The world has been suffering from COVID-19 disease for more than a year, and it still has a high mortality rate. In addition to the need to minimize transmission of the virus through non-pharmacological measures such as the use of masks and social distance, many efforts are being made to develop a variety of vaccines to prevent the disease worldwide. So far, several vaccines have reached the final stages of safety and efficacy in various phases of clinical trials, and some, such as Moderna/NIAID and BioNTech/Pfizer, have reported very high safety and protection. The important point is that comparing different vaccines is not easy because there is no set standard for measuring neutralization. In this study, we have reviewed the common platforms of COVID-19 vaccines and tried to present the latest reports on the effectiveness of these vaccines.

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In the present study, the magnetic NH2-MIL-101(Al)/chitosan nanocomposite (MIL/Cs@Fe3O4 NCs) was synthesized and used in the removal of azithromycin (AZT) from an aqueous solution for the first time. The as-synthesized MIL/Cs@Fe3O4 NCs was characterized by SEM, TEM, XRD, FTIR, BET, and VSM techniques. The effect of various key factors in the AZT adsorption process was modeled and optimized using response surface methodology based on central composite design (RSM-CCD). The low value of p-value (1.3101e−06) and RSD (1.873) parameters, along with the coefficient of determination > 0.997 implied that the developed model was well fitted with experimental data. Under the optimized conditions, including pH: 7.992, adsorbent dose: 0.279 g/L, time: 64.256 min and AZT concentration: 10.107 mg/L, removal efficiency and AZT adsorption capacity were obtained as 98.362 ± 3.24% and 238.553 mg/g, respectively. The fitting of data with the Langmuir isotherm (R2: 0.998, X2: 0.011) and Pseudo-second-order kinetics (R2: 0.999, X2: 0.013) showed that the adsorption process is monolayer and chemical in nature. ΔH° > 0, ΔS° > 0, and ∆G° < 0 indicated that AZT removal was spontaneous and endothermic in nature. The effect of Magnesium on AZT adsorption was more complicated than other background ions. Reuse of the adsorbent in 10 consecutive experiments showed that removal efficiency was reduced by about 30.24%. The performance of MIL/Cs@Fe3O4 NCs under real conditions was also tested and promising results were achieved, except in the treatment of AZT from raw wastewater.

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Background: The news of several people being affected by unusual pneumonia at the beginning of the year 2020 in China led to the introduction of a new type of coronavirus as the cause of a new respiratory disease. With the rapid spread of the disease in China and then to other parts of the world, the new coronavirus became scientifically known as severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and the resulting disease as coronavirus disease 2019 (COVID-19). This disease has a variety of symptoms and can cause SARS. Objectives: This study aimed to investigate the chronic diseases affecting the mortality rate of this disease. Methods: This retrospective cohort study was performed on 7222 eligible patients admitted to hospitals in Sirjan, Iran, from March 2020 to June 2021 with a positive polymerase chain reaction for COVID-19. The researcher extracted information from the patients' files using the questionnaire of demographic characteristics, clinical signs and symptoms, and the history of underlying diseases. The data were analyzed by the SPSS software using descriptive and analytical statistical tests, namely chi-squared, independent samples t-test, and univariate and multivariate logistic regression tests. Results: Out of 7,222 patients with COVID-19, 294 died, of whom 152 were male and 142 were female (OR = 1.23, CI: 0.97 - 1.55). Moreover, 220 people out of 294 dead cases were over 60 years old (OR = 8.92, CI: 6.82 - 11.67). The most common diseases were hypertension (OR = 3.63, CI: 2.81 - 4.69) and diabetes (OR = 3.16, CI: 2.38 - 4.20). The most common symptoms among those who died were respiratory distress (51.4%) and cough (34.7%). Conclusions: The mortality rate is directly related to the underlying diseases in COVID-19, and the most common underlying disease in the statistical population of this study was hypertension. In addition, respiratory distress is a common symptom in dead patients, which can be used as a predictor of death.

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Background: Hypertension is a leading risk factor for morbidity and mortality around the world. Preventing this health problem is considered an important priority. The aim of this study was to investigate the predictive factors for care and control of hypertension (CCH) according to the health belief model (HBM) in patients with hypertension during the COVID-19 epidemic in Sirjan, Iran. Methods: In this cross-sectional study, participants were chosen by simple random sampling. Data were collected by a valid and reliable researcher-made questionnaire from 200 patients with high blood pressure aged 30-60 years. Data were analyzed by SPSS21 and analysis based on descriptive statistics, Pearson correlation coefficients and linear regression were conducted. Results: The results of Pearson correlation coefficients showed that there was a significant correlation between almost all constructs of Health Belief Model (HBM), but the strongest correlations were between self-efficacy and perceived susceptibility (r = 0.940, P ≤ 0.001), and between perceived barriers with perceived benefits (r = -0.615, P ≤ 0.001). According to linear regression, perceived barriers (β = -0.291), cues to action (β = -0.590), and knowledge (β = 0.973) predicted more than 26% of CCH variability. Knowledge had a stronger role than other variables. Conclusions: The results of this study show that the constructs of the Health Belief Model can predict CCH in hypertensive patients. This model can be used as a tool for designing and implementing educational interventions to increase CCH among hypertensive patients.