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

School of Engineering, MIT ADT University, Pune.

Madhulika Bhati

CSIR-National Institute of Science, Technology & Development Studies,

Multiple version iconThere are 2 versions of this paper

Date Written: April 20, 2020

Abstract

The coronavirus outbreak (nCoV) has created an alarming situation at international level. COVID-19 pandemic is now continuing to develop and researchers across the world are working to combat with COVID-19 & to reduce and prevent its spread. Pathological tests are used to detect whether patient is corona positive or not but they are time consuming & also number of test kits & centers are limited. Surprising thing is 60% patients may not have any symptoms but still they are SARS-CoV-2 positive & may work as silent carrier causing outbreak of this disease. And a reason to worry is that yet there is no vaccine & exact drug for this disease.

Clinical data related to patient’s medical history, geographical location & symptoms can be analyzed using machine learning techniques to predict clinical outcomes. But as symptoms vary from person-to-person & are common in other diseases like flu, swine flu & pneumonia therefore accuracy of clinical outcomes is questionable. To tackle this problem, this paper proposes a technique to detect presence of SARS-CoV-2 in a person using genome sequencing of virus. This will accurately help to detect presence of virus, to develop targeted therapies & vaccines and also to learn how patient will respond to drugs. This paper summarizes primary survey of existing work & discusses a methodology to detect. Thus proposed methodology can be used by doctors & practitioners as a tool for making ease in decision making.

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

JEL Classification: I1, I14, I10

Suggested Citation

Bhonde, Swati and Prasad, Jayashree Rajesh and Bhati, Madhulika, Predictive Analytics to Combat with COVID-19 using Genome Sequencing (April 20, 2020). Available at SSRN: https://ssrn.com/abstract=3580656 or http://dx.doi.org/10.2139/ssrn.3580656

Swati Bhonde (Contact Author)

Smt. Kashibai Navale College of Engineering ( email )

Pune, Maharashtra
India
9960263614 (Phone)

Jayashree Rajesh Prasad

School of Engineering, MIT ADT University, Pune. ( email )

Railway station, Solapur - Pune Hwy, near Bharat P
Pune., MA Maharashtra 412201
India

HOME PAGE: http://https://mituniversity.edu.in/

Madhulika Bhati

CSIR-National Institute of Science, Technology & Development Studies, ( email )

Pusa Gate
KS Krishnan Marg
New Delhi, 110012
India
7042350914 (Phone)

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