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Sabri Engin AltintopSuluova State Hospital, Department of Internal Medicine, Amasya, Turkey

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Tugce Unalan-AltintopDepartment of Medical Microbiology, Amasya University Sabuncuoglu Serefeddin Research and Training Hospital, Amasya, Turkey

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Mustafa CihangirogluDepartment of Infectious Disease and Clinical Microbiology, Faculty of Medicine, Amasya University, Amasya, Turkey

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Pelin OnarerDepartment of Medical Microbiology, Amasya University Sabuncuoglu Serefeddin Research and Training Hospital, Amasya, Turkey

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Fikriye Milletli-SezginDepartment of Medical Microbiology, Faculty of Medicine, Amasya University, Amasya, Turkey

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Melih GozukaraAmasya Provincial Directorate of Health, Amasya, Turkey

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Bilge GozukaraSuluova State Hospital, Department of Internal Medicine, Amasya, Turkey

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Erman ZenginAmasya Provincial Directorate of Health, Amasya, Turkey

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Abstract

SARS-CoV-2 virus was initially identified in Wuhan, China, in December 2019 and a global pandemic was declared in March 2020 by World Health Organization. COVID-19 disease is characterized with severe pneumonia and hypoxemia, especially in the elderly population. The elderly population was primarily vaccinated with CoronaVac, which is a whole virion inactivated vaccine (Sinovac Biotech, China) in Turkey. This study aimed to investigate the association of viral load and laboratory parameters with the severity of the disease and vaccination status in elderly (older than 60 years old) COVID-19 patients. The age range of the patients was 61–97 years old with a mean of 71.80. Vaccinated patients had a lower viral load (P = 0.253) in nasopharyngeal swabs during breakthrough COVID-19 infection compared to unvaccinated ones and were hospitalized for a shorter period of time in hospital wards (P = 0.035). A lower number of patients were vaccinated in both moderate (n = 33, 29.20%) and severe/critical group (n = 46, 34.07%) (P = 0.412). Only 17 (32.08%) vaccinated patients were hospitalized in an intensive care unit (ICU), whereas 36 (67.92%) of the ICU patients were unvaccinated (P = 0.931). Severe/critical patients had higher c-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), fibrinogen, ferritin, and lactate dehydrogenase (LDH) levels compared to the moderate group on the admission day (P < 0.05). Our study suggested that elderly patients vaccinated with CoronaVac had a shorter stay in hospitals and according to our results CRP, PLR, fibrinogen, ferritin, and LDH levels could be used to determine the severity of the infections.

Abstract

SARS-CoV-2 virus was initially identified in Wuhan, China, in December 2019 and a global pandemic was declared in March 2020 by World Health Organization. COVID-19 disease is characterized with severe pneumonia and hypoxemia, especially in the elderly population. The elderly population was primarily vaccinated with CoronaVac, which is a whole virion inactivated vaccine (Sinovac Biotech, China) in Turkey. This study aimed to investigate the association of viral load and laboratory parameters with the severity of the disease and vaccination status in elderly (older than 60 years old) COVID-19 patients. The age range of the patients was 61–97 years old with a mean of 71.80. Vaccinated patients had a lower viral load (P = 0.253) in nasopharyngeal swabs during breakthrough COVID-19 infection compared to unvaccinated ones and were hospitalized for a shorter period of time in hospital wards (P = 0.035). A lower number of patients were vaccinated in both moderate (n = 33, 29.20%) and severe/critical group (n = 46, 34.07%) (P = 0.412). Only 17 (32.08%) vaccinated patients were hospitalized in an intensive care unit (ICU), whereas 36 (67.92%) of the ICU patients were unvaccinated (P = 0.931). Severe/critical patients had higher c-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), fibrinogen, ferritin, and lactate dehydrogenase (LDH) levels compared to the moderate group on the admission day (P < 0.05). Our study suggested that elderly patients vaccinated with CoronaVac had a shorter stay in hospitals and according to our results CRP, PLR, fibrinogen, ferritin, and LDH levels could be used to determine the severity of the infections.

Introduction

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was initially identified in Wuhan, China, in December 2019 and a pandemic was declared in March 2020 by the World Health Organization (WHO). SARS-CoV-2 is related to the SARS-associated coronavirus (SARS-CoV), which caused an epidemic in 2002–2003. For cell entry, both viruses use the same receptor; however, SARS-CoV-2 uses a modified spike protein with a higher affinity for the homologous human receptor, which likely increases viral infectivity. COVID-19 is characterized by pneumonia and hypoxemia in individuals who require hospitalization, even though the majority of those infected will not become very ill. Acute Respiratory Distress Syndrome (ARDS) and respiratory failure requiring invasive mechanical ventilation can result due to this hypoxemic state [1].

The CoronaVac (Sinovac Biotech, China) vaccine was one of the first vaccinations to be used worldwide. It is a whole virion vaccine inactivated with BPL and produced in Vero cells using the SARS-CoV-2 virus with aluminum hydroxide adjuvant. The recommended immunization regimen is two doses separated by two to four weeks. The vaccination is indicated for the prevention of symptomatic COVID-19 in people aged 18 and above, and listed for emergency use by WHO in May 2021 [2]. There are scarce data on viral load, clinical presentation, and viral dynamics of breakthrough infections with CoronaVac in the elder population.

This study aimed to investigate the association of viral load with the severity of the disease and vaccination status in elderly COVID-19 patients. The clinical, radiological, and laboratory characteristics of the patients followed up in Amasya, Turkey was also explored from the hospital records.

Materials and methods

Study participation

This study was conducted as a retrospective cohort study. COVID-19 patients who were older than 60 years, were enrolled in this study and were followed up at Amasya University Sabuncuoglu Serefeddin Research and Training Hospital and Suluova State Hospital between February and June 2021. During that period, an inactivated whole virion vaccine CoronaVac was used in our country. The study participants include moderate, severe, and critical COVID-19 patients who were tested positive for SARS-CoV-2 by RT-qPCR. Patients with asymptomatic and mild clinical picture were excluded from the study, due to the lack of medical records. This study was approved by Amasya University Non-Interventional Clinical Studies Ethical Committee (No: 7/106).

Viral loads

National COVID-19 guidelines were used for the diagnosis of suspected COVID-19 patients [3]. Fresh samples were tested for COVID-19 immediately after reaching the laboratory by a commercial reverse transcription-quantitative real-time PCR (RT-qPCR) (Bio-Speedy Direct RT-qPCR SARS CoV-2, Bioeksen, Turkey). The samples were collected in VNAT Nucleic Acid Buffer (Bioeksen, Turkey), which enables the extraction of viral nucleic acid in five minutes. Ct values, which demonstrate the amount of amplified target gene by detecting the fluorescent signal over the threshold, were investigated by the RT-qPCR method and utilized for the estimation of viral loads in nasopharyngeal swab samples. In our study, the difference between the positive control Ct value and sample Ct value (ΔCt) was used to normalize the estimation of viral loads, and to minimize the variation among different runs [4, 5]. Lower ΔCt values indicate the higher presence of the target gene, in other words, higher viral load in the investigated sample.

Clinical, demographic, and laboratory parameters

The clinical, demographic, and laboratory parameters were obtained from the medical records of both hospitals. The clinical severity was determined using the classification system proposed by the National Institute of Health (NIH) and summarized in Table 1 [6]. Vaccination status of the patients were determined from records of Amasya Provincial Directorate of Health. The individuals were grouped as vaccinated if they were diagnosed positive by PCR at least 14 days after two doses, according to the vaccination breakthrough definition of the Centers for Disease Control and Prevention (CDC) [7]. Patients who were vaccinated with one dose, or who were vaccinated with two doses but diagnosed positive before 14 days were grouped as unvaccinated.

Table 1.

The clinical classification system of COVID-19

Clinical classificationIdentifying features
ModeratePatients with the lower respiratory disease during clinical assessment or imaging and who have an oxygen saturation (SpO2) ≥94% on room air at sea level.
Severe/CriticalPatients who have SpO2 <94% on room air at sea level, a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) <300 mm Hg, a respiratory rate >30 breaths/min, or lung infiltrates >50%; and with respiratory failure, septic shock, and/or multiple organ dysfunction.

Statistical analysis

The statistical analysis was employed using Statistical Package for Social Sciences (SPSS), for Windows 23.0 (SPSS Inc. Chicago, USA). For descriptive statistics, categorical variables were given as numbers and percentage, continuous variables as mean and standard deviation or median (min-max). Normal distribution was analyzed using visual (hidtogram and probability graphs) and analytical (Kolmogorov-Smirnov/Shapiro-Wilk tests) methods for continuous variables. For normal distributed variables, mean and standard deviation was given, Median (min-max) values were given for variable that are not normal distributed. For statistical analysis, Student-T test was use for normal variables and Mann-Whitney U test for others. Categorical variables were compared with Chi-square and Fisher test. Statistical significance was taken as P < 0.05.

Results

Demographic and clinical characteristics

A total of 248 COVID-19 patients were enrolled in the study. The mean age of the patients was 71.80 (61–97) years. The number of male patients (n = 130, 52.42%) were slightly higher than females (n = 118, 47.58%). Due to clinical severity, 113 (45.56%) of the patients were classified in the moderate group and 135 (54.44%) in the severe/critical. 53 (21.37%) of the patients were followed-up in an intensive care unit (ICU). The average time of hospitalization is 7.00 days, and 8 days in ICU.

Vaccination, ΔCt values, and hospitalization

Patients who were vaccinated with a double dose of CoronaVac (n = 79) had a higher ΔCt value compared to the unvaccinated group (P = 0.253). A lower number of patients were vaccinated in both moderate (n = 33, 29.20%) and severe/critical group (n = 46, 34.07%) (P = 0.412). Only 17 (32.08%) out of 79 vaccinated patients were hospitalized in ICU, whereas 36 (67.92%) of the ICU patients were unvaccinated (n = 169) (P = 0.931). Vaccinated patients were hospitalized for shorter in hospital wards (P = 0.035) (Table 2).

Table 2.

Characteristics of vaccinated and unvaccinated individuals

UnvaccinatedVaccinatedTotalP value
ΔCt−2.23 ± 5.12−1.43 ± 4.94−1.97 ± 5.070.253
Moderate80 (70.8%)33 (29.2%)113 (100%)0.412
Severe/Critical89 (65.9%)46 (34.1%)135 (100%)
Hospitalization (days)8.00 (0–37)6.50 (0–51)7.00 (0–51)0.035
ICU36 (67.9%)17 (32.1%)35 (100%)0.969
ICU (days)8 (2–30)8 (1–30)8 (1–30)0.437

*ICU: intensive care unit.

Clinical severity, ΔCt values, and laboratory parameters

Patients who were classified as severe/critical had lower ΔCt values compared to moderate ones (P = 0.829). The age and gender of the patients were similar in both groups. Severe/critical patients had higher CORADS scores on Thorax CT scans (P < 0.001). Out of 53 ICU hospitalized patients, 42 (79.25%) were severe/critical and 11 (20.75%) were moderate (P < 0.001). Severe/critical patients had higher c-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), fibrinogen, ferritin, and lactate dehydrogenase (LDH) levels compared to the moderate group on the admission day (P < 0.05). Neutrophil-to-lymphocyte (NLR) ratio was slightly lower in severe/critical group (<0.001) Both groups had leukocytosis and lymphopenia (Table 3). 14 (17.72%) of the vaccinated patients were accepted as exitus state, whereas 33 (19.53%) of the unvaccinated patients (P = 0.74).

Table 3.

Characteristics of moderate and severe/critical COVID-19 patients

Moderate (n = 113)Severe/Critical (n = 135)Total (n = 248)P value
ΔCt−1.90 ± 4.69−2.04 ± 5.38−1.97 ± 5.070.829
Age70 (61–92)71 (61–97)71 (61–91)0.614
Gender (Female)56 (47.5%)62 (52.5%)118 (100%)0.568
Thorax CT
 CORADS 01 (100%)1 (100%)N/A
 CORADS 113 (86.7%)2 (13.3%)15 (100%)<0.001
 CORADS 227 (96.4%)1 (3.6%)28 (100%)<0.001
 CORADS 363 (88.7%)8 (11.3%)71 (100%)<0.001
 CORADS 48 (22.9%)27 (77.1%)35 (100%)0.003
 CORADS 51 (4.0%)24 (96.0%)25 (100%)<0.001
ICU11 (20.8%)42 (70.2%)53 (100%)<0.001
CRP55.0 (1.15–232.0)127.67 (5.0–337.0)78.48 (1.15–337.0)<0.001
Leucocyte5.46 (2.68–428.0)6.68 (0–19.44)6.09 (0–428.0)0.007
Lymphocyte1.14 (0.28–10.15)1.15 (0.07–4.98)1.15 (0.07–10.15)0.368
NLR0.30 (0.03–1.25)0.20 (0.05–1.42)0.22 (0.03–1.42)<0.001
PLR156 (0–566)200 (0–520)169 (0–566)0.018
Fibrinogen489 (213–924)592.5 (170–940)547 (170–940)<0.001
Ferritin145.9 (4.5–3534.5)345.2 (0–14419)249.3 (0–14419)0.004
LDH240 (170–492)361 (210–815)294 (170–815)<0.001

*CT: computer tomography, ICU: intensive care unit, CRP: c-reactive protein, NLR: neutrophil-to lymphocyte ratio, PLR: platelet-to-lymphocyte ratio, LDH: lactate dehydrogenase.

Discussion

Vaccines have been proven to reduce symptomatic SARS-CoV-2 infections significantly. However, the influence of vaccination on infectiousness of breakthrough cases is unknown. In this study, we observed that fully vaccinated patients with CoronaVac had higher ΔCt values compared to unvaccinated ones, however it was not statistically significant. This result suggests that vaccinated cases with decreased viral loads may have a reduced transmission risk unlike unvaccinated. Another study from China also found a decreased viral load in patients vaccinated with CoronaVac [8]. These results are concordant with studies investigating the relationship between viral load and the BNT162b2 mRNA vaccine (BioNTech, Pfizer, USA), where fully vaccinated patients were found to have lower viral loads [910]. In another study, which investigated the viral loads of breakthrough cases with different variants, full immunization significantly lowered infectious viral load for Delta breakthrough cases, compared to unvaccinated. Omicron breakthrough cases showed that only boosted but not fully vaccinated people had a lower infectious viral load than unvaccinated patients [11]. All these findings suggest that although breakthrough cases occur after full vaccination, they were found to have lower viral loads and had less transmission risk. However, it should be taken into account that lower infectious viral load does not always imply lower secondary attack rates, and it is dependent on other influencing factors such as viral particle environmental stability. Epidemiological studies have found that vaccinated index cases transmit less, but the extent of the effect varies on the predominant variant, the vaccine used, and the period since immunization [12]. While the viral load is an important component of transmission, the process of human-to-human transmission is complicated, and other factors such as recommended protection measures, overall incidence, perceived risks, and the context of contacts (household vs community transmission) can all have an impact on the results of the studies.

There are three randomized, placebo-controlled, phase 3 clinical trials, conducted in Brazil, Indonesia, and Turkey to determine the efficacy of CoronaVac (Sinopharm, China). The interim analyzes showed 50.65% efficacy against symptomatic illness in Brazil, 65.30% in Indonesia, and 83.50% in Turkey. The effectiveness against hospitalization and mortality was significantly higher, reaching 100%, albeit with large confidence ranges [13]. The number of participants in the clinical trials who were older than 60 years old was insufficient to evaluate efficacy in this age range. Chile was one of the first countries to deploy the CoronaVac vaccination on a broad scale in its national program. They reported the adjusted vaccine effectiveness of full immunization (two doses received, assessed 14 days after the second dose, with a 4-week interval between the doses) was 65.9% against COVID-19, 87.4% against hospitalization, 90.3% against ICU admission, and 86.3% against COVID-19–related mortality, for 10.2 million individuals who are 16 years of age or older. The study in Chile also looked at the effectiveness of the vaccination in older people, which had not been thoroughly explored in phase 3 studies. In the fully immunized group of people 60 years and older, the adjusted vaccine effectiveness against COVID-19 was 66.6%, with 85.3% against hospitalization, 89.2% against ICU admission, and 86.5% against COVID-19–related death [14]. A study from Brazil reported 81.6% effectiveness against hospitalization after the second dose of CoronaVac in 60–79 years old patients [15]. Another study reported two severe cases and no fatal cases in patients older than 60 years [16]. The effectiveness for CoronaVac was calculated as 69.9% for elder patients in Hong Kong [17]. Data on elderly patients vaccinated with CoronaVac is insufficient. Our study showed that fully vaccinated cases were hospitalized shorter in the ward. Our findings are consistent with studies evaluating long-term immune responses after inactivated virus vaccines [18–20]. However, the efficacy of inactivated vaccines has been shown to decrease with time, and studies support the booster dose to overcome this [15].

In this research, COVID-19 patients with high SARS-CoV-2 viral load had a greater risk of severe/critical presentation. Some investigations have demonstrated that SARS-CoV-2 viral loads on the upper respiratory tract are positively linked with illness severity, which is consistent with our findings [21–24]. Others, on the other hand, have found no link [25–27]. This discrepancy could be because, sample collection and SARS-CoV-2 viral load estimation took place at different times. Another explanation for the contradicting results could be that viral pneumonia in severe COVID-19 patients evolves into ARDS, which is the primary cause of intubation in COVID-19 and appears later in the disease course. Due to the temporal link between viral load in COVID-19 and disease progression, where viral load declines with disease duration, COVID-19 patients may be in the latter stages of their disease by the time they are intubated, which could explain their lower viral load.

In our study, we found that elevated CRP, PLR, fibrinogen, ferritin, and LDH were associated with severe/critical outcomes. Leukocytosis and lymphopenia were detected in both moderate and critical/severe groups. These findings are concurrent with the literature. A systematic review from Mehta et al. elucidated that lymphopenia was common in all COVID-19 patients, regardless of their severity. In comparison to the non-severe group, leukocytosis was more prevalent in the severe group. Serum LDH elevations followed a similar pattern, with a larger prevalence in the severely affected patients [28]. Zhou et al. found a difference in ferritin elevation response between the severe and non-severe groups [29]. A greater PLR level on admission is linked to increased morbidity and mortality, according to a systematic review from Sarkar et al. [30]. Han et al. demonstrated that fibrinogen levels are not only higher in healthy populations but also higher in critical COVID-19 patients compared to mild and moderate patients [31]. The laboratory markers that are linked to severe illness have a crucial role in the identification of the severe form of COVID-19 early and guide the clinicians to take proactive actions to prevent morbidity and mortality.

There are some limitations of this study. To begin with, it was a retrospective cohort study, based on medical records. Raw Ct measurements, normalization with positive control Ct values, and normalization with standard references with known copy numbers were all utilized to estimate the viral loads. In this study, normalization with positive control was employed to determine presumptive viral loads of samples because exact copy numbers per ml could not be obtained due to a lack of standard reference materials. The sampling period, sample quality, methodology, and use of fast viral nucleotide extraction may all have an impact on Ct values. Another limitation of the study is that [19] the emerging variant of concerns that demonstrate lower vaccine effectiveness against the symptomatic disease were not investigated.

To conclude, our study demonstrated that vaccinated elderly patients have lower viral loads and shorter stays in hospitals. Severe/critical patients had higher viral loads, CRP, PLR, fibrinogen, and ferritin levels compared to moderate cases. To enable rapid policy decisions, the global health community must work together to close remaining information gaps about the COVID-19 vaccine's effectiveness and characteristics of severe/critical presentation, with timely sharing of changing data.

Conflict of interest

The authors declare no conflict of interest or funding regarding this publication.

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    McMenamin ME, Nealon J, Lin Y, Wong JY, Cheung JK, Lau EHY, et al. Vaccine effectiveness of one, two, and three doses of BNT162b2 and CoronaVac against COVID-19 in Hong Kong: a population-based observational study. Lancet Infect Dis. 2022; 22: 14351443.

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    Sauré D, O'Ryan M, Torres JP, Zuniga M, Santelices E, Basso LJ. Dynamic IgG seropositivity after rollout of CoronaVac and BNT162b2 COVID-19 vaccines in Chile: a sentinel surveillance study. Lancet Infect Dis. 2022; 22: 5663.

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The author instruction is available in PDF.
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Senior editors

Editor-in-Chief: Prof. Dóra Szabó (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)

Managing Editor: Dr. Béla Kocsis (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)

Co-editor: Dr. Andrea Horváth (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)

Editorial Board

  • Prof. Éva ÁDÁM (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)
  • Prof. Sebastian AMYES (Department of Medical Microbiology, University of Edinburgh, Edinburgh, UK.)
  • Dr. Katalin BURIÁN (Institute of Clinical Microbiology University of Szeged, Szeged, Hungary; Department of Medical Microbiology and Immunobiology, University of Szeged, Szeged, Hungary.)
  • Dr. Orsolya DOBAY (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)
  • Prof. Ildikó Rita DUNAY (Institute of Inflammation and Neurodegeneration, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany)
  • Prof. Levente EMŐDY(Department of Medical Microbiology and Immunology, University of Pécs, Pécs, Hungary.)
  • Prof. Anna ERDEI (Department of Immunology, Eötvös Loránd University, Budapest, Hungary, MTA-ELTE Immunology Research Group, Eötvös Loránd University, Budapest, Hungary.)
  • Prof. Éva Mária FENYŐ (Division of Medical Microbiology, University of Lund, Lund, Sweden)
  • Prof. László FODOR (Department of Microbiology and Infectious Diseases, University of Veterinary Medicine, Budapest, Hungary)
  • Prof. József KÓNYA (Department of Medical Microbiology, University of Debrecen, Debrecen, Hungary)
  • Prof. Yvette MÁNDI (Department of Medical Microbiology and Immunobiology, University of Szeged, Szeged, Hungary)
  • Prof. Károly MÁRIALIGETI (Department of Microbiology, Eötvös Loránd University, Budapest, Hungary)
  • Prof. János MINÁROVITS (Department of Oral Biology and Experimental Dental Research, University of Szeged, Szeged, Hungary)
  • Prof. Béla NAGY (Centre for Agricultural Research, Institute for Veterinary Medical Research, Budapest, Hungary.)
  • Prof. István NÁSZ (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)
  • Prof. Kristóf NÉKÁM (Hospital of the Hospitaller Brothers in Buda, Budapest, Hungary.)
  • Dr. Eszter OSTORHÁZI (Institute of Medical Microbiology, Semmelweis University, Budapest, Hungary)
  • Prof. Rozália PUSZTAI (Department of Medical Microbiology and Immunobiology, University of Szeged, Szeged, Hungary)
  • Prof. Peter L. RÁDY (Department of Dermatology, University of Texas, Houston, Texas, USA)
  • Prof. Éva RAJNAVÖLGYI (Department of Immunology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary)
  • Prof. Ferenc ROZGONYI (Institute of Laboratory Medicine, Semmelweis University, Budapest, Hungary)
  • Prof. Zsuzsanna SCHAFF (2nd Department of Pathology, Semmelweis University, Budapest, Hungary)
  • Prof. Joseph G. SINKOVICS (The Cancer Institute, St. Joseph’s Hospital, Tampa, Florida, USA)
  • Prof. Júlia SZEKERES (Department of Medical Biology, University of Pécs, Pécs, Hungary.)
  • Prof. Mária TAKÁCS (National Reference Laboratory for Viral Zoonoses, National Public Health Center, Budapest, Hungary.)
  • Prof. Edit URBÁN (Department of Medical Microbiology and Immunology University of Pécs, Pécs, Hungary; Institute of Translational Medicine, University of Pécs, Pécs, Hungary.)

 

Editorial Office:
Akadémiai Kiadó Zrt.
Budafoki út 187-187, A/3, H-1117 Budapest, Hungary

Editorial Correspondence:
Acta Microbiologica et Immunologica Hungarica
Institute of Medical Microbiology
Semmelweis University
P.O. Box 370
H-1445 Budapest, Hungary
Phone: + 36 1 459 1500 ext. 56101
Fax: (36 1) 210 2959
E-mail: amih@med.semmelweis-univ.hu

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2021  
Web of Science  
Total Cites
WoS
696
Journal Impact Factor 2,298
Rank by Impact Factor Immunology 141/161
Microbiology 118/136
Impact Factor
without
Journal Self Cites
2,143
5 Year
Impact Factor
1,925
Journal Citation Indicator 0,39
Rank by Journal Citation Indicator Immunology 146/177
Microbiology 129/157
Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0,362
Scimago Quartile Score Immunology and Microbiology (miscellaneous) (Q3)
Medicine (miscellaneous) (Q3)
Scopus  
Scopus
Cite Score
3,6
Scopus
CIte Score Rank
General Immunology and Microbiology 26/56 (Q2)
Infectious Diseases 149/295 (Q3)
Microbiology (medical) 66/118 (Q3)
Scopus
SNIP
0,598

2020  
Total Cites 662
WoS
Journal
Impact Factor
2,048
Rank by Immunology 145/162(Q4)
Impact Factor Microbiology 118/137 (Q4)
Impact Factor 1,904
without
Journal Self Cites
5 Year 0,671
Impact Factor
Journal  0,38
Citation Indicator  
Rank by Journal  Immunology 146/174 (Q4)
Citation Indicator  Microbiology 120/142 (Q4)
Citable 42
Items
Total 40
Articles
Total 2
Reviews
Scimago 28
H-index
Scimago 0,439
Journal Rank
Scimago Immunology and Microbiology (miscellaneous) Q4
Quartile Score Medicine (miscellaneous) Q3
Scopus 438/167=2,6
Scite Score  
Scopus General Immunology and Microbiology 31/45 (Q3)
Scite Score Rank  
Scopus 0,760
SNIP
Days from  225
submission
to acceptance
Days from  118
acceptance
to publication
Acceptance 19%
Rate

2019  
Total Cites
WoS
485
Impact Factor 1,086
Impact Factor
without
Journal Self Cites
0,864
5 Year
Impact Factor
1,233
Immediacy
Index
0,286
Citable
Items
42
Total
Articles
40
Total
Reviews
2
Cited
Half-Life
5,8
Citing
Half-Life
7,7
Eigenfactor
Score
0,00059
Article Influence
Score
0,246
% Articles
in
Citable Items
95,24
Normalized
Eigenfactor
0,07317
Average
IF
Percentile
7,690
Scimago
H-index
27
Scimago
Journal Rank
0,352
Scopus
Scite Score
320/161=2
Scopus
Scite Score Rank
General Immunology and Microbiology 35/45 (Q4)
Scopus
SNIP
0,492
Acceptance
Rate
16%

 

Acta Microbiologica et Immunologica Hungarica
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Acta Microbiologica et Immunologica Hungarica
Language English
Size A4
Year of
Foundation
1954
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1217-8950 (Print)
ISSN 1588-2640 (Online)

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