| Literature DB >> 33035674 |
Shu-Wan Jian1, Hao-Yuan Cheng2, Xiang-Ting Huang3, Ding-Ping Liu4.
Abstract
AIM: Comprehensive case investigation and contact tracing are crucial to prevent community spread of COVID-19. We demonstrated a utility of using traditional contact tracing measures supplemented with symptom tracking and contact management system to assist public health workers with high efficiency.Entities:
Keywords: COVID-19; Contact tracing; Coronavirus; Digital tool; Outbreak response
Mesh:
Year: 2020 PMID: 33035674 PMCID: PMC7537669 DOI: 10.1016/j.ijid.2020.09.1483
Source DB: PubMed Journal: Int J Infect Dis ISSN: 1201-9712 Impact factor: 3.623
Figure 1Distribution of 457 COVID-19 cases and 8,051 close contacts by the time of symptom onset for cases and the time of last exposure for close contacts, Taiwan, January 11–August 26, 2020. The figure does not display 30 asymptomatic confirmed cases.
Figure 2Timeline from symptom onset to contact follow-up and the information flow during COVID-19 contact tracing in Taiwan. (A) The median time and IQR (interquartile range) between steps from last day of exposure to contact quarantine and the start of health status reporting. The dashed line represents that the timeline between the last day of exposure and the day of contact identification was made retrospectively. (B) Information flow from case confirmation to contact health status monitoring during contact tracing activities. Arrows with a dashed line represent information flow via emails/text messages/calls. NIA: National Immigration Agency; NNDSS: National Notifiable Disease Surveillance System; TRACE: Infectious disease contact tracing platform and management system.
Characteristics of close contacts of confirmed COVID-19 patients, Taiwan, January 11–August 26, 2020.
| Status of index case | Imported | Locally-acquired | Total |
|---|---|---|---|
| Characteristics of close contacts (n) | 6616 | 1435 | 8051 |
| Years of age, n(%) | |||
| 0–9 | 122(1.9) | 85(5.9) | 207(2.5) |
| 10–19 | 416(6.3) | 74(5.1) | 490(6.1) |
| 20–29 | 2470(37.3) | 323(22.5) | 2793(34.7) |
| 30–39 | 1305(19.7) | 251(17.5) | 1556(19.3) |
| 40–49 | 810(12.2) | 192(13.4) | 1002(12.4) |
| 50–59 | 677(10.2) | 133(9.3) | 810(10.1) |
| 60–69 | 401(6.1) | 112(7.8) | 513(6.4) |
| 70+ | 127(1.9) | 120(8.4) | 247(3.1) |
| NA | 288(4.4) | 145(10.1) | 433(5.4) |
| Gender, n(%) | |||
| Female | 3874(58.6) | 831(57.9) | 4705(58.4) |
| Male | 2689(40.6) | 562(39.2) | 3251(40.4) |
| NA | 53(0.8) | 42(2.9) | 95(1.2) |
| Hospital/clinic contacts, n(%) | |||
| Yes | 79(1.2) | 544(37.9) | 623(7.7) |
| No | 6537(98.8) | 891(62.1) | 7428(92.3) |
| Flight contacts, n(%) | |||
| Yes | 3523(53.2) | 0(0.0) | 3523(43.8) |
| No | 3093(46.8) | 1435(100.0) | 4528(56.2) |
| Duration of quarantine, day (IQR) | 12.0 (10.0–14.0) | 12.0 (9.0–14.0) | 11.3 (10.0–14.0) |
COVID-19 = coronavirus disease 2019; IQR = interquartile range.