Table 3 Data on epidemiological parameters. WT: Wildtype. VOC: Variant of concern. N/D: no data

1

Adam, 2020 [11]

0.43

(0.29, 0.67)

[observed offspring distribution and negative binomial distribution]

0.33

(0.13, 0.98)

[additional likelihood model based on all local clusters]

0.58

(0.45, 0.72)

[observed offspring distribution and negative binomial distribution]

0.74

(0.58, 0.97)

[add. likelihood model based on all local clusters]

19%

Note: 69% of primary cases did not generate secondary cases

1,038 cases 533 cases linked to 1 of 137 clusters

N/D

23/01/2020 – 28/04/2020

Hong Kong

WT

2

Bi, 2020 [20]

0.58 (0.35, 1.18)

0.4 (0.3, 0.5)

8.9% (3.5, 10.8%)

391 cases (1,286 contacts)

N/D

14/01/2020 – 12/02/2020

Shenzhen, China

WT

3

Endo, 2020 [7]

Estimate for R0 set to 2.5:0.1 (0.05, 0.2)

Joint estimation of R and k: 95%CI: (0.04, 0.2)

k point estimate for R0=2.5

Joint estimation of R and k: 95% CI: (1.4, 12)

~10%

2,788 cases

N/D

Up to 27/02/2020

36 countries

WT

4

Guo, 2022 [21]

0.33 (0.17, 0.62)

1.34 (0.94, 2.19)

20.3% (12.7, 29.6%)

234 cases (2 clusters)

N/D

02/01/2022 – 21/01/2022

Hong Kong

Omicron BA.1 + BA.2

5

Gupta, 2022 [22]

0.04 (0.03, 0.04).

0.23 (0.20, 0.26)

6824 cases (all cases)

09/03/2020 – 13/06/2020

Karnataka state, India

WT

0.12 (0.11, 0.15))

0.75 (0.62, 0.91)

8.7%

Note: 79.4% of primary cases did not generate secondary cases

956 cases (those with contacts confirmed to have been traced)

Asymptomatic:

n=753 R=0.41 (0.32, 0.52) k=0.12 (0.09–0.15)

Symptomatic:

n=203 R=2.04 (1.56–2.67) k=0.29 (0.23, 0.37)

09/03/2020 – 13/06/2020

0.22 (0.17, 0.27)

0.91 (0.72, 1.15)

12.4%

Note: 71.2% of primary cases did not generate secondary cases

3 largest clusters: 394 cases (#1: 221 cases, #2: 97 cases, #3: 76 cases)

Bellary cluster:

n=221 R=1.04 (0.76, 1.40) k=0.23 (0.17, 0.30)

Delhi convention cluster:

n=97 R=0.84 (0.54, 1.25) k=0.34 (0.22-0.48)

Pharmaceutical company cluster:

n=76 R=0.80 (0.48, 1.29) k=0.32 (0.20-0.46)

09/03/2020 – 21/07/2020

6

Hasan, 2020 [23]

Jakarta-Depok 0.06 (0.05, 0.07)

Batam 0.20 (0.09, 0.31)

Jakarta-Depok

6.79

(2.79, 13.07)

Batam

2.47

(1.03, 4.48)

10–15%

Jakarta-Depok 1,199

Batam 89 cases

N/D

Jakarta-Depok

02/03/2020 – 31/03/2020

Batam

19/03/2020 – 07/04/2020

Jakarta-Depok and Batam region, Indonesia

WT

7

He, 2020 [24]

0.70 (0.59, 0.98)

0.69

(0.62, 0.77)

N/D

9,120 cases

N/D

15/01/2020 – 29/02/2020

Mainland China

WT

8

James, 2021 [26]

All subclinical cases before alert level:

1.11 (0.15-∞)

All subclinical cases at alert level:

0.29 (0.10, 2.05)

All subclinical cases before alert level:

0.70 (0.18, 1.40)

All subclinical cases at alert level:

0.52

(0.25, 0.83)

“20% of cases among adults responsible for 65–85% of transmission” [26]

1,499 cases (627 domestic cases were assigned to 18 clusters)

Domestic clinical cases before alert level:

<10 years:

n=10 R=0.87 (0.33, 1.38) k=3.17 (0.32, ∞)

10-65 years:

n=336 R= 1.49 (1.41, 1.56) k=0.70 (0.60, 0.81)

>65 years:

n=36 R=1.51 (1.14, 1.81) k=0.50 (0.30, 0.84)

Domestic clinical cases at alert level:

<10 years:

n=23 R=0.25 (0.09, 0.44) k=0.80 (0.13, ∞)

10-65 years:

n=433 R=0.63 (0.58, 0.67) k=0.41 (0.32, 0.50)

>65 years:

n=65 R=1.27 (1.08, 1.49) k=0.23 (0.15, 0.35)

25/03/2020 – 27/04/2020

Proclaim of alert level:

25/03/2020

New Zealand

WT

9

Kirke-gaard, 2021 [6]

0.11 (0.08, 0.18)

For R=1.4, 10% of cases cause 70-87% of all infections

N/D

98 municipalities (surveillance at national level)

N/D

26/02/2020 – 17/11/2020

Denmark

WT

10

Ko, 2022 [27]

0.23 (0.22, 0.25)

0.47 (0.45, 0.49)

13.3%

(12.8, 13.9%)

Note: 76.7% of primary cases did not generate secondary cases

67,761 cases data

16,471 primary cases analysed for secondary transmission

Age: 0-19y

n=847 R=0.36 (0.30, 0.43) k=0.22 (0.17, 0.29)

Age 20-39y

n=7647 R=0.41 (0.38, 0.43) k=0.21 (0.19, 0.23)

Age 40-69y:

n=5832 R=0.52 (0.49, 0.55) k=0.29 (0.26, 0.32)

Age 70+y:

n=1996 R=0.62 (0.55, 0.69) k=0.21 (0.18, 0.24)

15/01/2020 – 31/08/2020

Japan

WT

11

Kremer, 2021 [28]

HK: 0.43

(0.38, 0.49)*

India: 0.50

(0.50, 0.51)*

Rwanda: 0.56

(0.29, 0.83)*

HK: 0.583

(0.448, 0.718)

India: 0.484

(0.480, 0.494)

Rwanda: 0.259

(0.216, 0.302)

HK: 28.8%

(20.8, 34.5%)

India: 31.9%

(31.4, 32.4%)

Rwanda: 32.3%

(22.3, 39.0%)

HK: 1,038 cases

India: 84,965 cases (575,071 exposed)

Rwanda: 795 cases

N/D

HK:

23/01/2020 – 18/04/2020*

India: By 01/08/2020*

Rwanda: By 31/12/2020*

Hong Kong (HK)

India

Rwanda

WT

12

Kwok, 2020 [19]

HK: 2.30

(0.39, ∞) / (0.02, 4.58)*

JP: 0.51

(0.26, 1.42) / (0.21, 1.59)*

SG 1.78

(0.36, ∞) / (0.09, 3.47)*

HK: 0.61

(0.47, 0.78)

JP: 0.48

(0.39, 0.59)

SG: 0.70

(0.55, 0.89)

N/D

89 (HK), 251 (JP) and 103 (SG) cases

These consisted of 35 (HK), 131 (JP), and 31 (SG) clusters of secondary cases

N/D

Up to 03/03/2020

Hong Kong (HK)

Japan (JP)

Singapore (SG)

WT

13

Lau, 2020 [18]

0.45 (Cobb County)

0.43 (Dekalb)

0.39 (Fulton)

0.49 (Gwinnett)

0.32 (Dougherty)

Mean R0:

3.30

(2.34, 5.2)

2% of primary cases generate 20% of total infections

9,559 symptomatic cases

Age group <60 years:

2.78 (2.10, 4.22) times larger average of the mean number of offspring than >60y cases, and tend to produce a more extreme number of offspring

01/03/2020 – 03/05/2020

Georgia, USA

WT

14

Laxmina-rayan, 2020 [14]

0.51 (0.49, 0.52)

1.1 to 1.4

N/D

Note: 71% of primary cases did not generate secondary cases

84,965 cases (575,071 exposed)

N/D

05/03/2020 – 01/08/2020

Tamil Nadu and Anda Pradesh State, India

WT

15

Lee, 2021 [29]

0.20 (0.14, 0.28)

Reff 2.26 (2.02, 2.53)

N/D

3,088 cases (61 clusters) analysed (cluster: >20 cases)

Settings:

Religious groups: k= 0.16 (0.06, 0.38)

Convalescent home: k= 0.5 (0.11, 0.22)

Hospital: k= 0.34 (0.09, 1.27)

Workplace and school: k= 0.20 (0.10, 0.42)

Leisure facilities: k= 0.23 (0.11, 0.49)

04/03/2020 – 04/12/2020

Seoul, South Korea

WT

16

Miller, 2020 [30]

2.97 (2.86, 3.08)*

N/D

5-10%

213 cases

N/D

Up to 22/04/2020

Israel

WT

17

Paireau, 2022 [8]

Contact tracing: 0.17

(0.12, 0.22)

Retrospective investigation: 0.28

(0.09, 0.47)

mean number of secondary cases identified per index case: 0.3–0.9

Contact tracing: 10%

Retrospective investigation:

16%

6,082 contacts of 735 cases were traced;

some infectors/ infectees paired by epidemiological investigation

Superspreading events occurrence:

work (10 cases),

neighbourhood dinner (6 cases),

family/religious gathering (10 cases),

mixed type settings: family, hospital and co-worker contact (31 cases)

24/01/2020 – 30/03/2020

France

WT

18

Riou, 2020 [17]

0.54 90% high density interval (0.014, 6.95)

2.2 90% high density interval (1.4, 3.8)

N/D

stochastic simulations that were consistent with the epidemiological findings at study date

N/D

Up to 18/01/2020

Global

WT

19

Ryu, 2022 [31]

Period 1:

0.64

(0.57, 0.72)

Period 2:

0.85

(0.75, 0.98)

No exact value depicted

Period 1:

23%

(22, 24%)

Period 2:

25%

(24, 26%)

Period 1:

19,635 cases

(2,169 transmission pairs)

Period 2:

34,569 cases

(3,609 transmission pairs)

N/D

Period 1:

11/07/2021 – 24/07/2021

Period 2:

25/07/2021 – 15/08/2021

South Korea

Delta (B.1.617.2)

20

Shi, 2021 [32]

G1: 0.484

(0.226, 1.038)

G2: 0.284

(0.110, 0.735)

G3: 0.107

(0.024, 0.482)

G4: 0.048

(0.004, 0.602)

Overall G1-G4: 0.205

(0.126, 0.334)

G1-G2: 1.64

(1.16–2.40) (before control measures)

G2-G3: 0.39

(0.24, 0.58)

G3-G4: 0.31

(0.12, 0.58)

N/D

183 cases (2,100 total close contacts)

Stratifying by symptoms of infector:

G1-G2 asymptomatic: R=2.44 (1.21, 6.75)

G1-G2 symptomatic: R=1.63 (1.03, 2.59)

G2-G3 asymptomatic: R=0.15 (0.00, 0.35)

G2-G3 symptomatic: R=0.54 (0.32, 0.84)

G3-G4 asymptomatic: R=0.06 (0.00, 0.21)

G3-G4 symptomatic: R=0.62 (0.24, 1.48)

21/01/2020 – 10/04/2020

Wanzhou, China

WT

21

Sun, 2020 [33]

0.30 (0.23, 0.39)

2.19 (2.08, 2.36)

15%

1,178 cases (15,648 contacts)

(19,227 separate exposure events)

Subset: 870 SARS-CoV-2 cases, 14,622 close contacts (exclusion of cases whose infected contacts reported a travel history to Wuhan):

Household contacts: k=0.72

Extended family contacts: k=0.64

Social contacts: k=0.19

Community contacts: k=0.14

16/01/2020 – 03/04/2020

Hunan province, China

WT

22

Tariq, 2020 [34]

0.11 (0.05, 0.25)

0.61 (0.39, 1.02)

N/D

247 cases (18 clusters)

N/D

23/01/2020 – 17/03/2020

Singapore

WT

23

Toth, 2021 [10]

0.43

(0.02, 2.0)

(called d_h here, variability of transmission within households);

converted to overall k=0.18

1.12 (0.78, 1.56)

N/D

28,321 household members

(in 9,224 households)

No subgroups of “household member” analysed

04/05/2020 – 15/08/2020

Utah, USA

WT

24

Tsang, 2022 [35]

For all contact settings: 0.34

(0.27, 0.41)

For all secondary cases:

0.25

(0.12, 0.37)

1.12 (0.63, 1.62)

20%

(15, 26%)

Note: 64% (55, 72%) of primary cases did not generate secondary cases

199 cases reported

97 primary cases in 89 close contact groups;

3,158 contacts analysed in 81 clusters.

Setting:

Household: k=0.34 (0.25, 0.43)

Healthcare facility: k=0.076 (0.05, 0.10)

Workplaces: k=0.054 (0.031, 0.076)

Air transportation: k=0.014 (0.006, 0.022)

22/01/2020 – 30/03/2020

Shandong Province, China

WT

25

Wang, 2020 [36]

0.23 (0.13, 0.39)

1.23 (1.09, 1.39)

N/D

208 cases

10 randomly selected phylogenetic trees: k estimate was higher than for the maximum clade credibility (MCC) tree. This subgroup analysis suggests that the phylogeny tends to underestimate superspreading events, as the MCC is the more accurate method.

24/12/2019 – 14/02/2020*

China

WT

26

Zhang, 2020 [37]

0.25 (0.13, 0.88)

0.67 (0.54, 0.84)

N/D

135 cases (43 transmission chains)

Before 01/02/2020

k=0.14 (0.04, 0.63) R= 0.74 (0.39, 1.61)

After 01/02/2020

k= 0.77 (0.14, 31.47) R= 0.53 (0.29, 0.96)

21/01/2020 – 26/02/2020

Tianjin, China

WT

27

Zhao, 2022 [38]

0.26 (0.16, 0.41)

0.91 (0.63, 1.36)

15% (12, 19%)

126 cases

N/D

05/2021 – 12/2021

Guangdong China

Delta (B.1.617.2)

28

Zhao, 2021 [9]

Zero-truncated version:

Dataset 1: 0.37

(0.29, 0.48)

Dataset 2: 0.32

(0.15, 0.64)

Dataset 3: 0.18

(0.01, 1.79)

N/D

N/D

Dataset 1: 2,214 cases (1407 transmission pairs, 807 infectors, 1,241 terminal cases)

Dataset 2: 290 cases (169 transmission pairs, 91 infectors, 153 terminal cases)

Dataset 3: 47 cases (36 clusters, 7 infectors, 11 terminal cases))

Study compares results to non-truncated version (Xu et al.; Adam et al.; Zhang et al.): k values in zero-truncated framework are lower than those obtained by the non-truncated version for all datasets

Otherwise no subgroups analysed

Dataset 1:

15/01/2020 – 29/02/2020

Dataset 2: 23/01/2020 – 28/04/2020

Dataset 3: 21/01/2020 – 26/02/2020

Dataset 1: Mainland, China

Dataset 2: Hong Kong

Dataset 3: Tianjin, China

WT