| Literature DB >> 34983429 |
Yueting Tang1, Jiayu Sun2, Yumeng Yuan2, Fen Yao2, Bokun Zheng1, Gui Yang1, Wen Xie1, Guangming Ye3, Zhen Li1, Xiaoyang Jiao4, Yirong Li5.
Abstract
BACKGROUND: Serosurveillance is crucial in estimating the range of SARS-CoV-2 infections, predicting the possibility of another wave, and deciding on a vaccination strategy. To understand the herd immunity after the COVID-19 pandemic, the seroprevalence was measured in 3062 individuals with or without COVID-19 from the clinic.Entities:
Keywords: COVID-19; SARS-CoV-2; Serosurveillance
Mesh:
Substances:
Year: 2022 PMID: 34983429 PMCID: PMC8724638 DOI: 10.1186/s12879-021-07010-w
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Positive rate of SARS-CoV2 among different groups
| Characteristics | No. P | No. (%) 95%CI | |||
|---|---|---|---|---|---|
| IgM (+) | IgG (+) | NA(+) | CT(+) | ||
| Male | 1652 | 41 (2.48) 1.81–3.38 | 104 (6.30) 5.20–7.60 | 1 (0.06) 0.003–0.39 | 34 (2.06) 1.45–2.90 |
| Female | 1410 | 45 (3.19) 2.36–4.28 | 126 (8.94) 7.52–10.58 | 3 (0.21) 0.055–0.68 | 63 (4.47) 3.48–5.72 |
| P | 0.141 | 0.004 | 0.256 | 0.000 | |
| ≤ 20 | 56 | 2 (3.57) 0.62–13.38 | 2 (3.57) 0.62–13.38 | 0 | 0 |
| 21–40 | 1059 | 17 (1.61) 0.97–2.61 | 65 (6.14) 4.80–7.80 | 0 | 15 (1.42) 0.82–2.38 |
| 41–60 | 1262 | 44 (3.49) 2.57–4.69 | 104 (8.24) 6.81–9.93 | 3 (0.24) 0.06–0.75 | 49 (3.88) 2.92–5.14 |
| > 60 | 685 | 23 (3.36) 2.19–5.07 | 59 (8.61) 6.67–11.03 | 1 (0.15) 0.1–0.94 | 33 (4.82) 3.39–6.77 |
| P | 0.035 | 0.098 | 0.461 | 0.000 | |
| Fever clinic for patients | 493 | 51 (10.34) 7.87–13.46 | 117 (23.73) 20.1–27.79 | 1 (0.20) 0.01–1.31 | 64 (12.98) 10.21–16.35 |
| Fever clinic for medical staff | 16 | 0 | 4 (25.00) 8.33–52.59 | 1 (6.25) 0.33–32.29 | 3 (18.75) 4.97–46.31 |
| Internal medicine | 1395 | 21 (1.51) 0.96–2.33 | 70 (5.02) 3.96–6.33 | 1 (0.07) 0.004–0.46 | 23 (1.65) 1.07–2.50 |
| Surgery department | 659 | 9 (1.37) 0.067–2.67 | 18 (2.73) 1.68–4.37 | 1 (0.15) 0.008–0.98 | 2 (0.30) 0.05–1.22 |
| Obstetrics/gynecology/fertility | 135 | 1 (0.74) 0.04–4.67 | 4 (2.96) 0.95–7.88 | 0 | 2 (1.48) 0.26–5.79 |
| Pediatric Department | 4 | 0 | 1 (25) 1.32–78.06 | 0 | 0 |
| Oncology department | 261 | 3 (1.15) 0.30–3.60 | 8 (3.07) 1.43–6.18 | 0 | 2 (0.77) 0.13–3.04 |
| General department/other | 99 | 1 (1.01) 0.05–6.30 | 8 (8.08) 3.81–15.76 | 0 | 1 (1.01) 0.05–6.30 |
| P | 0.000 | 0.000 | 0.000 | 0.000 | |
| COVID-19 convalescent | 110 | 35 (31.82) 23.45–41.48 | 85 (77.27) 68.11–84.49 | 2 (1.82) 0.32–7.10 | 51 (46.36) 36.89–56.09 |
| SSC | 355 | 12 (3.38) 1.84–5.99 | 28 (7.89) 5.40–11.32 | 0 | 14 (3.94) 2.26–6.68 |
| SAC | 1295 | 22 (1.70) 1.09–2.61 | 74 (5.71) 4.54–7.16 | 1 (0.08) 0.004–0.5 | 19 (1.47) 0.91–2.33 |
| Attendance for other diseases | 1302 | 17 (1.30) 0.79–2.13 | 43 (3.30) 2.43–4.46 | 1 (0.08) 0.004–0.50 | 13 (1.00) 0.56–1.75 |
| P | 0.000 | 0.000 | 0.000 | 0.000 | |
| Tumor | 387 | 7 (1.81) 0.79–3.86 | 14 (3.62) 2.07–6.14 | 0 | 5 (1.29) 0.48–3.17 |
| CCD | 146 | 2 (1.37) 0.24–5.37 | 5 (3.42) 1.27–8.22 | 0 | 2 (1.37) 0.24–5.37 |
| Digestive diseases | 259 | 2 (0.77) 0.13–3.06 | 11 (4.25) 2.25–7.68 | 0 | 2 (0.77) 0.13–3.06 |
| Urogenital diseases | 141 | 0 | 3 (2.13) 0.55–6.57 | 0 | 1 (0.71) 0.04–4.48 |
| Nervous diseases | 51 | 2 (3.92) 0.68–14.59 | 2 (3.92) 0.68–14.59 | 1 (1.96) 0.68–14.59 | 1 (1.96) 0.10–11.79 |
| Hematological diseases | 24 | 1 (4.17) 0.22–23.12 | 1 (4.17) 0.22–23.12 | 0 | 0 |
| Other respiratory diseases | 64 | 1 (1.56) 0.08–9.54 | 0 | 0 | 1 (1.56) 0.08–9.54 |
| External injury | 90 | 1 (1.11) 0.058–6.90 | 2 (2.22) 0.39–8.56 | 0 | 0 |
| Pregnancy check-up | 68 | 1 (1.47) 0.08–9.01 | 2 (2.94) 0.51–11.16 | 0 | 1 (1.47) 0.08–9.01 |
| AIDS | 13 | 0 | 0 | 0 | 0 |
| Other | 59 | 0 | 3 (5.08) 1.32–15.06 | 0 | 0 |
| P | 0.584 | 0.881 | 0.006 | 0.967 | |
CI confidence interval; SSC screening for symptomatic conditions (the most common symptoms related to COVID-19 including fever, cough, chest tightness, diarrhea); SAC screening for asymptomatic conditions (health examination professionals were asymptomatic currently, but did not rule out close contacts or had a symptom related to COVID-19); CCD cardiovascular and cerebrovascular diseases; Other including autoimmune diseases, skin diseases, stomatitis, laryngeal eyewinker, poisoning, etc.
Fig. 1Temporal change of IgM and IgG in COVID-19 patients. A The curve shows that positive rates of IgM and IgG in patients were reduced after March 22. The small peak occurring on March 28 is due to the attendance of more COVID-19 convalescent and SAC patients at that time. B In general, the positive rate of IgM was higher positive rate in COVID-19 convalescents than the SAC and SCC individuals. C During all study periods, the COVID-19 convalescents showed a higher positive IgG rate than the SAC and SCC individuals