A Generalized Overview of SARS-CoV-2: Where Does the Current Knowledge Stand?

Ullah, Md. Asad; Islam, Hiya; Rahman, Ahsab; Masud, Jaasia; Shweta, Dipita Saha; Araf, Yusha; Sium, Syed Muktadir Al; Sarkar, Bishajit

doi:10.29333/ejgm/8258

Cited by 18 publications

(12 citation statements)

References 172 publications

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“…The coronavirus disease-2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which was first reported in December 2019 in Wuhan, People's Republic of China. To date, the spread of this disease has been extremely rapid throughout the world (1), and the World Health Organization (WHO) declared COVID-19 as a Public Health Emergency on January 30, 2020. By March 11, 2020, COVID-19 was declared as a global pandemic by the WHO, and has since continued to spread at an accelerated rate.…”

Section: Introductionmentioning

confidence: 99%

Potential Effects of the COVID-19 Pandemic on Future Birth Rate

Ullah

Moin

Araf

et al. 2020

Front. Public Health

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Here, we examine the potential effect of the COVID-19 pandemic on future birth rates. This highly contagious disease originated in China, and rapidly spread worldwide, leading to extensive lockdown policies being implemented globally with the aim of containing the infection rates and its serious attendant consequences. Based on previous extant literature, this paper overviews the potential demographic consequences of the current progressively widespread epidemic on conception and fertility as driven by the data obtained during similar prior incidents. In general, epidemics manifest a common pattern as far as their impact on population, which is remarkably similar to natural disasters, i.e., a steep decline in birth rates followed by gradual increases and then followed by a baby boom. Additionally, we have also depicted how economic conditions, mental health, fear, and mortality may also influence future birth rates.

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Section: Introductionmentioning

confidence: 99%

Potential Effects of the COVID-19 Pandemic on Future Birth Rate

Ullah

Moin

Araf

et al. 2020

Front. Public Health

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“…Female isolates excavated according to country (number of sequence, state(s) extracted), include: Algeria (1, 1); Benin (4, 1); DRC (13,4); Egypt (4, 2); Gambia (4, 2); Ghana (4, 1); Kenya (4, 1); Madagascar (2, 2); Mali (4, 1); Morocco (2, 1); Nigeria (11,5); Senegal (11,3); South Africa (80, 24); Tunisia (1, 1). Hence, a total of 290 genome sequences (145 males, 145 females) with genome lengths of over 29000 nucleotides, were excavated.…”

Section: Data Source and Genome Sequences Selectionmentioning

confidence: 99%

Real Time Viral Sub-Strains Discovery in Emerging Infectious Disease Situation – The African Perspective

Ekpenyong

Uzoka

Edoho

et al. 2021

Preprint

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Background: The increased number of accessible genomes has prompted large-scale comparative studies for decerning evolutionary knowledge of infectious diseases, but challenges such as non-availability of close reference sequence(s), incompletely assembled or large number of genomes, preclude real time multiple sequence alignment and sub-strain(s) discovery. This paper introduces a cooperatively inspired open-source framework, for intelligent mining of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genomes. We situate this study within the African context, to drive advancement on state-of-the-art, towards intelligent infectious disease characterization and prediction. The outcome is an enriched Knowledge Base, sufficient to provide deep understanding of the viral sub-strains’ identification problem. We also open investigation by gender, which to the best of our knowledge has been ignored in related research. Data for the study came from the Global Initiative on Sharing All Influenza Data database (https://gisaid.org) and processed for precise discovery of viral sub-strains transmission between and within African countries. To localize the transmission route(s) of each isolate excavated and provide appropriate links to similar isolate strain(s), a cognitive solution was imposed on the genome expression patterns discovered by unsupervised self-organizing map (SOM) component planes visualization. The Freidman-Nemenyi’s test was finally performed to validate our claim. Results: Evidence of inter- and intra-genome diversity was noticed. While some isolates (or genomes) clustered differently, implying different evolutionary source (or high-diversity), others clustered closely together, indicating similar evolutionary source (or less-diversity). SOM component planes analysis revealed multiple sub-strains patterns, strongly suggesting local- or intra-community and country to country transmissions. Cognitive maps of both male and female isolates revealed multiple transmission routes. Freidman’s test results showed highly significant difference (p<0.01) among the various isolate groups. Nemenyi’s test revealed groups that differed in their isolates.Conclusion: The proposed framework offers explanations to SARS-CoV-2 diversity and provides real time identification to disease transmission routes, as well as rapid decision support for facilitating inter- and intra-country contact tracing of infected case(s). Intermediate data produced in this paper are helpful to enrich the genome datasets for intelligent characterization and prediction of COVID-19 and related pandemics, as well as the construction of intelligent device for accurate infectious disease monitoring.

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“…Male isolates excavated according to Country (number of sequence, state(s) extracted), include: Algeria (2, 1); Benin (5, 2); Cameroon (1, 1); DRC (15,4); Egypt (5, 2); Gambia (6, 2); Ghana (4, 1); Kenya (4, 1); Mali (5, 2); Morocco (5, 3); Nigeria (13,5); Senegal (14,6); South Africa (65,20); Tunisia (1, 1). Female isolates excavated according to country (number of sequence, state(s) extracted), include: Algeria (1, 1); Benin (4, 1); DRC (13,4); Egypt (4, 2); Gambia (4, 2); Ghana (4, 1); Kenya (4, 1); Madagascar (2, 2); Mali (4, 1); Morocco (2, 1); Nigeria (11,5); Senegal (11,3); South Africa (80, 24); Tunisia (1, 1). Hence, a total of 290 genome sequences (145 males, 145 females) with genome lengths of over 29000 nucleotides, were excavated.…”

Section: Data Source and Genome Sequences Selectionmentioning

confidence: 99%

Real Time Viral Sub-Strains Discovery in Emerging Infectious Disease Situation – The African Perspective

Ekpenyong¹,

Uzoka²,

Edoho³

et al. 2020

Preprint

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BackgroundThe increased number of accessible genomes has prompted large-scale comparative studies for decerning evolutionary knowledge of infectious diseases, but challenges such as non-availability of close reference sequence(s), incompletely assembled or large number of genomes, preclude real time multiple sequence alignment and sub-strain(s) discovery. This paper introduces a cooperatively inspired open-source framework, for intelligent mining of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genomes. We situate this study within the African context, to drive advancement on state-of-the-art, towards intelligent infectious disease characterization and prediction. The outcome is an enriched Knowledge Base, sufficient to provide deep understanding of the viral sub-strains’ identification problem. We also open investigation by gender, which to the best of our knowledge has been ignored in related research. Data for the study came from the Global Initiative on Sharing All Influenza Data database (https://gisaid.org) and processed for precise discovery of viral sub-strains transmission between and within African countries. To localize the transmission route(s) of each isolate excavated and provide appropriate links to similar isolate strain(s), a cognitive solution was imposed on the genome expression patterns discovered by unsupervised self-organizing map (SOM) component planes visualization. The Freidman-Nemenyi’s test was finally performed to validate our claim.ResultsEvidence of inter- and intra-genome diversity was noticed. While some isolates (or genomes) clustered differently, implying different evolutionary source (or high-diversity), others clustered closely together, indicating similar evolutionary source (or less-diversity). SOM component planes analysis revealed multiple sub-strains patterns, strongly suggesting local or intra-community and country to country transmissions. Cognitive maps of both male and female isolates revealed multiple transmission routes. Statistical results indicate significant difference between the various isolate groups at the 0.05 level of significance.ConclusionThe proposed framework offers explanations to SARS-CoV-2 diversity and provides real time identification to disease transmission routes, as well as rapid decision support for facilitating inter- and intra-country contact tracing of infected case(s). Intermediate data produced in this paper are helpful to enrich the genome datasets for intelligent characterization and prediction of COVID-19 and related pandemics, as well as the construction of intelligent device for accurate infectious disease monitoring.

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A Generalized Overview of SARS-CoV-2: Where Does the Current Knowledge Stand?

Cited by 18 publications

References 172 publications

Potential Effects of the COVID-19 Pandemic on Future Birth Rate

Potential Effects of the COVID-19 Pandemic on Future Birth Rate

Real Time Viral Sub-Strains Discovery in Emerging Infectious Disease Situation – The African Perspective

Real Time Viral Sub-Strains Discovery in Emerging Infectious Disease Situation – The African Perspective

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