In this study, 2,170 patients were analysed, with a median age of 47 years and 59% women. Of the total number of users, 1% were CCP and 0.2% ACD. The migrant population attending screening represented 1.6%, and there were 38.8% of users with a AMG of 2, 22.7% with a AMG of 3 and 5.0% with a AMG of 4 (Table 1).
Table 1
Characteristics of the total population, the first screening and the second screening.
|
Total
(N= 2,170)
|
1st Screening
(n=691)
|
2nd Screening
(n=1.479)
|
p-value
|
Women
|
1281 (59.03)
|
417 (60.3%)
|
864 (58.4%)
|
0.421
|
Age*
|
47.4 (20.09)
|
47.21 (20.98)
|
48.27 (19.65)
|
|
Age group
|
|
|
|
0.078
|
under 20 years old
|
255 (11.75)
|
97 (14.0%)
|
158 (10.7%)
|
|
20-39 years old
|
403 (18.57)
|
129 (18.7%)
|
274 (18.5%)
|
|
40-59 years old
|
842 (38.80)
|
248 (35.9%)
|
594 (40.2%)
|
|
60 years of age or older
|
670 (30.87)
|
217 (31.4%)
|
453 (30.6%)
|
|
Number of diagnoses
|
|
|
|
0,216
|
None
|
1107 (51.06)
|
337 (48.9%)
|
770 (52.1%)
|
|
1
|
595 (27.44)
|
195 (28.3%)
|
400 (27.0%)
|
|
2
|
252 (11.62)
|
77 (11.2%)
|
175 (11.8%)
|
|
3 or more
|
214 (9.87)
|
80 (11.6%)
|
134 (9.06%)
|
|
CCP
|
21 (0.97)
|
13 (1.88%)
|
8 (0.54%)
|
0.006
|
ACD
|
4 (0.18)
|
2 (0.29%)
|
2 (0.14%)
|
0.596
|
Migrants
|
32 (1.63)
|
7 (1.10%)
|
25 (1.89%)
|
0.271
|
AMG
|
|
|
|
0.105
|
1
|
709 (33.28)
|
207 (30.5%)
|
502 (34.6%)
|
|
2
|
827 (38.83)
|
272 (40.1%)
|
555 (38.2%)
|
|
3
|
487 (22.86)
|
156 (23.0%)
|
331 (22.8%)
|
|
4
|
107 (5.02)
|
43 (6.34%)
|
64 (4.41%)
|
|
COVID diagnosis (previous 6m)
|
123 (5.67)
|
78 (11.3%)
|
45 (3.04%)
|
<0.001
|
Contact COVID (previous 6m)
|
233 (10.74)
|
60 (8.68%)
|
173 (11.7%)
|
0.042
|
Cancer
|
387 (17.83)
|
143 (20.7%)
|
244 (16.5%)
|
0.020
|
Cardiopathy
|
35 (1.61)
|
15 (2.17%)
|
20 (1.35%)
|
0.220
|
DM
|
194 (8.94)
|
65 (9.41%)
|
129 (8.72%)
|
0.660
|
HTA
|
459 (21.15)
|
159 (23.0%)
|
300 (20.3%)
|
0.164
|
Kidney Failure
|
76 (3.5)
|
27 (3.91%)
|
49 (3.31%)
|
0.564
|
Obesity
|
527 (24.29)
|
173 (25.0%)
|
354 (23.9%)
|
0.615
|
Respiratory Disease
|
154 (7.1)
|
51 (7.38%)
|
103 (6.96%)
|
0.793
|
Smoking Diagnosis
|
356 (16.41)
|
105 (15.2%)
|
251 (17.0%)
|
0.328
|
Prescription Antibiotics
|
195 (8.99)
|
73 (10.6%)
|
122 (8.25%)
|
0.094
|
Prescription Antivirals
|
9 (0.41)
|
3 (0.43%)
|
6 (0.41%)
|
1.000
|
Prescription immunosuppressants
|
14 (0.65)
|
4 (0.58%)
|
10 (0.68%)
|
1.000
|
The p-value expresses the comparison between the first and second screening population. |
*The mean and standard deviation were used to describe the variable age. |
Just under half of the users had one or more diagnoses. The diagnoses detected were obesity (24.3%), cancer (17.8%), type II diabetes (8.9%), respiratory disease (7.10%), renal failure (3.5%) and heart disease (1.6%). Of the possible risk factors described, smoking (16.4%), prescription of antibiotics (8.9%), antivirals (0.4%) and immunosuppressants (0.6%) one month prior to the test were analysed (Table 1).
A total of 5.7% of the population analysed had a diagnosis of COVID in the 6 months prior to testing and 10.7% had a diagnosis of close contact COVID in the 6 months prior to testing (Table 1).
The prevalence of antibodies against COVID19 detected in the population analysed was 9.6%, with a 95% CI of 8.4–10.9%. By sex, the prevalence was similar between men and women, 9.2% and 10.1% respectively (p-value=0.525). The seroprevalence of antibodies increased with age (Figure 1) and this increase was significant in the older age group (p-value=0.008): in children under 20 years of age, the prevalence was 8.2%, in those aged 20 to 39 years 8.2%, in those aged 40 to 59 years 8.1% and in those over 59 years, the prevalence was 12.8% (Table 2). In CCP, the prevalence was 14.3% and in ACD, 25%.
Table 2
Prevalence and prevalence ratio of the variables analysed, in the total sample and in the first and second screening.
|
Total
|
PR
|
P-value
|
1st Screening
|
PR
|
P-value
|
2nd Screening
|
PR
|
P-value
|
Total sample
|
208 (9.58)
|
(8.42; 10.89)
|
|
84 (12.16)
|
(9.93; 14.80)
|
|
124 (8.38)
|
(7.01; 9.91)
|
|
Females
|
118 (9.21)
|
0.91 (0.70; 1.18)
|
0.525
|
49 (11.8)
|
0.92 (0.61; 1.38)
|
0.776
|
69 (7.99)
|
0.89 (0.64; 1.25)
|
0.576
|
Age group
|
|
|
0.008
|
|
|
0.705
|
|
|
0.003
|
Under 20
|
21 (8.23)
|
Ref
|
|
11c(11,34)
|
Ref
|
|
10 (6.33)
|
Ref
|
|
Between 20 and 39
|
33 (8.19)
|
0.99 (0.58; 1.74)
|
|
17 (13.17)
|
1.16 (0.55; 2.56)
|
|
16 (5.84)
|
0.92 (0.42; 2.10)
|
|
Between 40 and 59
|
68 (8.08)
|
0.98 (0.61; 1.64)
|
|
26 (10.48)
|
0.92 (0.47; 1.95)
|
|
42 (7.07)
|
1.12 (0.58; 2.36)
|
|
60 years of age or older
|
86 (12.83)
|
1.56 (0.99; 2.57)
|
|
30 (13.82)
|
1.22 (0.63; 2.54)
|
|
56 (12.36)
|
1.95 (1.04; 4.07)
|
|
Diagnostics
|
|
|
0.765
|
|
|
0.939
|
|
|
|
None
|
100 (9.03)
|
Ref
|
|
43 (12.76)
|
Ref
|
|
57 (7.40)
|
Ref
|
0.421
|
1
|
59 (9.91)
|
1.09 (0.79; 1.51)
|
|
24 (12.31)
|
0.96 (0.58; 1.57)
|
|
35 (8.75)
|
1.18 (0.77; 1.79)
|
|
2
|
25 (9.92)
|
1.09 (0.69; 1.67)
|
|
8 (10.39)
|
0.81 (0.35; 1.64)
|
|
17 (9.71)
|
1.31 (0.74; 2.20)
|
|
3 or more
|
24 (11.21)
|
1.24 (0.78; 1.90)
|
|
9 (11.25)
|
0.88 (0.40; 1.72)
|
|
15 (11.19)
|
1.51 (0.82; 2.59)
|
|
CCP
|
3 (14.29)
|
1.50 (0.52; 4.30)
|
0.446
|
2 (15.4)
|
1.27 (0.35; 4.63)
|
0.665
|
1 (12.5)
|
1.49 (0.24; 9.42)
|
0.504
|
ACD
|
1 (25.00)
|
2.62 (0.48; 14.35)
|
0.332
|
1 (50.0)
|
4.15 (1.02; 16.84)
|
0.228
|
0 (0.0)
|
-
|
1
|
Origin
|
|
|
0.129
|
|
|
0.605
|
|
|
0.018
|
Native
|
190 (9.85)
|
Ref
|
|
79 (12.5)
|
Ref
|
|
111 (8.55)
|
Ref
|
|
Migrant
|
6 (18.75)
|
1.90 (0.91; 3.97)
|
|
0 (0.0)
|
-
|
|
6 (24.00)
|
2.81 (1.37; 5.77)
|
|
AMG
|
|
|
0.043
|
|
|
0.435
|
|
|
0.095
|
1
|
52 (7.33)
|
Ref
|
|
19 (9.17)
|
Ref
|
|
33 (6.57)
|
Ref
|
|
2
|
84 (10.16)
|
1.38 (0.98; 1.97)
|
|
38 (13.97)
|
1.52 (0.89; 2.69)
|
|
46 (8.29)
|
1.26 (0.81; 1.98)
|
|
3
|
54 (11.09)
|
1.51 (1.03; 2.22)
|
|
20 (12.82)
|
1.39 (0.74; 2.63)
|
|
34 (10.27)
|
1.56 (0.97; 2.53)
|
|
4
|
15 (14.02)
|
1.91 (1.04; 3.31)
|
|
6 (13.95)
|
1.52 (0.55; 3.59)
|
|
9 (14.06)
|
2.14 (0.96; 4.28)
|
|
Covid Diagnostics
|
104 (84.55)
|
16.64 (13.60; 20.37)
|
<0.001
|
75 (96.15)
|
65.49 (34.19; 125.45)
|
<0.001
|
29 (64.44)
|
9.73 (7.27; 13.02)
|
<0.001
|
Contact COVID
|
32 (13.73)
|
1.51 (1.06; 2.15)
|
0.031
|
7 (11.7)
|
0.96 (0.46; 1.98)
|
1
|
25 (14.45)
|
1.91 (1.27; 2.87)
|
0.003
|
Cancer
|
39 (10.08)
|
1.06 (0.76; 1.48)
|
0.789
|
18 (12.6)
|
1.05 (0.64; 1.70)
|
0.973
|
21 (8.61)
|
1.03 (0.66; 1.62)
|
0.991
|
Cardiopathy
|
4 (11.43)
|
1.20 (0.47; 3.04)
|
0.572
|
1 (6.67)
|
0.54 (0.08; 3.65)
|
1
|
3 (15.0)
|
1.81 (0.63; 5.21)
|
0.232
|
DM
|
19 (9.79)
|
1.02 (0.65; 1.60)
|
1
|
6 (9.23)
|
0.74 (0.34; 1.63)
|
0.576
|
13 (10.08)
|
1.23 (0.71; 2.11)
|
0.575
|
HTA
|
44 (9.59)
|
1.00 (0.73; 1.37)
|
1
|
19 (11.9)
|
0.98 (0.61; 1.58)
|
1
|
25 (8.33)
|
0.99 (0.65; 1.51)
|
1
|
Kidney failure
|
9 (11.84)
|
1.25 (0.67; 2.33)
|
0.629
|
2 (7.41)
|
0.60 (0.16; 2.31)
|
0.638
|
7 (14.29)
|
1.75 (0.86; 3.54)
|
0.181
|
Obesity
|
62 (11.76)
|
1.32 (1.00; 1.75)
|
0.062
|
22 (12.7)
|
1.06 (0.67; 1.67)
|
0.899
|
40 (11.30)
|
1.51 (1.06; 2.16)
|
0.031
|
Respiratory disease
|
13 (8.44)
|
0.87 (0.51; 1.49)
|
0.72
|
4 (7.84)
|
0.63 (0.24; 1.64)
|
0.449
|
9 (8.74)
|
1.05 (0.55; 2.00)
|
1
|
Smoking
|
22 (6.18)
|
0.60 (0.39; 0.92)
|
0.022
|
14 (13.3)
|
1.12 (0.65; 1.91)
|
0.811
|
8 (3.19)
|
0.34 (0.17; 0.68)
|
0.002
|
Antibiotics
|
19 (9.74)
|
1.02 (0.65; 1.59)
|
1
|
6 (8.22)
|
0.65 (0.29; 1.44)
|
0.368
|
13 (10.66)
|
1.30 (0.76; 2.24)
|
0.438
|
Antivirals
|
2 (22.22)
|
2.33 (0.68; 7.79)
|
0.212
|
0 (0.0)
|
Ref
|
1
|
2 (33.33)
|
4.02 (1.28; 12.64)
|
0.083
|
Immunosuppressants
|
1 (7.14)
|
0.74 (0.11; 4.94)
|
1
|
1 (25.0)
|
2.07 (0.37; 11.43)
|
0.405
|
0 (0.0)
|
-
|
1
|
* They are represented by n and percentages. |
The reference category for comparison has been the No condition. |
The seroprevalence was significantly different according to the AMG morbidity index (p=0.043), with an increase from lower to higher AMG index: in AMG of 1, the prevalence was 7.3%, in AMG of 2, 10.2%, in AMG of 3, 11.1% and in AMG of 4, the prevalence was 14.0% (Table 2). The prevalence of antibodies was also higher in cases with a diagnosis of COVID and contact diagnosis of COVID (Table 2).
The seroprevalence of antibodies against COVID-19 was similar among users with or without a diagnosis of other pathologies, such as cancer, heart disease, diabetes, arterial hypertension, renal failure, obesity or respiratory disease. There was also no difference in antibody seroprevalence between users who took antibiotics, antivirals or immunosuppressants and those who did not. In contrast, users who smoked had a lower prevalence of antibodies than non-smoking users, with a PR = 0.60 (0.39, 0.92) (p-value = 0.022) (Table 2).
The study was conducted in two stages, a first one in October and a second one in December 2020, the period between 15 October and the end of December marked the second wave of COVID cases. The first screening sample was similar to the second screening sample in terms of age, percentage of women, AMG levels and total number of diagnoses. The number of CCPs tested was significantly higher in the first screening (p-value = 0.006) in which there was also a higher percentage of users who had been COVID+ in the last 6 months (p-value <0,001) (Table 1).
As for individual diagnoses, only the percentage of cancer showed differences, with a higher percentage in the first sample (20.7% vs. 16.5%, p-value = 0.020) (Table 1).
The seroprevalence of antibodies to COVID-19 was significantly higher in the October analysis 12.16% CI95: 9.93;14.80, than in the December analysis 8.38% CI95: 7.01;9.91 (Table 2).
In the October screening, no statistically significant associations were observed between the factors analysed and the detection of COVID-19 antibodies, except for the positive relationship between those who had undergone COVID-19 six months earlier and the positive antibody result. In contrast, in the second screening, a significant association was detected between antibody prevalence and categorized age, origin, obesity, smoking and having been COVID-19 positive or close contact in the last 6 months (Table 2).