Background: In December 2019 in Wuhan China the new coronavirus outbreak emerged and quickly spread in all parts of the world resulting to more than 500,000,000 infection cases and around 6,200,000 deaths. The global incidence of the infection is still growing as well as number of deaths. COVID-19 is a new virus, therefore not much is known about the immune response of infected organism, which is crucial not only for vaccination policy development, but also for identification of public health strategies. Aim: Current research aims to describe COVID-19 IgG levels depending on symptoms, antibiotic and antiviral medications intake history, existing chronic condition and smoking status during March-December of 2020 in Armenia. Furthermore, the study aims to help elucidate the fraction of asymptomatic or presymptomatic/sub- clinical infections in the population and understand the main risk factors for infection complication. Methodology: The cross-sectional study with convenience sampling of individuals who turned to “EcoSense” laboratories to be tested for COVID-19 IgG were examined. The NovaTec SARS-CoC-2 (COVID-19) IgG COVG940 96 Determinations ELISA test kits were used. The questionnaire was filled regarding the COVID-19 status, symptoms, exposure history, disease history, pre-existing chronic conditions, medication and vaccination history. The descriptive as well as multivariate analysis was performed. Results: Overall 1573 testing was performed 837 of subjects agreed to participate in the interview. 24.1% of participants had laboratory confirmed COVID-19 but by the time of interview were already recovered. 212 (25.3%) participants had positive IgG levels, among 126 (15.1%) participants IgG levels were in the grey zone. Out of PCR confirmed cases only 58.7% had positive IgG levels and 3.9% IgG level was in the grey zone. Headache was the most common symptom among participants (37.2% among all participants and 53.1% among participants who previously had positive COVID-19 PCR test). The second most common symptom was anosmia (23.7% among all participants and 48.9% among participants who previously had positive COVID-19 PCR test). 5.4% of participants mentioned previous hospitalization due to COVID-19, 71 (8.5%) mentioned being diagnosed with pneumonia and 24 (2.9%) participants mentioned being admitted to ICU, 20 (2.4%) mentioned receiving oxygen therapy and 4 (0.5%) of the participants mentioned receiving an artificial ventilation of lungs. There was a weak correlation between symptom sum score and IgG titers. The Correlation coefficient was 0.273, p < 0.05, R 2 = 0.075. The linear regression analysis was also performed. The obtained results indicate that the number of symptoms patients have is a significant predictor for IgG level F(1, 711) = 57.45, P < 0.01, R 2 = 0.075. Conclusions: Our study reviled that around half of PCR confirmed COVID-19 patients do not have positive titer for IgG, most importantly the number of symptoms is a weak predictor for IgG levels, which contradicts the existing misassumption regarding severity of clinical manifestation of COVID-19 and post-infection immunity.
A novel Coronavirus, severe acute respiratory syndrome (SARS-CoV-2) has emerged in December 2019 in Wuhan China and caused a human pandemic resulting to more than 500,000,000 infection cases and around 6,200,000 deaths [
Current research aims to determine the IgG antibody levels following COVID- 19 infection. Nevertheless, the study will help to elucidate the fraction of asymptomatic or pre-symptomatic/subclinical infections in the population and understand the main risk factors for infection complication.
Research also aims to explore the difference of antibody titers among symptomatic vs. asymptomatic patients. The difference of antibody titers will also be explored from the prospective of antiviral drugs, antibiotics taken and vaccination anamnesis. The multivariate analysis will be conducted.
One of the research questions will be related with smoking status and coronavirus infection complications.
The study will also explore how the pre-existing chronic conditions are related to the infection complications.
Current research aims to describe COVID-19 infection among large sample of population. This study will also serve for the baseline information to further evaluate the difference of the symptoms during different periods of pandemics caused by various mutated strains.
Starting from very early stages of coronavirus pandemics various assumptions existed regarding natural immunity [
The study was approved by Ethics Board of “EcoSense” diagnostic medical center. All participants were given an informed consent.
The cross-sectional study was performed with convenience sampling. The exclusion criteria was having COVID-19 positive test during last 14 days prior participation in the study. 1573 individuals who turned to any of the branches of “EcoSense” laboratories were offered to participate in the study by taking a blood sample and filling the interviewer administered questionnaire regarding the COVID-19 status, symptoms, exposure history, disease history, pre-existing chronic conditions, medication and the vaccination history (see Appendix). 837 agreed to participate in the study. The total duration of the study was 12 months. On the time of testing all the participants were recovered in less than 3 months period.
The high-quality reagents manufactured in Germany (NovaTec) were used. The testing was performed in ‘’EcoSense’’ diagnostic center in capital of Armenia: Yerevan. As the center also has 7 functioning branches in regions of Armenia as well as in the Republic of Artsakh the laboratory services are accessible not only for participants living in Yerevan, therefore it was possible to achieve a good geographic representativeness.
EcoSense is the only diagnostic center in Armenia having ISO 9001:2015 international certificate issued by TÜVRheinland (ID 9108658675) in 2020.
Blood samples were centrifuged and sent to the central laboratory in Yerevan. The ELISA equipment (Thermo Scientific Multiskan FC) has been used for analyzing. The data has been entered to SPSS and analyzed. The following ELISA test kits have been used NovaTec SARS-CoC-2 (COVID-19) IgG COVG940 96 Determinations. Descriptive, correlation as well as linear regression analysis was used to answer the research questions. Data was entered and analyzed using statistical package SPSS 22.
Overall 1573 testing was performed 837 of subjects agreed to participate in the interview. 57.5% were females. 24.1% of participants had laboratory confirmed COVID-19 but by the time of interview were already recovered. 212 (25.3%) participants had positive IgG levels, among 126 (15.1%) participants IgG levels were in the grey zone. Out of PCR confirmed cases only 58.7% had positive IgG levels and 3.9% IgG level was in the grey zone.
4.9% of participants was previously symptomatic, however were not tested to confirm COVID-19 infection. Out of all previously symptomatic but non-con- firmed cases 31.5% had positive IgG levels.
10.5% of patients had some level of symptoms persistence during participation in the study. 13.7% of participants with positive IgG titer did not have any symptoms, 3.8% had only loss of sense of taste and anosmia.
Headache was the most common symptom among participants (37.2% among all participants and 53.1% among participants who previously had positive CO- VID-19 PCR test). Second most common symptom was anosmia (23.7% among all participants and 48.9% among participants who previously had positive CO- VID-19 PCR test).
Symptoms | % From all participants n = 837 | % From previously PCR+ participants n = 143 | % From all IgG positive participants n = 212 |
---|---|---|---|
Fever more than 38˚C | 25.9 | 44.8 | 40.1 |
Subjective fever feeling | 33.8 | 51.0 | 41.9 |
Chills | 23.5 | 35.7 | 33.9 |
Myalgia | 35.8 | 51.7 | 46.7 |
Rhinorrhea | 20.6 | 25.2 | 23.6 |
Sore throat | 32.1 | 35.6 | 30.7 |
Cough (newly started or worsening of chronic cough) | 28.9 | 40.6 | 31.6 |
Shortness of breath | 18.5 | 32.2 | 26.4 |
Nausea/vomiting | 15.2 | 25.2 | 22.2 |
Headache | 37.2 | 53.1 | 42.5 |
Abdominal pain | 14.3 | 20.9 | 18.4 |
Diarrhea | 19.6 | 34.9 | 28.3 |
Loss of sense of smell or taste | 23.7 | 48.9 | 44.3 |
Conjunctivitis | 4.7 | 4.9 | 3.8 |
Other | 4.1 | 6.3 | 0.5 |
5.4% of participants mentioned previous hospitalization due to COVID-19, 71 (8.5%) mentioned being diagnosed with pneumonia and 24 (2.9%) participants mentioned being admitted to ICU 20 mentioned receiving oxygen therapy and 4 (0.5%) of the participants mentioned receiving an artificial ventilation of lungs. 26 of the participants mentioned being pregnant gestation age varied from 6 - 35 weeks.
19.4% of participants mentioned being a smoker. 6.8% of them previously had positive COVID-19 PCR test. However, among all smokers only 14.2% had positive IgG, 13.0% were in the grey zone.
41.1% of patients mentioned taking antibiotics during last one year period and 30.5% mentioned history of taking antiviral medication.
The symptoms quantity was summed up to a symptom score. In order to identify the association between symptoms quantity and IgG levels the correlation and linear regression analysis were performed. There was a weak positive correlation between symptom sum score and IgG titers. The Correlation coefficient was 0.273, p < 0.05, R2 = 0.075.
The overall regression model was significant F(1, 711) = 57.45, P < 0.01, R2 = 0.075. The obtained results for the linear regression analysis indicate that the number of symptoms patients have is a significant predictor for IgG level.
Model Summary | ||||
---|---|---|---|---|
Model | R* | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | 0.273a | 0.075 | 0.073 | 3.369 |
ANOVAa | ||||||
---|---|---|---|---|---|---|
Model | Sum of Squares | Df* | Mean Square | F** | Sig. | |
1 | Regression | 652.125 | 1 | 652.125 | 57.450 | 0.000b |
Residual | 8070.638 | 711 | 11.351 | |||
Total | 8722.763 | 712 |
Coefficientsa | ||||||
---|---|---|---|---|---|---|
Model | Unstandardized Coefficients | Standardized Coefficients | T | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | 2.221 | 0.198 | 11.248 | 0.000 | |
IgG1 | 0.115 | 0.015 | 0.273 | 7.580 | 0.000 |
aPredictors: (Constant), IgG1. *R is a correlation between predicted values and observed values.
aDependent Variable: symptomsum; bPredictors: (Constant), IgG1; *Df is Degree of Freedom; **F test of a null hypothesis.
aDependent Variable: symptomsum.
Unfortunately, there are no other seroprevalence studies to our knowledge conducted in Armenia, so we could compare our results. However, it was obvious that the numbers of COVID-19 cases are much greater than it was reported, as 31.5% had positive titer without previously having a positive COVID-19 test. This finding is comparable to the studies done in other countries [
The prevalence of symptom persistence is relevant to the existing studies [
According to our findings the most common symptom among participants was headache which contradicts other studies where the most common reported symptom was fever [
Current study has several limitations. The main limitation is sampling by convenience design, as our sample is consisting of individuals who turned to examination voluntarily, so it may consist of individuals who have previously had symptoms and are concerned about COVID-19. There is an overrepresentation of female participants in our study. Our study also cannot be quite generalized for vulnerable social groups of population, as the data was collected from the tests performed for payment. Even though the samples were arriving from different parts of Armenia, however there is no even distribution from each region as the majority of participants are from Yerevan. Therefore, the study results cannot be generalized to entire Armenia. Another important limitation is the fact that the evaluation of symptoms is based on self-reported data, which may involve some recall bias.
Scaling up the population wide serological testing in Armenia can help with evidence based public health decision making [
For further research we recommend to perform a follow up study and to assess antibody kinetics over time and the incidence of reinfection with COVID-19 in the year of 2021 in cases of non-vaccinated as well as vaccinated individuals. The effects of smoking status, as well as different chronic conditions on COVID- 19 shall be studied further.
The authors declare no conflicts of interest regarding the publication of this paper.
Nazaryan, I., Mnatsakanyan, S. and Pepanyan, N. (2022) Serological Investigation of COVID-19 Antibodies in Armenia. Advances in Infectious Diseases, 12, 337-346. https://doi.org/10.4236/aid.2022.122027