| Literature DB >> 33116979 |
Dahai Zhao1,2, Haijiang Lin3, Zhiruo Zhang4.
Abstract
INTRODUCTION: In less than two months, the COVID-19 outbreak in China was controlled through the stringent strategies of screening and isolation. This article aims to use empirical data from all cases from a prefecture-level city of China to introduce and examine the feasibility and efficiency of the screening and isolation strategies and how these were essential in combatting the COVID-19 outbreak.Entities:
Keywords: COVID-19; China; isolation; pandemic control; screening
Year: 2020 PMID: 33116979 PMCID: PMC7549023 DOI: 10.2147/RMHP.S269573
Source DB: PubMed Journal: Risk Manag Healthc Policy ISSN: 1179-1594
Description of All Confirmed Cases of COVID-19 in Taizhou
| Variables | All Cases | New Arrivals | Local Patients | |
|---|---|---|---|---|
| Age, years | 0.08 | |||
| Mean (SD) | 47.3(14.2) | 45.6(13.0) | 49.8(15.5) | |
| Range | 4–87 | 4–74 | 13–87 | |
| ≤19 | 4(2.7%) | 2(2.4%) | 2(3.3%) | |
| 20–39 | 38(26.0%) | 23(27.1%) | 15(24.6%) | |
| 40–59 | 76(52.1%) | 49(57.6%) | 27(44.3%) | |
| ≥60 | 28(19.2%) | 11(12.9%) | 17(27.9%) | |
| Sex | 0.42 | |||
| Male | 78(53.4%) | 43(50.6%) | 35(57.4%) | |
| Female | 68(46.6%) | 42(49.4%) | 26(42.6%) | |
| Occupation | 0.58 | |||
| Without jobs or household work | 14(9.6%) | 6(7.1%) | 8(13.1%) | |
| Agriculture worker | 39(26.7%) | 23(27.1%) | 16(26.2%) | |
| Factory workers | 11(7.5%) | 4(4.7%) | 7(11.5%) | |
| Business workers | 68(46.6%) | 43(50.6%) | 25(41.0%) | |
| Government workers or teachers | 4(2.7%) | 3(3.5%) | 1(1.6%) | |
| Retired | 5(3.4%) | 3(3.5%) | 2(3.3%) | |
| Students or infants | 5(3.4%) | 3(3.5%) | 2(3.3%) | |
| First symptoms | 0.04* | |||
| Without symptoms | 19(13.0%) | 13(15.3%) | 6(9.8%) | |
| Symptoms with fever | 61(41.8%) | 41(48.2%) | 20(32.8%) | |
| Symptoms without fever | 66(45.2%) | 31(36.5%) | 35(57.4%) | |
| First hospitals | 0.05 | |||
| Private clinics | 15(10.3%) | 7(8.2%) | 8(13.1%) | |
| Township or community health centers | 15(10.3%) | 10(11.8%) | 5(8.2%) | |
| County-level hospitals | 71(48.6%) | 35(41.2%) | 36(59.0%) | |
| Tertiary hospitals | 45(30.8%) | 33(38.8%) | 12(19.7%) | |
| Days between exposures to symptoms | 0.001** | |||
| Total number | 100 | 54 | 46 | |
| Mean (SD) | 6.4(3.7) | 5.4(3.3) | 7.7(3.7) | |
| Range | 1–17 | 1–14 | 2–17 | |
| Days between symptoms to confirmation | 0.08 | |||
| Total number | 128 | 73 | 55 | |
| Mean (SD) | 5.7(3.6) | 5.2(3.4) | 6.3(3.8) | |
| Range | 1–17 | 1–16 | 1–17 |
Notes: *P<0.05; **P<0.01.
Figure 1Framework and implementation of screening, isolation and confirmation of COVID-19 in Taizhou.
Description of Tracing All Confirmed Cases of COVID-19 in Taizhou
| Variables | First Round (New Arrivals) | Second Round | Third Round | Fourth Round | |
|---|---|---|---|---|---|
| Wuhan | Other areas | ||||
| Number of cases (%) | 75(51.4) | 10(6.8) | 31(21.2) | 25(17.1) | 5(3.4) |
| Dates of confirmation onset | 1/21 | 1/22 | 1/25 | 1/30 | 2/2 |
| Last Day of confirmation | 2/7 | 2/15 | 2/12 | 2/14 | 2/8 |
| First day of exposure to confirmation | 1/10 | 1/11 | 1/13 | 1/15 | 1/23 |
| Last day of exposure to confirmation | 1/24 | 1/27 | 1/24 | 1/24 | 1/30 |
| Cases of missing exposure dates (persons) | 18 | 2 | 0 | 8 | 1 |
Notes: Cases in the second round were close contacts of cases from the first round, and so on. This table uses date format type as month/date. For example,1/21 means January 21; all dates are in 2020.
Determinants of Early Detection and Confirmation of COVID-19 in Taizhou
| Variables | Days Between Exposures to Symptoms | Days Between Symptoms to Confirmations | ||||
|---|---|---|---|---|---|---|
| Std. Error | Std. Error | |||||
| Age | 0.010 | 0.027 | 0.708 | 0.016 | 0.023 | 0.494 |
| Sex | 0.022 | 0.717 | 0.975 | 0.792 | 0.625 | 0.208 |
| Occupation | 0.343 | 0.267 | 0.201 | 0.426 | 0.237 | 0.075 |
| New arrivals or local patients | 2.424 | 0.713 | 0.001** | 2.449 | 0.706 | 0.001** |
| First symptoms | 1.681 | 0.613 | 0.007** | |||
| First hospitals | −0.269 | 0.376 | 0.477 | |||
| Days between exposures to symptoms | −0.270 | 0.092 | 0.004** | |||
| R square of the model | 0.120 | 0.295 | ||||
Notes: This table did not include the patients whose data on days between exposure to symptoms were missing. The total number of cases of this table is 100. **P<0.01.