Abbreviations
- CoV
Coronaviruses
- COVID19
coronavirus disease 2019
- HMM
Hospital Madrid Monteprincipe
- IgG
Immunoglobulin G
- IgM
Immunoglobulin M
- RT‐PCR
Reverse transcription‐polymerase chain reaction
- SARS‐CoV‐2
severe acute respiratory syndrome coronavirus 2
- VLP
Virus‐like particles
To 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. 1 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. 2 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". 3 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. 4 In fact, more than 20% of infected subjects were healthcare workers. 4
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 | |
Moreover, 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 | . | |
A 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. 5 , 6
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.
Supporting information
Appendix S1
ACKNOWLEDGMENTS
We would like to thank Francisco Rodriguez, PhD, Ramses Reina, PhD and Luis Martinez Gil, PhD for kindly providing essential molecular tools (full length Spike protein and VLP reporters for neutralization assay and VLPs for ELISA) to perform the planned assays. We acknowledge the collaboration of all the participants in the study as well as nurses in the Oncology department at HMM. We would like to thank Tomás Clive Barker Tejeda for his help revising the manuscript. Dr Escribese has nothing to disclose. Dr Nistal Villan has nothing to disclose. Dr Fernandez Martinez has nothing to disclose Dr Rico has nothing to disclose. Dr Martín Antoniano has nothing to disclose. Dr de la Cuerda has nothing to disclose. Dr Chivato has nothing to disclose.Dr Barber has nothing to disclose.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Appendix S1