Predictive Analytics to Combat with COVID-19 using Genome Sequencing

18 Pages Posted: 21 Apr 2020 Last revised: 11 May 2020

See all articles by Swati Bhonde

Swati Bhonde

Smt. Kashibai Navale College of Engineering

Jayashree Prasad

Sinhgad College of Engineering, Vadgaon, Pune.

Madhulika Bhati

CSIR-National Insitute of Science, Technology and Development Studies

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Date Written: April 15, 2020

Abstract

The coronavirus outbreak (nCoV) has created an alarming situation at the international level.

COVID-19 pandemic is now continuing to develop and researchers across the world are working to combat COVID-19 and to reduce and prevent its spread. Traditional pathological tests are used but they are time-consuming & also the number of test kits & centers is limited. Surprising thing is 60% of patients may not have any symptoms but still, they are SAR-CoV-2 positive & may work as silent carriers causing an outbreak of this disease. And a reason to worry is that there is no vaccine & exact drug for this disease.

Machine learning techniques can be used to analyze clinical data but again symptoms vary from person-to-person & accuracy of clinical outcomes is questionable. To tackle this problem, this the paper proposes a technique to detect the presence of SAR-CoV-2 in a person using genome sequencing.

This will accurately help to detect the presence of the virus, to develop targeted therapies & vaccines and also to learn how the patient will respond to drugs. This paper summarizes the primary survey of existing work & proposes a technique using predictive analytics to detect the presence of SAR-CoV-2 using genome sequencing to combat COVID-19. This system will be able to differentiate SAR-CoV- 2 from its other subtypes, such as MERS-CoV, HCoV-NL63, HCoV-OC43, HCoV-229E, HCoV- HKU1, and SARS-CoV regardless of some missing information and noise in the dataset. Thus the proposed methodology can be used by doctors & practitioners as a tool for making ease in decision making.

Note: Funding: No Funding.

Conflict of Interest: Authors don't have any competing interest for publication of this work.

Keywords: COVID-19; machine learning; predictive analytics; genome sequencing SARS-CoV-2; India pandemic

Suggested Citation

Bhonde, Swati and Prasad, Jayashree Rajesh and Bhati, Madhulika, Predictive Analytics to Combat with COVID-19 using Genome Sequencing (April 15, 2020). Available at SSRN: https://ssrn.com/abstract=3580692 or http://dx.doi.org/10.2139/ssrn.3580692

Swati Bhonde

Smt. Kashibai Navale College of Engineering ( email )

Pune, Maharashtra
India
9960263614 (Phone)

Jayashree Rajesh Prasad

Sinhgad College of Engineering, Vadgaon, Pune. ( email )

Survey No 44/1, Vadgaon, Pune.
Pune., MA Maharashtra 411051
India
02024100000 (Phone)
411051 (Fax)

HOME PAGE: http://www.sinhgad.edu

Madhulika Bhati (Contact Author)

CSIR-National Insitute of Science, Technology and Development Studies ( email )

Dr. K.S. Krishnan Marg
PUSA Gate
New Delhi, IN 110012
India
110012 (Fax)

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