No Arabic abstract
Lockdowns imposed in most of the countries were lifted following a decline in the COVID-19 cases towards May-June 2020. A recent surge (second wave) in the COVID-19 cases in Europe and other temperate countries as compared to the tropical regions suggests the likely role of solar radiation. We hypothesized that ultraviolet radiations effect might be a significant factor moderating the spread of the COVID-19 across countries. Regression analysis was done for the UV radiation data for seven hotspot cities (New Delhi, Mumbai, Milan, Madrid, New York, Melbourne and Sydney) with the daily COVID-19 cases. Global erythemal UV radiation values were lower during winter and higher during summer. In general, the daily new COVID-19 cases registered were higher during the winter months having low UV radiation dose (0.5-3.7 kJ m-2). Cases began to decline with summer onset that corresponded to increased UV radiation (2.5-6.7 kJ m-2). Our studies suggest that the natural UV radiation could be a strong determining factor moderating the spread of COVID-19 cases. The importance of UV radiation in natural sunlight as a disinfectant for SARS-CoV-2 cannot be ignored since the lockdowns were lifted; further, it can be considered as a factor for COVID management.
The genomic ssRNA of coronaviruses is packaged within a helical nucleocapsid. Due to transitional symmetry of a helix, weakly specific cooperative interaction between ssRNA and nucleocapsid proteins leads to the natural selection of specific quasi-periodic assembly/packaging signals in the related genomic sequence. Such signals coordinated with the nucleocapsid helical structure were detected and reconstructed in the genomes of the coronaviruses SARS-CoV and SARS-CoV-2. The main period of the signals for both viruses was about 54 nt, that implies 6.75 nt per N protein. The complete coverage of ssRNA genome of length about 30,000 nt by the nucleocapsid would need 4,400 N proteins, that makes them the most abundant among the structural proteins. The repertoires of motifs for SARS-CoV and SARS-CoV-2 were divergent but nearly coincided for different isolates of SARS-CoV-2. We obtained the distributions of assembly/packaging signals over the genomes with non-overlapping windows of width 432 nt. Finally, using the spectral entropy, we compared the load from point mutations and indels during virus age for SARS-CoV and SARS-CoV-2. We found the higher mutational load on SARS-CoV. In this sense, SARS-CoV-2 can be treated as a newborn virus. These observations may be helpful in practical medical applications and are of basic interest.
While the SARS-CoV-2 keeps spreading world-wide, comparing its evolution across different nations is a timely challenge of both theoretical and practical importance. The large variety of dissimilar and country-dependent epidemiological factors, in fact, makes extremely difficult to understand their influence on the epidemic trends within a unique and coherent framework. We present a geometric framework to characterize, in an integrated and low-dimensional fashion, the epidemic plume-like trajectories traced by the infection rate, $I$, and the fatality rate, $D$, in the $(I,D)$ plane. Our analysis enables the definition of an epidemiometric system based on three geometric observables rating the SARS-CoV-2 pandemic events via scales analogous to those for the magnitude and the intensity of seismic events. Being exquisitely geometric, our framework can be applied to classify other epidemic data and secondary waves, raising the possibility of designing epidemic alerts or early warning systems to enhance public and governmental responses to a rapidly emerging outbreak.
The coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, has caused 60 millions of infections and 1.38 millions of fatalities. Genomic analysis of SARS-CoV-2 can provide insights on drug design and vaccine development for controlling the pandemic. Inverted repeats in a genome greatly impact the stability of the genome structure and regulate gene expression. Inverted repeats involve cellular evolution and genetic diversity, genome arrangements, and diseases. Here, we investigate the inverted repeats in the coronavirus SARS-CoV-2 genome. We found that SARS-CoV-2 genome has an abundance of inverted repeats. The inverted repeats are mainly located in the gene of the Spike protein. This result suggests the Spike protein gene undergoes recombination events, therefore, is essential for fast evolution. Comparison of the inverted repeat signatures in human and bat coronaviruses suggest that SARS-CoV-2 is mostly related SARS-related coronavirus, SARSr-CoV/RaTG13. The study also reveals that the recent SARS-related coronavirus, SARSr-CoV/RmYN02, has a high amount of inverted repeats in the spike protein gene. Besides, this study demonstrates that the inverted repeat distribution in a genome can be considered as the genomic signature. This study highlights the significance of inverted repeats in the evolution of SARS-CoV-2 and presents the inverted repeats as the genomic signature in genome analysis.
One year after the onset of the COVID-19 pandemic, the origin of SARS-CoV-2 still eludes humanity. Early publications firmly stated that the virus was of natural origin, and the possibility that the virus might have escaped from a lab was discarded in most subsequent publications. However, based on a re-analysis of the initial arguments, highlighted by the current knowledge about the virus, we show that the natural origin is not supported by conclusive arguments, and that a lab origin cannot be formally discarded. We call for an opening of peer-reviewed journals to a rational, evidence-based and prejudice-free evaluation of all the reasonable hypotheses about the virus origin. We advocate that this debate should take place in the columns of renowned scientific journals, rather than being left to social media and newspapers.
A number of epidemics, including the SARS-CoV-1 epidemic of 2002-2004, have been known to exhibit superspreading, in which a small fraction of infected individuals is responsible for the majority of new infections. The existence of superspreading implies a fat-tailed distribution of infectiousness (new secondary infections caused per day) among different individuals. Here, we present a simple method to estimate the variation in infectiousness by examining the variation in early-time growth rates of new cases among different subpopulations. We use this method to estimate the mean and variance in the infectiousness, $beta$, for SARS-CoV-2 transmission during the early stages of the pandemic within the United States. We find that $sigma_beta/mu_beta gtrsim 3.2$, where $mu_beta$ is the mean infectiousness and $sigma_beta$ its standard deviation, which implies pervasive superspreading. This result allows us to estimate that in the early stages of the pandemic in the USA, over 81% of new cases were a result of the top 10% of most infectious individuals.