Volume 27, Number 11—November 2021
Dispatch
Socioeconomic Patterns of COVID-19 Clusters in Low-Incidence City, Hong Kong
Gary K.K. Chung, Siu-Ming Chan, Yat-Hang Chan, Jean Woo, Hung Wong, Samuel Y. Wong, Eng Kiong Yeoh, Michael Marmot, and Roger Y. Chung
Table 1
Characteristics of local coronavirus disease case-patients with a valid residential address, Hong Kong, 2020*
| Characteristic | Total sample, N = 3,587 | Area-level income poverty rate† |
|||
|---|---|---|---|---|---|
| 1st quartile | 2nd quartile | 3rd quartile | 4th quartile | ||
| Mean age, y (SD) | 47.92 (19.96) | 44.20 (19.17) | 47.66 (18.65) | 49.93 (20.86) | 46.63 (19.60) |
| Sex | |||||
| M | 1,750 (48.8) | 158 (51.6) | 348 (47.4) | 712 (50.6) | 532 (46.6) |
| F |
1,837 (51.2) |
148 (48.4) |
386 (52.6) |
694 (49.4) |
609 (53.4) |
| Sizable infection clustering | |||||
| Noncluster cases | 2,809 (78.3) | 275 (89.9) | 617 (84.1) | 1,033 (73.5) | 884 (77.5) |
| Cluster cases‡ | 778 (21.7) | 31 (10.1) | 117 (15.9) | 373 (26.5) | 257 (22.5) |
| Living clusters | 159 (4.4) | 0 (0.0) | 3 (0.4) | 99 (7.0) | 57 (5.0) |
| Working clusters | 225 (6.3) | 8 (2.6) | 42 (5.7) | 77 (5.5) | 98 (8.6) |
| Dining clusters | 248 (6.9) | 15 (4.9) | 35 (4.8) | 137 (9.7) | 61 (5.3) |
| Entertainment clusters | 114 (3.2) | 8 (2.6) | 27 (3.7) | 48 (3.4) | 31 (2.7) |
| Others§ |
33 (0.9) |
1 (0.3) |
10 (1.4) |
12 (0.9) |
10 (0.9) |
| Case classification | |||||
| Infection source cases | 1,455 (40.6) | 133 (43.5) | 317 (43.2) | 528 (37.6) | 477 (41.8) |
| Probable local cases | 95 (2.6) | 29 (9.5) | 31 (4.2) | 24 (1.7) | 11 (1.0) |
| Local cases | 1,360 (37.9) | 104 (34.0) | 286 (39.0) | 504 (35.8) | 466 (40.8) |
| Cases epidemiologically linked to infection source cases | 2,132 (59.4) | 173 (56.5) | 417 (56.8) | 878 (62.4) | 664 (58.2) |
| Linked to probable local cases | 62 (1.7) | 12 (3.9) | 20 (2.7) | 22 (1.6) | 8 (0.7) |
| Linked to local cases |
2,070 (57.7) |
161 (52.6) |
397 (54.1) |
856 (60.9) |
656 (57.5) |
| Presence of symptoms | |||||
| Asymptomatic | 590 (16.4) | 44 (14.4) | 89 (12.1) | 262 (18.6) | 195 (17.1) |
| Symptomatic |
2,997 (83.6) |
262 (85.6) |
645 (87.9) |
1144 (81.4) |
946 (82.9) |
| Type of housing | |||||
| Public rental housing | 1,479 (41.2) | 6 (2.0) | 243 (33.1) | 591 (42.0) | 639 (56.0) |
| Subsidized home ownership | 409 (11.4) | 6 (2.0) | 137 (18.7) | 171 (12.2) | 95 (8.3) |
| Private housing | 1,377 (38.4) | 261 (85.3) | 307 (41.8) | 469 (33.4) | 340 (29.8) |
| Residential care homes | 116 (3.2) | 3 (1.0) | 6 (0.8) | 86 (6.1) | 21 (1.8) |
| Other |
206 (5.7) |
30 (9.8) |
41 (5.6) |
89 (6.3) |
46 (4.0) |
| Area-level population density# | |||||
| 1st quartile | 409 (11.4) | 82 (26.8) | 165 (22.5) | 102 (7.3) | 60 (5.3) |
| 2nd quartile | 752 (21.0) | 91 (29.7) | 177 (24.1) | 275 (19.6) | 209 (18.3) |
| 3rd quartile | 888 (24.8) | 55 (18.0) | 200 (27.2) | 310 (22.0) | 323 (28.3) |
| 4th quartile | 1,538 (42.9) | 78 (25.5) | 192 (26.2) | 719 (51.1) | 549 (48.1) |
*Values are no. (%) except as indicated. We used data current to October 31, 2020. †The 1st quartile is the wealthiest group and 4th quartile the poorest group. ‡The number of cluster cases differed from the sum of cluster cases across cluster types because one case was involved in both dining and working clusters. §Traveling, religious, grocery shopping activities. #The 1st quartile is lowest population density and 4th quartile the highest density.
Page created: September 01, 2021
Page updated: October 19, 2021
Page reviewed: October 19, 2021
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