Published online Mar 25, 2025. doi: 10.5501/wjv.v14.i1.100338
Revised: September 30, 2024
Accepted: November 1, 2024
Published online: March 25, 2025
Processing time: 99 Days and 6 Hours
At the end of December 2019, the world faced severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which led to the outbreak of coronavirus disease 2019 (COVID-19), associated with respiratory issues. This virus has shown significant challenges, especially for senior citizens, patients with other underlying illnesses, or those with a sedentary lifestyle. Serological tests conducted early on have helped identify how the virus is transmitted and how to curb its spread. The study hypothesis was that the rapid serological test for SARS-CoV-2 antibodies could indicate the immunoreactive profile during the COVID-19 pandemic in a university population.
To conduct active surveillance for serological expression of anti-SARS-CoV-2 antibodies in individuals within a university setting during the COVID-19 pandemic.
This sectional study by convenience sampling was conducted in a large university in Niteroi-RJ, Brazil, from March 2021 to July 2021. The study population consisted of students, faculty, and administrative staff employed by the university. A total of 3433 faculty members, 60703 students, and 3812 administrative staff were invited to participate. Data were gathered through rapid serological tests to detect immunoglobulin (Ig) M and IgG against SARS-CoV-2. The χ² or Fisher's exact test was used to conduct statistical analysis. A 0.20 significance level was adopted for variable selection in a multiple logistic regression model to evaluate associations.
A total of 1648 individuals were enrolled in the study. The proportion of COVID-19 positivity was 164/1648 (9.8%). The adjusted logistic model indicate a positive association between the expression of IgM or IgG and age [odds ratio (OR) = 1.16, 95%CI: 1.02-1.31] (P < 0.0024), individuals who had been in contact with a COVID-19-positive case (OR = 3.49, 95%CI: 2.34-5.37) (P < 0.001), those who had received the COVID-19 vaccine (OR = 2.33, 95%CI: 1.61-3.35) (P < 0.001) and social isolation (OR = 0.59, 95%CI: 0.41-0.84) (P < 0.004). The likelihood of showing a positive result increased by 16% with every ten-year increment. Conversely, adherence to social distancing measures decreased the likelihood by 41%.
These findings evidenced that the population became more exposed to the virus as individuals discontinued social distancing practices, thereby increasing the risk of infection for themselves.
Core Tip: This study highlights the significance of serological surveillance in a university population during the coronavirus disease 2019 (COVID-19) pandemic. The findings show that age, contact with COVID-19-positive individuals, and vaccination status are positively associated with the manifestation of severe acute respiratory syndrome-coronavirus 2 antibodies. Additionally, adherence to social distancing measures significantly reduces the likelihood of infection. The prevalence of infection increased with relaxed social distancing practices, emphasizing the continued importance of preventive measures in controlling viral transmission.
- Citation: Pinheiro MG, Alves GGO, Conde MER, Costa SL, Sant’Anna RCS, Antunes IMF, Carneiro MC, Ronzei FS, Scaffo JC, Pinheiro FR, Andre LS, Povoa HC, Baltar VT, Giordani F, Hemerly ES, Alexandre GC, de Paula KC, Watanabe M, Nóbrega ACLD, Lobato JCP, Aguiar-Alves F. Serological surveillance for SARS-CoV-2 antibodies among students, faculty and staff within a large university system during the pandemic. World J Virol 2025; 14(1): 100338
- URL: https://www.wjgnet.com/2220-3249/full/v14/i1/100338.htm
- DOI: https://dx.doi.org/10.5501/wjv.v14.i1.100338
In late 2019, the global landscape was disrupted by the emergence of a novel coronavirus-induced acute respiratory syndrome known as coronavirus disease 2019 (COVID-19), caused by a newly identified severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). Coronaviruses, belonging to the Coronaviridae family, can cause respiratory infections in various mammals and avian species[1]. In recent years, they have acquired the ability to adapt to humans via zoonotic transmission in a mechanism analogous to the one observed in the Zika virus outbreak[2].
The virus was highly contagious and was transmitted human-to-human via respiratory droplets expelled by infected individuals, which led to respiratory difficulties, particularly impacting individuals with pre-existing conditions, such as chronic obstructive pulmonary disease (COPD), asthma, cystic fibrosis, and lung cancer, including mesothelioma[3-5]. It also severely affected individuals over 60 and those with a sedentary lifestyle[6].
Many studies have established a connection between adipose and remote tissue inflammation among overweight and obese individuals[7]. Severe cases of coronavirus disease would dwell in the inflammation of the lungs. Therefore, a body naturally more prone to inflammation will experience the consequences of viral attacks on pulmonary alveoli more intensely[8].
Although significant advances in understanding the virus molecular and pathogenic characteristics remain limited, several vaccines have been developed in record time[9]. The first variant emerged in the population in February 2020 and was more infectious; after that, more variants were identified[10]. The evolution of SARS-CoV-2 is related to a virus changing behavior over pandemic stages[11].
Diagnostic strategies were used to detect viral infections, including immunoassays based on human anti-SARS-CoV-2 antigens or antibodies and even serological methods[12].
The production and release of specific immunoglobulin (Ig) M antibodies in the bloodstream start a few days after exposure to SARS-CoV-2. IgG antibodies become detectable 7-10 days after infection and can persist in the circulation for up to 12 weeks post-infection[13]. However, in specific individuals, traces of antibodies may still be detected several days after the initial infection. These antibodies are identified in the patient's blood and specifically target the spike glycoprotein[14].
Serology testing at the pandemic onset could help us understand SARS-CoV-2 distribution and infection patterns. Furthermore, rapid diagnostic methodologies in population testing can potentially mitigate disease progression[6,15]. Positive IgG results could also correlate with age and profession, with an understanding that healthcare workers were the most likely to be exposed and develop infection[16].
A significant challenge in accurately collecting data on infected individuals is regarding those who recently displayed symptoms and showed positive results in rapid serological tests. If these people are COVID-19-negative, their absence could unnecessarily decrease the workforce and disrupt the return to normal activities. However, if employees continue their activities while unknowingly COVID-19 positive, they may transmit the virus to other professionals, thereby increasing the disease’s spread[17].
This study aimed to conduct active surveillance for serological expression of anti-SARS-CoV-2 antibodies in individuals within a university setting during the COVID-19 pandemic.
This sectional study comprised active surveillance for anti-SARS-CoV-2 antibodies by convenience sampling and was conducted at several Fluminense Federal University campuses (Niteroi, Campos dos Goytacazes, Macae, Nova Friburgo, Rio das Ostras, Santo Antonio de Padua, and Volta Redonda) from March 2021 to July 2021.
The study population consisted of students, faculty, and administrative staff employed by the Fluminense Federal University. Each participant provided a blood sample from their fingertip pulp and was invited to complete a survey regarding potential associated factors associated with SARS-CoV-2 infection.
All 3433 faculty members, 60703 students (distance education, sequential, and in-person), and 3812 administrative staff were invited to participate [data available at (https://app.uff.br/transparencia/), accessed on 02/24/2021]. The study included students, faculty, and administrative staff with active enrollment during data collection. There were no exclusion criteria.
The tests were performed per the manufacturer’s guidelines (FIOCRUZ-Brazil)[18-20]. A single drop of blood from the individual’s fingertip pulp was collected using a plastic capillary tube and used for an assay on a test cartridge.
A positive test result for COVID-19 was defined as a positive test result for the presence of IgG or IgM antibodies. The following variables were evaluated through a questionnaire: (1) Gender (male/female); (2) Age (adolescents-under 20 years/adults-20-59 years/older adults-60 years and over); (3) Affiliation (student/faculty/administrative staff); (4) Smoking (yes/no/used to smoke); (5) COVID-19 vaccination (no/yes); (6) Adherence to distancing measures (no/yes); (7) Contact with a positive case (no/yes/don’t know); (8) Having a healthcare professional in the family (no/yes); (9) Symptoms (no/yes); (10) Whether symptoms led to missing a day of work (no/yes); (11) Need for medical care (no/yes); and (12) Need for hospitalization (no/yes), comorbidities (no/yes) for diabetes, Alzheimer's disease, hypertension, asthma, human immunodeficiency virus/acquired immunodeficiency syndrome, cancer, depression, stroke, Parkinson’s, and COPD. Data collection was performed by trained students.
Data was described by calculating the relative frequencies of COVID-19 positive results in every qualitative variable grouping. The χ² or Fisher’s exact test was used to verify further the observed associations between the qualitative variables and positive results[21]. A 0.20 significance level was adopted for variable selection in a multiple logistic regression model to evaluate associations between sociodemographic, behavioral, and clinical factors and positive COVID-19 results[22]. A 0.05 significance level was utilized in the multiple models. A diagnostics analysis for the model was performed through the standard deviation of residuals, influential points (Cook's distance), and leverage. All statistical analyses were performed through R4.2.1.
All participants provided informed consent. This study was approved by the Research Ethics Committee (No. 43947221.6.0000.5243) and has been conducted under the code of Ethics of the World Medical Association.
A total of 1648 individuals were enrolled in the study. Most were students (763/1545, 49.4%), adults (1499/1648, 91%), Caucasian (710/1648, 43.1%), and female (962/1648, 58.4%). The proportion of COVID-19 positivity was 164/1648 (9.8%). A total of 1114/1601 (69%) of the studied population adhered to social distancing measures, and 884/1644 (53.8%) reported contact with a positive case, 1203/1648 (73%) individuals had symptoms, and 27/1648 (1.6%) required hospitalization. Only 374 individuals (23%) had been vaccinated, and 435 out of 1648 (26.4%) had some chronic disease (Table 1).
| Characteristics | Total | Coronavirus disease 2019 | P value1 | |
| No (n = 1484) | Yes (n = 164) | |||
| Tie to the university | 1545 | 0.3 | ||
| Students | 763 (49.4) | 695 (91) | 68 (8.9) | |
| Professors | 438 (28.3) | 391 (89) | 47 (11) | |
| Technical employees | 344 (22.3) | 303 (88) | 41 (12) | |
| Gender | 1648 | > 0.9 | ||
| Female | 962 (58.4) | 867 (90) | 95 (9.9) | |
| Male | 686 (41.6) | 617 (90) | 69 (10) | |
| Age | 1648 | 0.015 | ||
| Adolescents (younger than 20 years of age) | 48 (2.9) | 44 (92) | 4 (8.3) | |
| Adults (20–59 years of age) | 1499 (91) | 1358 (91) | 141 (9.4) | |
| Older adults (60 years of age or more) | 101 (6.1) | 82 (81) | 19 (19) | |
| Ethnicity | 1648 | 0.4 | ||
| Asian | 12 (0.7) | 12 (100) | 0 (0) | |
| Caucasian | 710 (43.1) | 646 (91) | 64 (9.0) | |
| Mixed race | 273 (16.6) | 242 (89) | 31 (11) | |
| Afro-Brazilian | 144 (8.7) | 133 (92) | 11 (7.6) | |
| Non-declared | 509 (30.9) | 451 (89) | 58 (11) | |
| Has a family member in healthcare | 1642 | 0.003 | ||
| No | 1211 (73.7) | 1106 (91.3) | 105 (8.7) | |
| Yes | 431 (26.3) | 372 (86) | 59 (14) | |
| Adhered to social distancing measures | 1601 | < 0.001 | ||
| No | 487 (30.4) | 419 (86) | 68 (14) | |
| Yes | 1114 (69.6) | 1021 (91.7) | 93 (8.3) | |
| Was in contact with a positive result patient | 1644 | < 0.001 | ||
| No | 700 (42.6) | 667 (95.3) | 33 (4.7) | |
| Does not know | 60 (3.6) | 57 (95) | 3 (5) | |
| Yes | 884 (53.8) | 756 (86) | 128 (14) | |
| Presented symptoms | 1648 | |||
| Yes | 1203 (73) | 1064 (88) | 139 (12) | |
| Healthcare was needed | 1648 | < 0.001 | ||
| No | 1216 (73.8) | 1126 (93) | 90 (7.4) | |
| Does not know | 1 (0.1) | 1 (100) | 0 (0) | |
| Yes | 431 (26.1) | 357 (83) | 74 (17) | |
| Did symptoms make one miss a day of work | 1648 | < 0.001 | ||
| No | 1410 (85.5) | 1299 (92.1) | 111 (7.9) | |
| Does not know | 1 (0.1) | 1 (100) | 0 (0) | |
| Yes | 237 (14.4) | 184 (78) | 53 (22) | |
| Was the individual hospitalized | 1648 | |||
| Yes | 27 (1.6) | 19 (70) | 8 (30) | |
| Presence of chronic disease | 1648 | 0.5 | ||
| Negative | 1213 (73.6) | 1089 (90) | 124 (10) | |
| Positive | 435 (26.4) | 395 (90.8) | 40 (9.2) | |
| Smoker | 1643 | 0.5 | ||
| Not currently | 175 (10.7) | 159 (91) | 16 (9.1) | |
| Non-smokers | 1333 (81.1) | 1202 (90) | 131 (9.8) | |
| Current smokers | 135 (8.2) | 118 (87) | 17 (13) | |
| The patient is vaccinated against severe acute respiratory syndrome-coronavirus 2 | 1605 | < 0.001 | ||
| No | 1231 (76.7) | 1135 (92.2) | 96 (7.8) | |
| Yes | 374 (23.3) | 309 (83) | 65 (17) | |
The variables associated with COVID-19 positivity included age (P = 0.015), having a family member who is a health professional (P = 0.003), frequent close contact with a confirmed COVID-19 case (P < 0.001), need for medical care (P < 0.001), severity of symptoms (P < 0.001), adherence to social distancing measures (P < 0.001), and COVID-19 vaccination status (P < 0.001).
In an adjusted logistic model (Table 2), individuals in contact with a confirmed COVID-19-positive case were more likely [odds ratio (OR) = 3.49, 95%CI: 2.34-5.37] to test positive for COVID-19 (IgM or IgG) than those who were vaccinated against COVID-19 (OR = 2.33, 95%CI: 1.61-3.35). The likelihood of a positive result increased by 16% with each ten-year age increment. On the other hand, adhering to social distancing measures decreased the likelihood by 41%.
| Characteristic | Odds ratio | 95%CI | P value |
| Gender | |||
| Female | 1 | - | |
| Male | 0.97 | 0.68-1.37 | 0.9 |
| Age (10 years) | 1.16 | 1.02-1.31 | 0.024 |
| Social distancing | |||
| No | 1 | - | |
| Yes | 0.59 | 0.41-0.84 | 0.004 |
| Case positive contact | |||
| No | 1 | - | |
| Yes | 3.49 | 2.34-5.37 | < 0.001 |
| Get vaccinated | |||
| No | 1 | - | |
| Yes | 2.33 | 1.61-3.35 | < 0.001 |
This study examined the immunoreactive profile for serological assessment of anti-SARS-CoV-2 antibodies within a university environment during the COVID-19 pandemic. The serological rapid test may reveal the presence of COVID-19 antibodies in individuals.
The COVID-19 positivity rate was 162/1648 (9.8%). A commercial rapid test detected SARS-CoV-2 antibodies in the blood, distinguishing between positive and negative results for SARS-CoV-2 specific IgM and IgG antibodies. However, this test does not confirm the presence of the virus itself, a molecular test would be required for that confirmation[23]. Throughout the study, it was impossible to ascertain whether IgG/IgM-positivity resulted from prior exposure to the virus or vaccination. Participants without symptoms who tested positive for IgM or IgG were subjected to a real-time PCR test to confirm the presence of SARS-CoV-2, following recommendations by Hoffman et al[24].
However, this test does not confirm the presence of the virus itself; a molecular test would be required for that confirmation
According to Shahbazi et al[25], individuals exposed to COVID-19-positive patients were at higher risk of acquiring the virus. Moreover, there was also an association between positive results on rapid tests and exposure to COVID-19-positive individuals, representing a risk factor for infections. Although the virus detection was not confirmed among these participants, the detection of circulating antibodies indicated this association.
Gujski et al[26] described the detection of antigens in 15 (3.5%) of the subjects in a study of 423 medical students through the rapid antigen test in Warsaw, Poland, from November 15 to December 10, 2021. In the present study, 68/763 (8.9%) undergraduate students were positive for the rapid COVID-19 antibody test. These findings could be associated with an immunological memory from previous infections or a current acute phase of COVID-19.
Notably, we observed the prevalence of negative results on antibody rapid tests among subjects who adhered to social distancing measures, accounting for 1114/1601 (69%). Sims et al[27], in a meta-analysis study, discussed distancing’s efficacy in reducing the transmission of infectious diseases, including COVID-19, as discussed across several papers.
Social distancing includes measures to limit interactions in a community that may include infected subjects who have not yet been identified and are, therefore, not isolated. Given that diseases transmitted by respiratory droplets require some physical proximity for contagion to occur, social distancing allows limiting transmission[28]. This study also observed a relationship between participants who adhered to social distancing measures with negative results for COVID-19 IgG and IgM-specific rapid test (P < 0.001).
In this study, a history of prior hospitalization was associated with COVID-19-specific IgG and IgM antibodies, suggesting exposure to infected patients or increased virus circulation within the hospital setting. Additionally, Ko et al[29] found that higher COVID-19 hospitalization rates might be associated with age and gender.
Whitaker et al[30] outlined an association between age and positive outcomes for COVID-19 IgG and IgM-specific rapid tests. This study also observed a 16% rise in the likelihood of testing positive for COVID-19 IgG and IgM-specific rapid tests with every ten-year age increase (Table 2), which can be attributed to the immune response observed in older adults, as shown by Grifoni et al[31].
The literature supports the statement that reported symptoms are associated with COVID-19 infections[32]. Although it is acknowledged that data collection methods used in this study could not definitively confirm COVID-19 infection, we observed an association between previous symptoms and positivity on COVID-19 antibody rapid tests. Although rapid test can indicate the presence of the antibodies, we could not confirm the COVID-19 infection without molecular characterization. These findings were justified because most individuals 1203/1648 (73%) who reported COVID-19-specific symptoms tested positive for detecting circulating antibodies. Although COVID-specific antibody rapid tests are no longer in use, these results still offer insights into understanding the spread of COVID-19 during that period and that symptomatic subjects play a crucial role in disease transmission.
Although specific factors indicating immune protection against SARS-CoV-2 through vaccination are not clearly outlined, there is wide consensus that elevated levels of antibodies are beneficial[33]. Therefore, our study revealed an association between participants vaccinated against SARS-CoV-2 and positivity for IgG and IgM antibodies in the COVID-19 rapid test. This result may reflect the potential immunity conferred by the vaccination.
As a limitation of this study, the proportion of positivity in the rapid test might be underestimated due to possible test errors[23]. Convenience sampling may reflect a study population more exposed to SARS-CoV-2, that had been vaccinated, or was more concerned about their immunity status, not representing the total university population. The lack of molecular characterization of clinical samples may interfere with the confirmation of rapid test results.
The immunoreactive profile observed in the rapid test was associated with prior contact with people positive for COVID-19-positive individuals, COVID-19 vaccination status, age group, and having a family member who is a healthcare professional. On the other hand, negativity on the rapid test was linked to individuals adhering to social distancing measures. This study suggests that examining the immunoreactive profile could help us understand the presence of COVID-19 antibodies in individuals and identify associated factors.
| 1. | Sharma A, Ahmad Farouk I, Lal SK. COVID-19: A Review on the Novel Coronavirus Disease Evolution, Transmission, Detection, Control and Prevention. Viruses. 2021;13:202. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 245] [Cited by in F6Publishing: 278] [Article Influence: 92.7] [Reference Citation Analysis (0)] |
| 2. | Azhar EI, El-Kafrawy SA, Farraj SA, Hassan AM, Al-Saeed MS, Hashem AM, Madani TA. Evidence for camel-to-human transmission of MERS coronavirus. N Engl J Med. 2014;370:2499-2505. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 616] [Cited by in F6Publishing: 611] [Article Influence: 61.1] [Reference Citation Analysis (0)] |
| 3. | Brackenborough K, Ellis H, Flight WG. Respiratory Viruses and Cystic Fibrosis. Semin Respir Crit Care Med. 2023;44:196-208. [PubMed] [DOI] [Cited in This Article: ] [Reference Citation Analysis (0)] |
| 4. | Çakır Edis E. Chronic Pulmonary Diseases and COVID-19. Turk Thorac J. 2020;21:345-349. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 13] [Cited by in F6Publishing: 16] [Article Influence: 4.0] [Reference Citation Analysis (0)] |
| 5. | Mangone L, Mancuso P, Bisceglia I, Giorgi Rossi P, Chellini E, Negro C, Benfatto L, Migliore E, Casotto V, Mensi C, Romanelli A, Tumino R, Grappasonni I, Cavone D, Mazzoleni G, Tallarigo F, Marinaccio A; ReNaM Working Group. The impact of COVID-19 on new mesothelioma diagnoses in Italy. Thorac Cancer. 2022;13:702-707. [PubMed] [DOI] [Cited in This Article: ] [Cited by in F6Publishing: 2] [Reference Citation Analysis (0)] |
| 6. | Castro R, Luz PM, Wakimoto MD, Veloso VG, Grinsztejn B, Perazzo H. COVID-19: a meta-analysis of diagnostic test accuracy of commercial assays registered in Brazil. Braz J Infect Dis. 2020;24:180-187. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 89] [Cited by in F6Publishing: 88] [Article Influence: 22.0] [Reference Citation Analysis (0)] |
| 7. | Kawai T, Autieri MV, Scalia R. Adipose tissue inflammation and metabolic dysfunction in obesity. Am J Physiol Cell Physiol. 2021;320:C375-C391. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 101] [Cited by in F6Publishing: 699] [Article Influence: 174.8] [Reference Citation Analysis (0)] |
| 8. | Hu B, Guo H, Zhou P, Shi ZL. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021;19:141-154. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 2083] [Cited by in F6Publishing: 2899] [Article Influence: 966.3] [Reference Citation Analysis (0)] |
| 9. | Rotondo JC, Martini F, Maritati M, Mazziotta C, Di Mauro G, Lanzillotti C, Barp N, Gallerani A, Tognon M, Contini C. SARS-CoV-2 Infection: New Molecular, Phylogenetic, and Pathogenetic Insights. Efficacy of Current Vaccines and the Potential Risk of Variants. Viruses. 2021;13:1687. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 53] [Cited by in F6Publishing: 38] [Article Influence: 12.7] [Reference Citation Analysis (0)] |
| 10. | Roederer AL, Cao Y, Denis KS, Sheehan ML, Li CJ, Lam EC, Gregory DJ, Poznansky MC, Iafrate AJ, Canaday DH, Gravenstein S, Garcia-Beltran WF, Balazs AB. Ongoing evolution of SARS-CoV-2 drives escape from mRNA vaccine-induced humoral immunity. medRxiv. 2024;. [PubMed] [DOI] [Cited in This Article: ] [Reference Citation Analysis (0)] |
| 11. | Xiao B, Wu L, Sun Q, Shu C, Hu S. Dynamic analysis of SARS-CoV-2 evolution based on different countries. Gene. 2024;916:148426. [PubMed] [DOI] [Cited in This Article: ] [Reference Citation Analysis (0)] |
| 12. | Contini C, Rotondo JC, Perna B, Guarino M, De Giorgio R. Special Issue: Advances in SARS-CoV-2 Infection. Microorganisms. 2023;11:1048. [PubMed] [DOI] [Cited in This Article: ] [Reference Citation Analysis (0)] |
| 13. | Rotondo JC, Martini F, Maritati M, Caselli E, Gallenga CE, Guarino M, De Giorgio R, Mazziotta C, Tramarin ML, Badiale G, Tognon M, Contini C. Advanced Molecular and Immunological Diagnostic Methods to Detect SARS-CoV-2 Infection. Microorganisms. 2022;10:1193. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 31] [Cited by in F6Publishing: 39] [Article Influence: 19.5] [Reference Citation Analysis (0)] |
| 14. | Pavlova IP, Nair SS, Kyprianou N, Tewari AK. The Rapid Coronavirus Antibody Test: Can We Improve Accuracy? Front Med (Lausanne). 2020;7:569. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis (0)] |
| 15. | Vena A, Berruti M, Adessi A, Blumetti P, Brignole M, Colognato R, Gaggioli G, Giacobbe DR, Bracci-Laudiero L, Magnasco L, Signori A, Taramasso L, Varelli M, Vendola N, Ball L, Robba C, Battaglini D, Brunetti I, Pelosi P, Bassetti M. Prevalence of Antibodies to SARS-CoV-2 in Italian Adults and Associated Risk Factors. J Clin Med. 2020;9:2780. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 63] [Cited by in F6Publishing: 62] [Article Influence: 15.5] [Reference Citation Analysis (0)] |
| 16. | Vimercati L, Stefanizzi P, De Maria L, Caputi A, Cavone D, Quarato M, Gesualdo L, Lopalco PL, Migliore G, Sponselli S, Graziano G, Larocca AMV, Tafuri S. Large-scale IgM and IgG SARS-CoV-2 serological screening among healthcare workers with a low infection prevalence based on nasopharyngeal swab tests in an Italian university hospital: Perspectives for public health. Environ Res. 2021;195:110793. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 24] [Article Influence: 8.0] [Reference Citation Analysis (0)] |
| 17. | Ji T, Liu Z, Wang G, Guo X, Akbar Khan S, Lai C, Chen H, Huang S, Xia S, Chen B, Jia H, Chen Y, Zhou Q. Detection of COVID-19: A review of the current literature and future perspectives. Biosens Bioelectron. 2020;166:112455. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 274] [Cited by in F6Publishing: 235] [Article Influence: 58.8] [Reference Citation Analysis (0)] |
| 18. | Castro N, Lopes T, Cassaro B, Fonseca F, Fernandes A, Teixeira S, Gazzinelli R. Fragment production of the spike protein from SARS-CoV-2 in insect cells for the development of serological diagnosis. In: International Symposium on Immunobiological. Rio de Janeiro: Bio-Manguinhos; 2021: 89. [DOI] [Cited in This Article: ] |
| 19. | Lopes T, Coelho F, Santos A, Castro N, Bagno F, Gazzinelli R, Fernandes A. Development of a rapid test for detection of anti-COVID-19 IgG and IgM antibodies. In: International Symposium on Immunobiological. Rio de Janeiro: Bio-Manguinhos; 2021: 84. [DOI] [Cited in This Article: ] |
| 20. | Stutz C, Alcantara DMC, Dos Santos CM, Torres JM, Rodrigues R, Marcon GEB, Ferreira EC, Sarti ECFB, de Oliveira TF, Mendes FML, Lemos EF, Demarchi LHF, Lichs GGC, Zardin MCSU, Gonçalves CCM, Guilhermino JF, Perdomo RT, Fernandez ZDC. Seroprevalence of antibodies against SARS-CoV-2 in the school community in Campo Grande, state of Mato Grosso do Sul, Brazil, October 2021-November 2022. Front Immunol. 2024;15:1354786. [PubMed] [DOI] [Cited in This Article: ] [Reference Citation Analysis (0)] |
| 21. | Kim HY. Statistical notes for clinical researchers: Chi-squared test and Fisher's exact test. Restor Dent Endod. 2017;42:152-155. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 438] [Cited by in F6Publishing: 655] [Article Influence: 93.6] [Reference Citation Analysis (0)] |
| 22. | Schober P, Vetter TR. Logistic Regression in Medical Research. Anesth Analg. 2021;132:365-366. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 26] [Cited by in F6Publishing: 72] [Article Influence: 24.0] [Reference Citation Analysis (0)] |
| 23. | Dinnes J, Deeks JJ, Adriano A, Berhane S, Davenport C, Dittrich S, Emperador D, Takwoingi Y, Cunningham J, Beese S, Dretzke J, Ferrante di Ruffano L, Harris IM, Price MJ, Taylor-Phillips S, Hooft L, Leeflang MM, Spijker R, Van den Bruel A; Cochrane COVID-19 Diagnostic Test Accuracy Group. Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection. Cochrane Database Syst Rev. 2020;8:CD013705. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 297] [Cited by in F6Publishing: 352] [Article Influence: 88.0] [Reference Citation Analysis (0)] |
| 24. | Hoffman T, Nissen K, Krambrich J, Rönnberg B, Akaberi D, Esmaeilzadeh M, Salaneck E, Lindahl J, Lundkvist Å. Evaluation of a COVID-19 IgM and IgG rapid test; an efficient tool for assessment of past exposure to SARS-CoV-2. Infect Ecol Epidemiol. 2020;10:1754538. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 70] [Cited by in F6Publishing: 103] [Article Influence: 25.8] [Reference Citation Analysis (0)] |
| 25. | Shahbazi R, Yasavoli-Sharahi H, Alsadi N, Ismail N, Matar C. Probiotics in Treatment of Viral Respiratory Infections and Neuroinflammatory Disorders. Molecules. 2020;25:4891. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 28] [Cited by in F6Publishing: 42] [Article Influence: 10.5] [Reference Citation Analysis (0)] |
| 26. | Gujski M, Mularczyk-Tomczewska P, Raciborski F, Samel-Kowalik P, Samoliński Ł, Olczak-Kowalczyk D, Jankowski M. Screening for SARS-CoV-2 Infection in Students at the Medical University of Warsaw, Poland Between November 15 and December 10, 2021 Using a Single Lateral Flow Test, the Panbio™ COVID-19 Ag Rapid Test. Med Sci Monit. 2022;28:e936962. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis (0)] |
| 27. | Sims S, Harris R, Hussein S, Rafferty AM, Desai A, Palmer S, Brearley S, Adams R, Rees L, Fitzpatrick JM. Social Distancing and Isolation Strategies to Prevent and Control the Transmission of COVID-19 and Other Infectious Diseases in Care Homes for Older People: An International Review. Int J Environ Res Public Health. 2022;19:3450. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 19] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis (0)] |
| 28. | Wilder-Smith A, Freedman DO. Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med. 2020;27:taaa020. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 1273] [Cited by in F6Publishing: 1097] [Article Influence: 274.3] [Reference Citation Analysis (0)] |
| 29. | Ko JY, Danielson ML, Town M, Derado G, Greenlund KJ, Kirley PD, Alden NB, Yousey-Hindes K, Anderson EJ, Ryan PA, Kim S, Lynfield R, Torres SM, Barney GR, Bennett NM, Sutton M, Talbot HK, Hill M, Hall AJ, Fry AM, Garg S, Kim L; COVID-NET Surveillance Team. Risk Factors for Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization: COVID-19-Associated Hospitalization Surveillance Network and Behavioral Risk Factor Surveillance System. Clin Infect Dis. 2021;72:e695-e703. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 113] [Cited by in F6Publishing: 218] [Article Influence: 72.7] [Reference Citation Analysis (0)] |
| 30. | Whitaker M, Davies B, Atchison C, Barclay W, Ashby D, Darzi A, Riley S, Cooke G, Donnelly CA, Chadeau-Hyam M, Elliott P, Ward H. SARS-CoV-2 rapid antibody test results and subsequent risk of hospitalisation and death in 361,801 people. Nat Commun. 2023;14:4957. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis (0)] |
| 31. | Grifoni A, Alonzi T, Alter G, Noonan DM, Landay AL, Albini A, Goletti D. Impact of aging on immunity in the context of COVID-19, HIV, and tuberculosis. Front Immunol. 2023;14:1146704. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 31] [Cited by in F6Publishing: 30] [Article Influence: 30.0] [Reference Citation Analysis (0)] |
| 32. | Subramanian A, Nirantharakumar K, Hughes S, Myles P, Williams T, Gokhale KM, Taverner T, Chandan JS, Brown K, Simms-Williams N, Shah AD, Singh M, Kidy F, Okoth K, Hotham R, Bashir N, Cockburn N, Lee SI, Turner GM, Gkoutos GV, Aiyegbusi OL, McMullan C, Denniston AK, Sapey E, Lord JM, Wraith DC, Leggett E, Iles C, Marshall T, Price MJ, Marwaha S, Davies EH, Jackson LJ, Matthews KL, Camaradou J, Calvert M, Haroon S. Symptoms and risk factors for long COVID in non-hospitalized adults. Nat Med. 2022;28:1706-1714. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 105] [Cited by in F6Publishing: 494] [Article Influence: 247.0] [Reference Citation Analysis (0)] |
| 33. | Barnes E, Goodyear CS, Willicombe M, Gaskell C, Siebert S, I de Silva T, Murray SM, Rea D, Snowden JA, Carroll M, Pirrie S, Bowden SJ, Dunachie SJ, Richter A, Lim Z, Satsangi J, Cook G, Pope A, Hughes A, Harrison M, Lim SH, Miller P, Klenerman P; PITCH consortium, Basu N, Gilmour A, Irwin S, Meacham G, Marjot T, Dimitriadis S, Kelleher P, Prendecki M, Clarke C, Mortimer P, McIntyre S, Selby R, Meardon N, Nguyen D, Tipton T, Longet S, Laidlaw S, Orchard K, Ireland G; CONSENSUS, Thomas D, Kearns P, Kirkham A, McInnes IB; OCTAVE Collaborative Group. SARS-CoV-2-specific immune responses and clinical outcomes after COVID-19 vaccination in patients with immune-suppressive disease. Nat Med. 2023;29:1760-1774. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 27] [Cited by in F6Publishing: 47] [Article Influence: 47.0] [Reference Citation Analysis (0)] |