Background Characterizing the post-COVID health conditions is helpful to direct patients to appropriate healthcare. Aims To describe the presence of symptoms in COVID-19 patients within 6 months after diagnosis and to investigate the associated factors in terms of reporting symptoms. Methods Data of DEU-COVIMER (a telephone interview-based COVID-19 follow-up center established in a tertiary care hospital) was analyzed for SARS-CoV-2 RNA positive participants aged ≥ 18 years from November 1st, 2020, to May 31st, 2021. Symptom frequencies were stratified by demographic and clinical characteristics at one, three, and 6 months after diagnosis. With the patients who had symptoms at baseline, generalized estimating equations were applied to identify the factors associated with reporting of symptoms. Results A total of 5610 patients agreed to participate in the study. Symptom frequency was 37.2%, 21.8%, and 18.2% for the first, third, and sixth months. Tiredness/fatigue, muscle or body aches, and dyspnea/difficulty breathing were the most common symptoms in all time frames. In multivariate analysis, older age, female gender (odds ratio OR 1.74, 95% confidence interval 1.57–1.93), bad economic status (OR 1.37, 1.14–1.65), current smoking (OR 1.15, 1.02–1.29), being fully vaccinated before COVID-19 (OR 0.53, 0.40–0.72), having more health conditions (≥ 3 conditions, OR 1.78, 1.33–2.37), having more symptoms (> 5 symptoms, OR 2.47, 2.19–2.78), and hospitalization (intensive care unit, OR 2.18, 1.51–3.14) were associated with reporting of symptoms. Conclusions This study identifies risk factors for patients who experience post-COVID-19 symptoms. Healthcare providers should appropriately allocate resources prioritizing the patients who would benefit from post-COVID rehabilitation.

Limited data are available on the short‐ to midterm levels of antibodies to the CoronaVac vaccine and quantitative change in humoral response after homologous or heterologous booster doses. In this prospective cohort study, we evaluated the anti‐receptor‐binding domain (RBD) immunoglobulin G (IgG) levels after two doses of CoronaVac and heterologous/homologous booster administration among healthcare workers in a university hospital in Turkey. Quantitative anti‐RBD IgG antibody levels were measured at first and fourth months in 560 healthcare workers who had completed two doses of CoronaVac vaccine, and within 2 months after the third dose of CoronaVac or BNT162b2. Participants were asked to complete a questionnaire during the first blood draw. The seropositivity rate was 98.9% and 89.1%, and the median antibody level was 469.2 AU/ml and 166.5 AU/ml at first and fourth month, respectively. In the fourth month, a mean reduction of 61.4% ± 20% in antibody levels was observed in 79.8% of the participants. The presence of chronic disease (odds ratio [OR]: 1.76, 95% confidence interval [CI]: 1.15–2.69) and being in the 36–50 age group (OR: 2.11, 95% CI: 1.39–3.19) were identified as independent predictors for low antibody response. The antibody level increased 104.8‐fold (median: 17 609.4 vs. 168 AU/ml) and 8.7‐fold (median: 1237.9 vs. 141.4 AU/ml) in the participants who received BNT162b2 and CoronaVac, respectively. During the follow‐up, 25 healthcare workers (4.5%) were infected with severe acute respiratory syndrome coronavirus 2. Considering the waning immunity and circulating variants, a single booster dose of messenger RNA vaccine seems reasonable after the inactivated vaccine especially in risk groups.

Background Healthcare workers (HCWs) have an increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection due to occupational exposure. Strict measures generally focus on the patient-to-HCW contacts. However, interactions between the HCWs also pose a high risk for SARS-CoV-2 exposure. Aims This study was aimed to investigate the effect of social contacts on the level of SARS-CoV-2 exposure risk among workers by broadening the current risk assessment algorithm. Methods Contact tracing records of the workers in a large university hospital between 19th March and 31st December 2020 were analysed. Multivariate conditional logistic regression models were estimated to evaluate factors associated with high-risk exposure for contacts among workers. Results Of the 329 exposed clusters, 260 (79%) were HCW-to-HCW contacted clusters. High-risk exposure was higher in the HCW-to-HCW contacts (44%), when compared to the patient-to-HCW contacts (5%) (P < 0.001). A total of 1827 HCWs contacted a laboratory-confirmed COVID-19-positive co-worker. Among the HCW-to-HCW contacts, high-risk exposure was higher in the support staff (49%, P < 0.001), in non-patient care settings (47%, P < 0.001) and in the social contacts (57%, P < 0.001). Social contacts between workers increased the high-risk exposure (adjusted odds ratio: 3.50, 95% confidence interval 2.62–4.69) in multivariate analysis. Conclusions A significant association between social contacts among workers and high-risk exposure of SARS-CoV-2 was observed. The results of the study emphasize the need for policies regarding the improved protection of HCWs in social settings in addition to patient care services.

Objective: It is important to put forward the characteristics of the COVID-19 cases to fight the disease effectively. The aim of this study is to determine the epidemiological characteristics of COVID-19 cases in Turkey. And also to determine the risk factors associated with intensive care unit (ICU) admission and death. Methods: In this cross-sectional study, the characteristics of the confirmed COVID-19 cases who applied to a University Hospital in Turkey between March 19th and June 11th, 2020, were analyzed. Variables such as epidemic trend, case fatality rate, need for hospitalization, ICU admission rate, and ICU mortality were calculated. In addition, risk factors affecting ICU admission and death were determined by logistic regression analysis. Results: 19.8% of 654 cases participating in the study were asymptomatic at admission. ICU admission rate was 7.6% and case fatality rate found to be 7.8%. Age, male gender, and cancer were associated with ICU admission. Each 1-unit increase in age increased ICU admissions by 8% (OR: 1.08; CI: 1.06-1.10). Men had a 2.71 times higher risk of ICU admission (OR: 2.71; CI: 1.37-5.39); and cancer patients showed 3.72 (OR: 3.72; CI: 1.35-10.20) times more ICU admissions (p<0.05). Age, cancer, and ICU admission were associated with death. Each 1-unit increase in age increased the risk of death by 10% (OR: 1.10; CI: 1.06-1.15). The risk of death was found to be 5.22 times higher in cancer patients (OR: 5.22; GA: 1.09-24.89) and 87.42 times higher in those admitted to ICU (OR: 87.42; GA: 30.15-153.46) (p<0.05). Conclusions: It was revealed that the course of the disease worsens, and deaths increase with age. Male gender has been associated with the increased need for intensive care. Cancer was significantly associated both with ICU admission and death. Attention should be paid to the groups of elderly, men and those with a comorbidity. More detailed studies with larger samples are of critical importance in fighting against the pandemic. Key Words: Turkey, COVID-19, coronavirus, SARS-CoV-2, epidemiology.

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