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.

BACKGROUND There is recently a concern regarding the reinfection and reactivation of previously reCoVered coronavirus disease 2019 (CoVID-19) patients. AIM To summarize the recent findings and reports of CoVID-19 reinfection in patients previously reCoVered from the disease. METHODS This study was a systematic review of current evidence conducted in August 2020. The authors studied the probable reinfection risk of novel coronavirus (CoVID-19). We performed a systematic search using the keywords in online databases. The investigation adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to ensure the reliability and validity of this study and results. RESULTS We reviewed 31 studies. Eight studies described reCoVered patients with reinfection. Only one study reported reinfected patients who died. In 26 studies, there was no information about the status of the patients. Several studies indicated that reinfection is not probable and that post-infection immunity is at least temporary and short. CONCLUSION Based on our review, we concluded that a positive polymerase chain reaction retest could be due to several reasons and should not always be considered as reinfection or reactivation of the disease. Most relevant studies in positive retest patients have shown relative and probably temporary immunity after the reCoVery of the disease.

Introduction Coronavirus Disease-2019 (SARS-CoV-2) started its devastating trajectory into a global pandemic in Wuhan, China, in December 2019. Ever since, several variants of SARS-CoV-2 have been identified. In the present review, we aimed to characterize the different variants of SARS-CoV-2 and explore the related morbidity and mortality. Methods A systematic review including the current evidence related to different variants of SARS-CoV-2 and the related morbidity and mortality was conducted through a systematic search utilizing the keywords in the online databases including Scopus, PubMed, Web of Science, and Science Direct; we retrieved all related papers and reports published in English from December 2019 to September 2020. Results A review of identified articles has shown three main genomic variants, including type A, type B, and type C. we also identified three clades including S, V, and G. Studies have demonstrated that the C14408T and A23403G alterations in the Nsp12 and S proteins are the most prominent alterations in the world, leading to life-threatening mutations.The spike D614G amino acid change has become the most common variant since December 2019. From missense mutations found from Gujarat SARS-CoV-2 genomes, C28854T, deleterious mutation in the nucleocapsid (N) gene was significantly associated with patients' mortality. The other significant deleterious variant (G25563T) is found in patients located in Orf3a and has a potential role in viral pathogenesis. Conclusion Overall, researchers identified several SARS-CoV-2 variants changing clinical manifestations and increasing the transmissibility, morbidity, and mortality of COVID-19. This should be considered in current practice and interventions to combat the pandemic and prevent related morbidity and mortality.

Introduction: Patients with COVID-19 may present different viral loads levels. However, the relationship between viral load and disease severity in COVID-19 is still unknown. Therefore, this study aimed to systematically review the association between SARS-CoV-2 viral load and COVID-19 severity. Methods: The relevant studies using the keywords of "COVID-19" and "viral load" were searched in the databases of PubMed, Scopus, Google Scholar, and Web of Science. A two-step title/abstract screening process was carried out and the eligible studies were included in the study. Results: Thirty-four studies were included from the initial 1015 records. The vast majority of studies have utilized real-time reverse transcriptionpolymerase chain reaction of the nasopharyngeal/respiratory swabs to report

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.