ABSTRACT
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that causes coronavirus disease 2019 (COVID-19) is a public health problem and may have co-infection with other pathogens such as influenza virus.This study aims to assess the co-infection of SARS-CoV-2 with influenza among COVID-19 cases.The all relevant studies were collected from international databases. For improving the quality of the present literature, the all studies were evaluated by two reviewers in order to confirm all of the studies have inclusion criteria. Finally, all articles with sufficient quality scores were included in meta-analysis. Assessment of heterogeneity among the studies of primary studies was performed using the statistic chi‐squared test (Cochran’s Q) and I2 index. In this results, random or fixed effect model were used for determination of heterogeneity test. All statistical analyses were performed using Comprehensive Meta-Analysis (CMA), V.2 software.This meta- analysis included 9 primary studies investigating the co-infection of SARS-CoV-2 with influenza among COVID-19 cases. Pooled prevalence (95% confidence interval) of co-infection is shown that the prevalence of influenza A is higher than influenza B. 2.3(0.5-9.3) vs 0.1 (0.4-3.3). Using the fixed effect model the frequency of fever was (80.6% [95% CI 76.1–84.40, p < 0.153]) and it is shown that fever is the most prevalent symptom in patients.Patients admitted to hospital with COVID-19 also infected with influenza virus. Thus, the current research provides a better understanding about the control and treatment of co-infection with SARS-CoV-2 and the influenza virus.
Subject(s)
Coronavirus Infections , Coinfection , Fever , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
SARS-CoV-2(COVID-19) currently is the main cause of the severe acute respiratory disease and fatal outcomes in human beings worldwide. Several genes are used as targets for the detection of SARS-CoV-2, including the RDRP, N, and E genes. The present study aimed to determine the RDRP, N, and E genes expressions of SARS-CoV- 2 in clinical samples. For this purpose, 100 SARS-CoV-2 positive samples were collected from diagnostic laboratories of Mazandaran province, Iran. After RNA extraction, the real time RT-PCR assay was performed for differential gene expressions’ analysis of N, E, and RDRP. The CT values for N, RDRP, and E targets of 100 clinical samples for identifying SARS-CoV-2 were then evaluated using qRT-PCR. This result suggests N gene as a potential target for the detection of the SARS‐CoV‐2, since it was observed to be highly expressed in the nasopharyngeal or oropharynges of COVID-19 patients (P < 0.0001). Herein, we showed that SARS-CoV- 2 genes were differentially expressed in the host cells. Therefore, to reduce obtaining false negative results and to increase the sensitivity of the available diagnostic tests, the target genes should be carefully selected based on the most expressed genes in the cells.
Subject(s)
Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The high mutation rate of RNA viruses causes genetic variation, virus evolution and it is a strategy to escape the immune system. In the present study, all researches and evidence were extracted from the available online national databases. Two researchers randomly evaluated the assessment of the research sensitivity. Finally, after quality assessment and specific inclusion and exclusion criteria, the eligible articles were entered for meta-analysis. The heterogeneity between the results of studies was measured using test statistic (Cochran's Q) and I2 index. The forest plots illustrated the point and pooled estimates with 95% confidence intervals (crossed lines). All statistical analyses were performed using Comprehensive meta-Analysis V.2 software.This meta-analysis included 13 primary studies investigating the SARS-CoV-2 genetic variations and mutations in the COVID-19 genomic sequence. According to the pooled prevalence (95% confidence interval) of mutations, the spike gene variations showed the highest non-synonymous mutation frequency (16.4%, CI: 13.6, 16.6) and the Non-structural protein (NSP) genes possess the highest mutation frequency among total mutations (31.6%, CI: 21, 44.6). Genomic mutation analysis of SARS-CoV-2 strains may provide knowledge about different biological infrequent mutations and their relationships of viral transmission, pathogenicity, infectivity, and fatality rates between SARS-CoV-2 and human cells.