Table 1.

Literature estimates: this table contains study-level data for the number of index cases, secondary cases and total household contacts

Name	Index cases	Secondary infections	Household contacts	Average household	SAR (corrected)	SAR (uncorrected)	Rh (corrected)	Rh (uncorrected)	Correction	Contacts quarantined
Bi et al., Shenzhen, China*	391	77	686	2.75	16% (12–20%)	11% (9–14%)	0.21 (0.17––0.26)	0.17 (0.14–0.20)	FNR	False
Boscolo-Rizzo et al., Treviso, Italy	179	54	269	2.5	36% (25–48%)	20% (15–24%)	0.35 (0.28–0.42)	0.23 (0.19–0.27)	AR/FNR	True
Burke et al., USA	10	2	19	2.9	22% (7–40%)	14% (4–25%)	0.29 (0.14–0.44)	0.21 (0.09–0.33)	AR/FNR	True
Chaw et al., Brunei*	19	28	264	14.89	15% (10–21%)	11% (8–15%)	0.67 (0.59–0.75)	0.60 (0.52–0.68)	FNR	True
Chen et al., Ningbo, China**	157	49	272	2.73	18% (14–23%)	18% (14–22%)	0.24 (0.20–0.28)	0.24 (0.19–0.28)	–	False
Cheng et al., Taiwan	100	10	151	2.51	15% (8–23%)	8% (4–12%)	0.18 (0.10–0.26)	0.11 (0.06–0.15)	AR/FNR	True
Dawson et al., Wisconsin, USA*	26	16	64	3.46	31% (19–43%)	23% (15–32%)	0.43 (0.33–0.52)	0.36 (0.27–0.45)	FNR	False
Fateh-Moghadam et al., Trento, Italy	1489	500	3546	3.38	27% (21–34%)	14% (13–15%)	0.39 (0.33–0.45)	0.25 (0.24–0.27)	AR/FNR	True
Jing et al., Guangzhou, China**	215	93	542	3.52	17% (14–20%)	17% (14–20%)	0.30 (0.27–0.34)	0.30 (0.26–0.34)	–	False
Korea CDC, South Korea	30	9	119	4.96	17% (8–26%)	9% (5–14%)	0.39 (0.27–0.53)	0.26 (0.16–0.36)	AR/FNR	False
Kwok et al., Hong Kong	53	24	206	4.88	23% (14–32%)	12% (8–16%)	0.47 (0.36–0.56)	0.32 (0.25–0.40)	AR/FNR	True
Laxminarayan et. al., Tamin Nadu, India*	997	380	4066	5.07	13% (11–15%)	9% (8–10%)	0.34 (0.30–0.38)	0.28 (0.26–0.29)	FNR	False
Li et al., Wuhan, China**	105	64	392	4.73	17% (13–20%)	16% (13–20%)	0.38 (0.33–0.43)	0.38 (0.33–0.43)	–	True
Luo et al., Guangzhou, China**	347	96	946	3.72	10% (9–12%)	10% (8–12%)	0.22 (0.19–0.25)	0.22 (0.19–0.25)	–	True
Park, Choe et al., South Korea**	5706	1250	10 592	2.85	12% (11–12%)	12% (11–12%)	0.18 (0.17–0.19)	0.18 (0.17–0.19)	–	True
Park, Kim et al., Seoul, South Korea*	97	34	225	3.31	21% (14–27%)	15% (11–20%)	0.32 (0.25–0.39)	0.26 (0.21–0.32)	FNR	True
Rosenberg et al., New York, USA*	229	131	343	2.49	47% (39–56%)	37% (32–42%)	0.41 (0.37–0.46)	0.36 (0.33–0.39)	FNR	False
Son et al., Busan, Korea*	108	16	212	2.96	12% (7–17%)	8% (5–12%)	0.18 (0.12–0.25)	0.14 (0.09–0.20)	FNR	False
Sun et al., Zhejiang, China*	148	189	598	5.04	41% (34–48%)	31% (28–35%)	0.62 (0.58–0.66)	0.56 (0.53–0.58)	FNR	False
Wang, Ma et al., Wuhan, China*	85	47	155	2.82	38% (28–48%)	29% (22–36%)	0.41 (0.34–0.47)	0.34 (0.29–0.40)	FNR	True
Wang, Pan et al., Beijing, China*	585	111	714	2.22	21% (17–26%)	16% (13–18%)	0.20 (0.17–0.24)	0.16 (0.14–0.18)	FNR	True
Wang, Tian et al., Beijing, China*	124	77	335	3.7	30% (23–38%)	23% (18–27%)	0.45 (0.39–0.51)	0.38 (0.33–0.42)	FNR	False
Wang, Zhou et al., Wuhan, China	25	10	43	2.72	35% (18–52%)	21% (12–31%)	0.37 (0.25–0.48)	0.27 (0.17–0.36)	AR/FNR	False
Wu, Huang et al., Zhuhai, China**	35	48	148	5.22	32% (24–38%)	30% (24–38%)	0.57 (0.51–0.62)	0.56 (0.50–0.61)	–	False
Wu, Song et al., Hangzhou, China*	144	50	280	2.94	24% (17–31%)	18% (14–22%)	0.32 (0.26–0.38)	0.26 (0.21–0.30)	FNR	False
Xin et al., Qingdao, China**	31	19	125	5.03	16% (10–23%)	16% (10–21%)	0.39 (0.30–0.48)	0.38 (0.29–0.47)	–	False
Yu et al., Wuhan, China	560	143	1396	3.49	20% (14–26%)	10% (9–12%)	0.33 (0.27–0.39)	0.20 (0.18–0.23)	AR/FNR	True
Zhang et al., Shandong, China*	11	12	93	9.45	19% (10–28%)	14% (7–20%)	0.60 (0.48–0.71)	0.53 (0.42–0.64)	FNR	False
van der Hoek et al., Netherlands**	54	47	155	3.87	30% (23–37%)	29% (22–35%)	0.46 (0.40–0.52)	0.45 (0.39–0.50)	–	False
Global meta-estimate	12060	3586	26 956	3.23	24% (20–28%)	18% (14–21%)	0.34 (0.30–0.38)	0.28 (0.25–0.32)
China	2963	1085	6725	3.27	24% (19–30%)	19% (15–24%)	0.35 (0.30–0.41)	0.30 (0.26–0.35)
Not China	9097	2501	20 231	3.22	24% (17–32%)	17% (12–22%)	0.35 (0.28–0.42)	0.27 (0.21–0.33)
East Asia	9076	2456	18 494	3.04	21% (17–26%)	16% (13–20%)	0.30 (0.26–0.34)	0.25 (0.21–0.29)
Not East Asia	2984	1130	8462	3.83	33% (21–46%)	23% (14–34%)	0.48 (0.39–0.57)	0.39 (0.29–0.50)
Small household	7467	1741	13 244	2.77	29% (19–40%)	20% (13–27%)	0.34 (0.25–0.41)	0.26 (0.20–0.33)
Medium households	3164	1072	7701	3.43	23% (16–30%)	18% (12–23%)	0.35 (0.29–0.42)	0.30 (0.24–0.36)
Large households	1429	773	6011	5.21	22% (15–30%)	18% (12–25%)	0.48 (0.40–0.57)	0.42 (0.33–0.52)
Contacts quarantined	9335	2363	18 875	3.02	21% (16–28%)	14% (11–18%)	0.30 (0.24–0.36)	0.23 (0.19–0.27)
Contacts not quarantined	2725	1223	8081	3.97	26% (20–32%)	21% (15–26%)	0.43 (0.37–0.49)	0.38 (0.32–0.44)

It includes estimates and 95% confidence intervals of study-level SAR and R_h (with and without AR/FNR adjustments). The weight columns contain the contribution of each study towards the meta-estimate. A high SAR value does not always imply a high R_h value, or vice versa. SAR measures the prevalence of infection among susceptible individuals, whereas R_h measures the growth of infection within households. The relationship between the two measures is described by the equation: SAR = R_h × (#total infected)/(#susceptible). Assuming a fixed ratio of primary to secondary infections, SAR is inversely proportional to the relative number of susceptible individuals. Studies that have larger numbers of susceptible members (larger average household size) tend to have smaller SAR values. Conversely, studies that have smaller household sizes tend to have larger SAR values.