María M Escribese1, Estanislao Nistal-Villan1,2, Paloma Fernandez1, Pilar Rico1, Isabel A Martin-Antoniano1, Alicia de la Cuerda3,4, Tomas Chivato1, Domingo Barber1. 1. Department of Basic Medical Sciences, Faculty of Medicine, Institute of Applied Molecular Medicine, Universidad San Pablo CEU, CEU Universities, Madrid, Spain. 2. Microbiology Section, Departamento Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo CEU, CEU Universities, Boadilla del Monte, Spain. 3. HM Hospitales, Instituto de investigación Sanitaria HM Hospitales, Hospital Universitario HM Montepríncipe, Madrid, Spain. 4. Fundación de Investigación HM Hospitales, CEU Universities, Universidad San Pablo-CEU, Madrid, Spain.
Coronavirusescoronavirus disease 2019Hospital Madrid MonteprincipeImmunoglobulin GImmunoglobulin MReverse transcription‐polymerase chain reactionsevere acute respiratory syndrome coronavirus 2Virus‐like particlesTo the Editor,Coronaviruses (CoV) are large, enveloped, positive‐strand RNA viruses and until the first outbreak of SARS in 2002 had long been considered pathogens with low hospitalization incidence for healthy people. SARS‐CoV‐2 is a novel pathogenic CoV responsible for a new type of pneumonia. Initial reports placed the initial outbreak in Wuhan (China) in December 2019, and it has since spread and caused hundreds of thousands of deaths worldwide.
The virus pandemic has spread extremely fast, and it is reasonable to suggest that further outbreaks may appear along the next years before effective treatments or vaccines are available in the market.
Thus, in the meantime, only by achieving a better diagnostic monitoring and by understanding the interactions between the virus and host immune response will we be able to rationally manage future outbreaks.The immune response to SARS‐CoV‐2 is currently under study and needs to be better characterized. However, it has been previously reported that viral infection involves activation of CD8 + cytotoxic cells, antibody‐producing B cells, and innate immune response that in some patients triggers a so‐called "cytokine storm".
Moreover, whether immune responses to SARS‐CoV‐2 generate long‐term memory or whether immunized patients have long‐term sterilizing immunity is still unknown.Spain has been devastated by the COVID‐19 pandemic with more than 280 000 confirmed cases, from which more than 67 000 were in Madrid, causing a huge personal, health system, and economic burden.
In fact, more than 20% of infected subjects were healthcare workers.We aimed to generate an immune response map to SARS‐CoV‐2 in a very specific population of a Medical School were both healthcare workers and nonhealthcare workers cohabit, and elucidate the main risk factors that can be associated with COVID‐19 diagnosis in each population. With that purpose, we analyzed a population of 100 people mainly ascribed to the Medical School of San Pablo CEU University and one of its University Hospitals, HM Monteprincipe (HMM), where students perform the last 4 years of the medical degree. The population of study included 50 medical doctors from HMM that were exposed to viral loads on a daily basis (healthcare workers) and 50 researchers and teachers from the medical school that can be considered as a representative sample of the general population (nonhealthcare workers). In this study, we used the so‐called “fast” IgM/IgG immunological commercial kits (REAL 2019‐NCOV RAPID TEST CASSETTE) to analyze the population immunity.Healthcare workers were recruited and classified in two subgroups depending on whether they were diagnosed or not for COVID‐19 by RT‐PCR (Appendix S1).Table 1 shows that healthcare workers with a confirmed diagnosis by RT‐PCR display a significant association with symptoms such as fever, cough, fatigue, dysgeusia, and anosmia. Moreover, diarrhea, even if it does not show a significant association, presents an OR of 2.65, suggesting this symptom as a novel risk factor associated with COVID‐19 diagnosis. Moreover, the immunological tests demonstrate that almost 96% of the subjects diagnosed by RT‐PCR were positive for IgG with an OR of 42.2. Thus, it seems there is a clear association between symptoms, RT‐PCR results, and the positive results for IgG test.
Table 1
Summary table of healthcare workers according to RT‐PCR diagnosis
NO RT‐PCR N = 26
RT‐PCR (+) N = 24
OR
P ratio
P overall
Field: Hospital
26 (100%)
24 (100%)
Ref.
Ref.
.
Age
45.4 (8.84)
44.6 (10.1)
0.99 [0.93;1.05]
.773
.780
Gender
Female
21 (80.8%)
14 (58.3%)
Ref.
Ref.
.155
Male
5 (19.2%)
10 (41.7%)
2.90 [0.83;11.4]
.097
Fever
NO
24 (92.3%)
6 (25.0%)
Ref.
Ref.
<.001
Yes
2 (7.69%)
18 (75.0%)
30.9 [6.59;255]
<.001
Cough
NO
20 (76.9%)
7 (29.2%)
Ref.
Ref.
.002
Yes
6 (23.1%)
17 (70.8%)
7.59 [2.22;29.7]
.001
Fatigue
NO
21 (80.8%)
4 (16.7%)
Ref.
Ref.
<.001
Yes
5 (19.2%)
20 (83.3%)
18.8 [4.80;94.1]
<.001
Pneumonia
NO
25 (96.2%)
17 (70.8%)
Ref.
Ref.
.021
Yes
1 (3.85%)
7 (29.2%)
8.91 [1.36;242]
.020
Headache
NO
20 (76.9%)
11 (45.8%)
Ref.
Ref.
.049
Yes
6 (23.1%)
13 (54.2%)
3.78 [1.14;13.8]
.029
Diarrhea
NO
22 (84.6%)
16 (66.7%)
Ref.
Ref.
.249
Yes
4 (15.4%)
8 (33.3%)
2.65 [0.69;11.9]
.158
Dysgeusia
NO
22 (84.6%)
9 (37.5%)
Ref.
Ref.
.002
Yes
4 (15.4%)
15 (62.5%)
8.52 [2.35;38.1]
.001
Anosmia
NO
21 (80.8%)
9 (37.5%)
Ref.
Ref.
.005
Yes
5 (19.2%)
15 (62.5%)
6.59 [1.91;26.4]
.002
IgG
Neg
18 (69.2%)
1 (4.17%)
Ref.
Ref.
<.001
Pos
8 (30.8%)
23 (95.8%)
42.2 [6.95;1126]
<.001
Summary table of healthcare workers according to RT‐PCR diagnosisMoreover, in the nonhealthcare workers population, no RT‐PCR was performed for diagnosis and only 7 out of 50 subjects (14%) in the group were positive for IgG. Interestingly, these results agree with those recently published by the Spanish Ministry of Health regarding a seroprevalence study in Spanish population (n = 60 000 citizens) with different range of age, region, economic income, etc The epidemiological study shows a seroprevalence of 11% in Madrid.Furthermore, Table 2 shows that in this group, positive IgG subjects present a significant association with fatigue, dysgeusia, and anosmia. Surprisingly, no association was found with symptoms such as fever or cough.
Table 2
Summary table of nonhealthcare workers according to IgG Test
Neg
N = 43
Pos
N = 7
OR
P ratio
P overall
Field: University
43 (100%)
7 (100%)
Ref.
Ref.
.
Age
42.1 (13.4)
43.1 (10.2)
1.01 [0.95;1.07]
.837
.811
Gender
Female
24 (55.8%)
5 (71.4%)
Ref.
Ref.
.684
Male
19 (44.2%)
2 (28.6%)
0.53 [0.06;2.90]
.481
Fever
NO
41 (95.3%)
5 (71.4%)
Ref.
Ref.
.089
Yes
2 (4.65%)
2 (28.6%)
7.61 [0.67;87.4]
.096
Cough
NO
39 (90.7%)
5 (71.4%)
Ref.
Ref.
.192
Yes
4 (9.30%)
2 (28.6%)
3.83 [0.40;27.6]
.222
Fatigue
NO
39 (90.7%)
4 (57.1%)
Ref.
Ref.
.048
Yes
4 (9.30%)
3 (42.9%)
6.86 [0.98;47.2]
.052
Pneumonia: NO
43 (100%)
7 (100%)
Ref.
Ref.
Headache
NO
40 (93.0%)
6 (85.7%)
Ref.
Ref.
.464
Yes
3 (6.98%)
1 (14.3%)
2.33 [0.07;24.2]
.553
Diarrhea
NO
39 (90.7%)
6 (85.7%)
Ref.
Ref.
.546
Yes
4 (9.30%)
1 (14.3%)
1.74 [0.06;15.6]
.684
Dysgeusia
NO
42 (97.7%)
5 (71.4%)
Ref.
Ref.
.048
Yes
1 (2.33%)
2 (28.6%)
14.3 [1.00;502]
.050
Anosmia
NO
43 (100%)
4 (57.1%)
Ref.
Ref.
.002
Yes
0 (0.00%)
3 (42.9%)
N/A
.
Summary table of nonhealthcare workers according to IgG TestNegN = 43PosN = 7A possible explanation for these results might be that healthcare workers were exposed to higher viral loads and during more time along the peak of the pandemic, while nonhealthcare workers were confined at home. In fact, almost all of them presented the above‐mentioned symptoms during the first 2 weeks of lockdown. IgM results were not conclusive in either group.This pilot study is the first step in the elucidation of a “population immunological map” in our special community in the Medical School with healthcare and nonhealthcare workers. The results demonstrate that the prevalence of COVID‐19 is higher in healthcare workers, as expected. Additionally, this pilot study provides the knowledge and the positive controls (healthcare workers with positive RT‐PCR) for the development of future methodological strategies aiming to set up new immunological tests for herd immunity follow‐up (ELISA, neutralization assays, etc). This will be helpful if we take into account the shortage of commercial kits for SARS‐CoV‐2 immunological tests during the pandemic, and the limitations of these tests in terms of specificity and sensitivity.
,Additionally, the results obtained from this rationale together with the information related to previous pathologies and risk factors will allow the design of personalized strategies of reincorporation into academic activities in the future. This will significantly reduce the human and economic burden of future COVID‐19 infection waves in our community. The proposed strategy can be easily implemented by several research laboratories and might help in better activity plans in other locations to be ready for future outbreaks.
CONFLICTS OF INTEREST
The authors declare that they do not have any conflict of interest in relation to this study.
Funding information
This work was supported by ISCIII (Project number, PI19/00044 and PI18/01467) and co‐funded by European Regional Development Fund “Investing in your future” for the thematic network and co‐operative research centers ARADyAL RD16/0006/0015.Appendix S1Click here for additional data file.
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