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Genomic diversity and evolution, diagnosis, prevention, and therapeutics of the pandemic COVID-19 disease.

ABSTRACT: The coronavirus disease 19 (COVID-19) is a highly transmittable and pathogenic viral infection caused by a novel evolutionarily divergent RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, China in December 2019, and subsequently spreaded around the world. Genomic analyses revealed that this zoonotic virus may be evolved naturally but not a purposefully manipulated laboratory construct. However, currently available data are not sufficient to precisely conclude the origin of this fearsome virus. Comprehensive annotations of the whole-genomes revealed hundreds of nucleotides, and amino acids mutations, substitutions and/or deletions at different positions of the ever changing SARS-CoV-2 genome. The spike (S) glycoprotein of SARS-CoV-2 possesses a functional polybasic (furin) cleavage site at the S1-S2 boundary through the insertion of 12 nucleotides. It leads to the predicted acquisition of 3-O-linked glycan around the cleavage site. Although real-time RT-PCR methods targeting specific gene(s) have widely been used to diagnose the COVID-19 patients, however, recently developed more convenient, cheap, rapid, and specific diagnostic tools targeting antigens or CRISPR-Cas-mediated method or a newly developed plug and play method should be available for the resource-poor developing countries. A large number of candidate drugs, vaccines and therapies have shown great promise in early trials, however, these candidates of preventive or therapeutic agents have to pass a long path of trials before being released for the practical application against COVID-19. This review updates current knowledge on origin, genomic evolution, development of the diagnostic tools, and the preventive or therapeutic remedies of the COVID-19. We also discussed the future scopes for research, effective management, and surveillance of the newly emerged COVID-19 disease.

SUBMITTER: Hoque MN

PROVIDER: S-EPMC7510477 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Genomic diversity and evolution, diagnosis, prevention, and therapeutics of the pandemic COVID-19 disease.

Hoque M Nazmul MN Chaudhury Abed A Akanda Md Abdul Mannan MAM Hossain M Anwar MA Islam Md Tofazzal MT

PeerJ 20200901

The coronavirus disease 19 (COVID-19) is a highly transmittable and pathogenic viral infection caused by a novel evolutionarily divergent RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, China in December 2019, and subsequently spreaded around the world. Genomic analyses revealed that this zoonotic virus may be evolved naturally but not a purposefully manipulated laboratory construct. However, currently available data are not sufficie ...[more]

PMID: 33005486

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Project description:Epidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ([Formula: see text]). The relationship between public health interventions and [Formula: see text] was explored, firstly using a hierarchical clustering algorithm on initial [Formula: see text] patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, [Formula: see text], and daily incidence counts in subsequent months. The impact of updating [Formula: see text] every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future [Formula: see text] (75 days lag), while a lower [Formula: see text] was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated [Formula: see text] produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when [Formula: see text] was kept constant. Monitoring the evolution of [Formula: see text] during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated [Formula: see text] values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of [Formula: see text] over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

Dataset Information

Genomic diversity and evolution, diagnosis, prevention, and therapeutics of the pandemic COVID-19 disease.

Publications

Genomic diversity and evolution, diagnosis, prevention, and therapeutics of the pandemic COVID-19 disease.

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