Do socioeconomic inequalities increase the spread of COVID-19 in Turkey?

This paper clarifies the medical and socio-economic factors affecting the prevalence of COVID-19 by using clinical and survey data in a binary probit model. Socio-economic factors are associated with risk of infection and can increase exposure to and mortality from COVID-19. Inequalities in socio-economic variables affect the prevalence to different degrees. Disparities in education and poverty are more important than being employed or being a smoker for the spread of COVID-19, we find evidence that confirms the hypothesis.

Validity and Reliability of the COVID-19 Knowledge, Attitude and Behavior Scale.

BACKGROUND: The aim of this research is to develop a scale that will evaluate the knowledge, attitudes and behaviors of employees about COVID-19 and to test its validity and reliability. METHODOLOGY: The methodological type of research was used between August-November 2020, under observation in organized industrial zones. Information was collected from a total of 543 employees. Confirmatory factor analysis and correlation analysis were performed for the value, item-total correlations and construct validity. SPSS 25.0 (IBM Inc., Armonk, NY, USA), Jasp 0.14 (University of Amsterdam) and Lisrel 9.1(Scientific Software International, Inc., Chapel Hill, NC, USA) programs were used in the analysis. RESULTS: 83.1% of the participants in the study are male, the average age is 37.4 ± 8.0, 76.1% are married, and 49.4% are high school graduates. The Cronbach alpha value of the COVID-19 information part is 0.86 in total, the contamination information dimension is 0.71 and the protection information dimension is 0.84. The COVID-19 attitude section consists of four sub-dimensions and 13 items classified within the framework of the health belief model. In summary, the goodness of fit values for the knowledge, attitude and behavior sections, respectively, are: RMSEA values 0.05, 0.03 and 0.04; CFI values 0.98, 0.98 and 0.99; GFI values 0.97, 0.97 and 0.99. CONCLUSIONS: It has been determined that the internal consistency of the COVID-19 knowledge, attitude and behavior scale conducted on employees is high and compatible, and its validity findings are sufficient. The scale is recommended as an applicable tool to measure COVID-19 knowledge, attitudes and behaviors.

[Investigation of the Relationship Between the Immune Responses due to COVID-19 Vaccine and Peripheral Bloodlymphocyte Subtypes of Healthcare Workers]. / Saglik Çalisanlarinda COVID-19 Asisina Bagli Bagisik Yanit ile Hemogram Parametreleri ve Periferik Kandaki Lenfosit Alt Tipleri Arasindaki Iliskinin Arastirilmasi.

Worldwide vaccination is the best strategy to limit the Coronavirus disease-2019 (COVID-19) pandemic. The aim of this study was to investigate the antibody levels and hemogram parameters and the prediction of T-helper, T-cytotoxic and B lymphocyte subtypes in the peripheral blood for the development of these antibodies in the selected group of healthcare workers who were vaccinated with CoronaVac® (Sinovac, China). In a previous study with the same researchers, blood samples were taken from healthcare workers one month after the second vaccination, and anti-RBD anti-severe acute respiratory syndrome coronavirus-2 (anti-SARS-CoV-2) IgG antibodies were measured by enzyme linked immunosorbent assay (ELISA) method. Test results were classified as binding antibody <25.6 BAU/mL unresponsive, 25.6-35.1 BAU/mL weak response, <35.2 BAU/mL strong response, according to the assay manufacturer's recommendations. According to these criteria, it was determined that 22 (8.3%) people had no response, 25 (9.5%) people had a moderate response, and 217 (82.2%) people had a strong response. According to these results, 30 people from each group were invited. The results of three individuals were excluded from the evaluation due to chronic illness. A total of 87 health workers were included in the study. Twenty-two of these people had no response, 25 had a moderate response, and 40 had a good response. Flow cytometry was used to examine the peripheral blood lymphocyte percentage distribution. Statistical analyzes were performed with SPSS 26 software. The conformity of the variables to the normal distribution was examined using analytical methods (Kolmogorov-Smirnov/ Shapiro-Wilk tests). Pearson's Chi-square test was used to compare categorical variables. The correlation between the antibody level and the measurement results of hemogram parameters and lymphocyte indicators was evaluated by Pearson's correlation analysis. The model was established by performing linear regression analysis with the variables correlated with the antibody level. Cases with a p value below 0.05 were considered statistically significant. The age range of the participants in the study was 22-69. The mean age was 45.5 ± 10.4 years. Antibodies against SARS-CoV-2 virus were detected by ELISA method in 65 (74.7%) of the healthcare professionals, while no antibodies were detected in 22 (25.3%) of them. Lymphocyte count (p= 0.002), CD3 count (p= 0.0004), CD4 count (p= 0.0001), CD3/CD19 ratio (p= 0.011), CD4 percentage (p= 0.004) in the antibody positive group was found to be significant. According to the level of correlation between antibody level and lymphocyte indicators, a statistically significant negative correlation was found in CD3, CD4, CD8 and CD19 positive lymphocytes, respectively, and the best correlation was observed in CD3 positive lymphocytes. The formula f (Antibody level)= y= 358002 -0.176 x CD3 + 0.469 x CD19 was created using the linear regression model. In the light of the data of this study, the central role of T and B cells in COVID-19 immunization emerges. The vaccine-related antibody level-related formula may be useful for healthcare professionals in patient follow-up. It is thought that conducting vaccine related immune response studies involving larger populations will contribute more to the literature.

Visual evoked potential and nerve conduction study findings in patients recovered from COVID-19.

OBJECTIVE: COVID-19 infection is associated with peripheral neuropathy. However, subclinical neurological involvement may occur anytime, and diagnostic methods that reveal this subclinical involvement are not well established. We aimed to assess the subclinical neurological involvement by visual evoked potential (VEP) measurements and nerve conduction studies (NCS) and explore the relationship between neurological electrophysiological findings and the severity of COVID-19 infection. METHODS: Seventy-six patients recovered from COVID-19 infection, and 44 healthy controls were enrolled in the study. Patients were assessed for clinical and demographic parameters. NCS and VEP analyses were performed to detect any peripheral neuropathy or optic neuropathy in both groups. RESULTS: None of the COVID-19 patients had electrophysiological evidence of peripheral neuropathy. However, patients with COVID-19 pneumonia had significant abnormalities in several peripheral nerve measurements compared to patients without pneumonia. Although P100 parameters did not differ significantly between patients and controls, 12 patients with COVID-19 had prolonged P100 latencies. CONCLUSIONS: We detected subclinical afferent visual pathway abnormality evaluated by VEP analysis. In addition, we found subtle electrophysiological features in the NCS of the patients presented with COVID-19 pneumonia. However, our findings did not fortify the diagnosis of peripheral neuropathy or optic neuropathy. Further studies are needed to determine the characteristics of COVID-19-related peripheral neuropathy/optic neuropathy whether it has distinct clinical features and disease course.

Adverse events report of inactivated COVID-19 vaccine from 4040 healthcare workers.

OBJECTIVES: Numerous vaccination studies are conducted to protect against COVID-19 infection, and preclinical and clinical studies are still ongoing worldwide. During this extraordinary period, the necessity to perform COVID-19 vaccine studies and immunization programs together has emerged. Vaccine Adverse Effects (VAEs) need to be documented quickly. We aimed to determine the VAEs and to compare the frequency of VAEs between groups according to sociodemographic characteristics after the inactivated vaccine (CoronaVac) was administered to healthcare workers (HCWs) in Turkey. METHODS: An online questionnaire was delivered to 4040 volunteer HCWs across the whole country who were vaccinated with CoronaVac. Sociodemographic characteristics, medical history, history of COVID-19 infection, and VAEs occurring after the first and second doses of the inactivated vaccine were evaluated. RESULTS: The most common local and systemic VAEs after first and second doses of the COVID-19 vaccine were reported as, pain at the injection site (37.9%; 37.6%), headache (21.5%; 16.8%), fatigue (18%; 15%), drowsiness (9.6%; 8.2%), back pain (8.8%; 8.2%), nausea (6.3%; 4.8%), and joint pain (4.7%; 4.7%). Individuals with a history of allergies (generalized or vaccine-related) and females had a higher rate of VAE. Participants aged 60 and over reported less frequent VAEs. CONCLUSION: It is extremely important to identify and document the VAEs occurring in the early postvaccination period in different groups of the community. These initial findings may provide reassurance to healthcare providers and vaccine recipients and promote confidence in the safety of this inactive COVID-19 vaccine, however longitudinal follow-up studies are recommended.