Introduction In the current COVID-19 pandemic, disease diagnosis is essential for optimal management and timely isolation of infected cases in order to prevent further spread. The aim of this study was to systematically review the assessment of risk and model the predictors of mortality in COVID-19 patients. Methods A systematic search was conducted of PubMed, Scopus, Embase, Google Scholar, and Web of Science databases. Variables associated with hospital mortality using bivariate analysis were included as potential independent predictors associated with mortality at the p <0.05levels. Results We included 114 studies accounting for 310,494 patients from various parts of the world. For the purpose of this analysis, we set a cutoff point of 10% for the mortality percentages. High mortality rates were defined as higher than 10% of confirmed positive cases and were given a score of two, while low mortality percentage (<10%) was assigned to the score of one. We then analyzed the associations between 72 variables and the observed mortality rates. These variables included a large range of related conditions such as demographics, signs and symptoms and related morbidities, vital signs, laboratory findings, imaging studies, underlying diseases, and the status of countries' income based on United Nation's classifications. Conclusion Findings suggest that older age, hypertension, and diabetes mellitus conferred a significant increased risk of mortality among patients with COVID-19. In the multivariate analysis, only diabetes mellitus demonstrated an independent relationship with increased mortality. Further studies are needed to ascertain the relationship between possible risk factors with COVID-19 mortality.

Introduction While COVID-19 pandemic continues to spread worldwide, researchers have linked patterns of traits to poor disease outcomes. Risk factors for COVID-19 include asthma, elderly age, being pregnant, having any underlying diseases such as cardiovascular disease, diabetes, obesity, and experiencing lifelong systemic racism. Recently, connections to certain genes have also been found, although the susceptibility has not yet been established. We aimed to investigate the available evidence for the genetic susceptibility to COVID-19. Methods This study was a systematic review of current evidence to investigate the genetic susceptibility of COVID-19. By systematic search and utilizing the keywords in the online databases including Scopus, PubMed, Web of Science, and Science Direct, we retrieved all the related papers and reports published in English from December 2019 to September 2020. Results According to the findings, COVID-19 uses the angiotensin-converting enzyme 2 (ACE2) receptor for cell entry. Previous studies have shown that people with ACE2 polymorphism who have type 2 transmembrane serine proteases (TMPRSS2) are at high risk of SARS-CoV-2 infection. Also, two studies have shown that males are more likely to become infected with SARS-CoV-2 than females. Besides, research has also shown that patients possessing HLA-B*15:03 genotype may become immune to the infection. Conclusion Combing through the genome, several genes related to immune system’s response were related to the severity and susceptibility to the COVID-19. In conclusion, a correlation was found between the ACE2 levels and the susceptibility to SARS-CoV-2 infection.

Introduction: Many potential vaccines for COVID-19 are being studied, and several studies have reported the results of these vaccines. We aimed to review the current evidence of the feasibility and effectiveness of Vaccines for COVID-19. Methods: A search was carried out utilizing the keywords in the online databases, including Scopus,Web of Science, PubMed, Embase, and Cochrane. We included both human and non-human studies because of the vaccine novelty, which could limit our ability to include sufficient human studies. Results: The review of studies showed that several SARS-CoV-2 vaccines are under development; different platforms are being used, including eight vaccines are adenovirus-based vectors, six vaccines are RNA-based formulations, one vaccine is DNA-based formulations, and other vaccines are using other platforms, including lipid nano particles. Conclusion: It is crucial to gather as much clinically relevant evidence as possible regarding the immunogenicity, efficacy, and safety profiles of these vaccines and adhere wisely to CDC protocols and guidelines of vaccine production.