Prevalence and effect of bacterial co-infections on clinical outcomes in hospitalized COVID-19 patients at a tertiary care centre of India (preprint)

Background Bacterial co-infections are a leading cause of morbidity and mortality during viral infections including COVID-19. Systematic testing of COVID-19 patients having bacterial co-infections is essential to select the correct antibiotic for treatment in order to reduce mortality and also prevent spread of antimicrobial resistance (AMR). The present study aims to evaluate the prevalence, demographic parameters, antibiotic sensitivity patterns and outcomes in hospitalized COVID-19 patients with bacterial co-infections. Methods A total of 1019 COVID-19 patients were selected for the study. We analyzed the prevalence, antibiotic sensitivity pattern and clinical outcomes in COVID-19 patients having bacterial co-infections. Results Out of a total 1019 COVID-19 patients screened, 5.2% of patients demonstrated clinical signs of bacterial co-infection. Bacteremia was found in majority of the patients followed by respiratory and urinary infections. Escherichia coli, Pseudomonas aeruginosa and Klebsiella spp . were most common isolates among the Gram-negative and Coagulase-negative Staphylococci (CONS) and Staphylococcus aureus among the Gram-positive bacterial infections. Antibiotic sensitivity profiling revealed that colistin, imipenem and fosfomycin were the most effective drugs against the Gram-negative isolates while vancomycin, teicoplanin and doxycycline against the Gram-positive isolates. Analysis of clinical outcomes revealed that the mortality rate was higher (39%) among the patients with bacterial co-infections as compared to the group without co-infection (17%). Conclusions This study reveals that the rate of bacterial co-infections is significantly increasing among COVID-19 patients and leading to increase in mortality. Systematic testing of bacterial co-infections is therefore essential in COVID-19 patients for better clinical outcomes and to reduce AMR.

Severe Acute Respiratory Syndrome Coronavirus-2 genome sequence variations relate to morbidity and mortality in Coronavirus Disease-19 (preprint)

Outcome of infection with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) may depend on the host, virus or the host-virus interaction related factors. Complete SARS-CoV-2 genome was sequenced using Illumina and Nanopore platforms from naso-/oro-pharyngeal ri-bonucleic acid (RNA) specimens from COVID-19 patients of varying severity and outcomes, including patients with mild upper respiratory symptoms (n=35), severe disease admitted to intensive care with respiratory and gastrointestinal symptoms (n=21), fatal COVID-19 outcome (n=17) and asymptomatic (n=42). Of a number of genome variants observed, p.16L>L (Nsp1), p.39C>C (Nsp3), p.57Q>H (ORF3a), p.71Y>Y (Membrane glycoprotein), p.194S>L (Nucleocapsid protein) were observed in similar frequencies in different patient subgroups. However, seventeen other variants were observed only in symptomatic patients with severe and fatal COVID-19. Out of the latter, one was in the 5UTR (g.241C>T), eight were synonymous (p.14V>V and p.92L>L in Nsp1 protein, p.226D>D, p.253V>V, and p.305N>N in Nsp3, p.34G>G and p.79C>C in Nsp10 protein, p.789Y>Y in Spike protein), and eight were non-synonymous (p.106P>S, p.157V>F and p.159A>V in Nsp2, p.1197S>R and p.1198T>K in Nsp3, p.97A>V in RdRp, p.614D>G in Spike protein, p.13P>L in nucleocapsid). These were completely absent in the asymptomatic group. SARS-CoV-2 genome variations have a significant impact on COVID-19 presentation, severity and outcome.

Development of RNA-based assay for rapid detection of SARS-CoV-2 in clinical samples (preprint)

The ongoing spread of pandemic coronavirus disease (COVID-19) is caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). In the lack of specific drugs or vaccines for SARS-CoV-2, demands rapid diagnosis and management are crucial for controlling the outbreak in the community. Here we report the development of the first rapid-colorimetric assay capable of detecting SARS-CoV-2 in the human nasopharyngeal RNA sample in less than 30 minutes. We utilized a nanomaterial-based optical sensing platform to detect RNA-dependent RNA polymerase (RdRp) gene of SARS-CoV-2, where the formation of oligo probe-target hybrid led to salt-induced aggregation and changes in gold-colloid color from pink to blue in visible range. Accordingly, we found a change in colloid color from pink to blue in assay containing nasopharyngeal RNA sample from the subject with clinically diagnosed COVID-19 (n=18). The colloid retained pink color when the test includes samples from COVID-19 negative subjects (n=18) or human papillomavirus (HPV) infected women (n=2). The optimized method has detection limit as little as 0.5 ng of SARS-CoV-2 RNA. Overall, the developed assay rapidly detects SARS-CoV-2 RNA in clinical samples in a cost-effective manner and would be useful in pandemic management by facilitating mass screening. DisclosureA patent application has been filed (ref#202011018132) on subject matter described in the publication.

Pandemic Coronavirus Disease (COVID-19): Challenges and A Global Perspective (preprint)

The technology-driven world of the 21st century is currently confronted with a major threat to humankind in the form of the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of April 22, 2020, COVID-19 has claimed 169, 006 human lives and had spread to over 200 countries with more than 2,471,136 confirmed cases. The perpetually increasing figures associated with COVID-19 are disrupting the social and economic systems globally. The losses are unmatched and significantly higher compared to those from previously encountered pathogenic infections. Previously, two CoVs (SARS-CoV and Middle East respiratory syndrome-CoV) affected the human population in 2002 and 2012 in China and Saudi Arabia, respectively. Based on genomic similarities, animal-origin CoVs, primarily those infecting bats, civet cats, and pangolins, were presumed to be the source of emerging human CoVs, including the SARS-CoV-2. The cohesive approach amongst virologists, bioinformaticians, big data analysts, epidemiologists, and public health researchers across the globe has delivered high-end viral diagnostics. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. The rapidly evolving and popular technology of artificial intelligence played a major role in confirming and countering the COVID-19 pandemic using digital technologies and mathematical algorithms. In this review, we discuss the noteworthy advancements in the mitigation of the COVID-19 pandemic, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology, animal reservoirs, laboratory animal models, disease transmission, diagnosis using artificial intelligence interventions, therapeutics and vaccines, and disease mitigation measures to combat disease dissemination.