 90%
Kurita 2020 (peer-reviewed) ODE compartmental model Based on exponential distributions N/R 1 generation 0; 10; 20; 30; 40; 50;
60; 70; 80; 90; 100
1.5 6.6 days N/R N/R 2 days 0 days N/R
Nuzzo 2020 (peer-reviewed)20 ODE compartmental model Based on exponential distributions N/A§ N/A§ 0; 10; 20; 30; 40; 50;
60; 70; 80; 90
3.02 5.1 days N/R Fitted to curve, value not specified N/R N/R 100%
Pollmann 2020 (preprint)12 ODE compartmental model Based on exponential distributions and distributions Bidirectional >1 generation 60; 75; 90; 100 2.0–3.0–4.0 4.0; 7.4 days 10 days 7%¶ 0; 2; 4; 6 days N/R 100%
Scott 2020 (peer-reviewed) Agent-based model Distributions Forward 1 generation 0–50 Fitted to curve, value not specified 4.6 days 8–14 days Fitted to curve, value not specified 1 day 1 day 0% in HH
80%–100% in other settings
Shamil 2020 (preprint)11 Agent-based model Distributions Forward 1 generation 60; 75 Fitted to curve, value not specified 6.0 days 10 days N/R 0 days 0 days 100%

Model-specific characteristics of model-based studies looking at effectiveness of contact and tracing apps for SARS-CoV-2. Dashes (–) indicate a continuous range between numbers, semicolons indicate separate distinct values.

*Fraction of infections before symptoms are relevant.

†Isolation based on positive notification, not a positive test.

‡Changing app coverage covers imperfect isolation.

§No true tracing, fixed proportion cases will self-isolate.

¶Time-dependent, maximum value reported in table.

HH, household; N/A, not applicable; N/R, not reported; ODE, ordinary differential equations; PDE, partial differential equations; R, reproduction number.