• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

How can Data Science be Instrumental in Combating Corona Outbreak?

Sai Sharma / 3 min read.
March 19, 2020
Datafloq AI Score
×

Datafloq AI Score: 52

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/wL6pX

171,909 Cases; 6,351 Deaths; 77,783 Recoveries.

These are some metrics as on March 16, 2020, of Coronavirus Outbreak that began its rampage on the last day of 2019 and brought the world into a frenzy in less than three months.

In the 2020s, to better combat this global health emergency we can understand the spread of COVID-19 with the arsenal of new-age data-driven techniques.

From supply chains to consumption patterns, the virus has affected everybody down to the lowest common denominator. Machine learning and data engineering can be leveraged to analyze news reports and social posts, information coordination can be made better, and predictions can be made.

It is critical to determine where the virus would surface in order to block its spread effectively. We are trying to understand how is the virus interacting with the population at large.

~BlueDot, a company running AI and data-driven surveillance for COVID-19

How can AI, data science and machine learning be instrumental?

Is the virus more prevalent in certain areas than in others, and why? Is the spread only correlated to the primary sources (directly coming from infected countries) and secondary cases (people primary sources are coming in contact with) or there is more to the story?

What are the trends witnessed globally in the case of community spread?

These and many more questions can be answered by data visualization and interpretation. AI and supercomputers are using big data on the virus to develop a vaccine (with major companies like Tencent, DiDi, and Huawei involved in the research). Data science techniques can approach the problem of such magnitude and suggest combat strategies. Let’s see how.

Handling the crisis with data science

Data Science can be used in multifaced ways to track and forecast outbreaks; in testing; process healthcare claims, using robots in sterilization and food supplies, determining non-compliance to government and health advisory, using chatbots to share information.

To these goals, the data science industry can go about the problem through three methods.


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

First, by understanding the problem. Followed by taking the action. Finally, prevention.

First Phase: Understand the problem

This involves extracting as much information as possible about the virus and understanding it through data visualization techniques, GIS techniques, and graph analysis. The analysis will become fundamental to the next steps to take.

Some answers to dig for include: Where are the outbreaks? How fast is it spreading? How many have become sick? What are the demographics of those infected? Which areas have been most successful in diagnosing and handling its spread? Etc.

Data Visualization, GIS Mapping, and Network Mapping are few techniques that can aid data engineering in this phase.

Second Phase: Action

Based on the information collected and analyzed, determine which training models should be deployed to take action? Which applications should be used?

It can be complicated to determine with success which actions to take. Choose and deploy models based on their scalability, effectiveness, and speed. Since a system that can respond to such a massive phenomenon needs to be able to hand data with high concurrence levels.

Third Phase: Prevention

If and when we manage to contain the pandemic, it is important to prepare for the future. Keep the pulse of best practices, its likely occurrence (if at all) again, and augmenting preparation levels to deal with the crisis.

One of the major challenges that would also emerge is related to the privacy of data infrastructure, an issue pervasive in data engineering and data analysis.

Despite the international community coming together, obtaining relevant information about the virus is still a challenge.

Although it is not expected to be contained in the short-term, making efforts and becoming better prepared than before is the least any community can do. It, even more, applies to data science pros, the mavens of information.

Categories: Big Data
Tags: bad data, big data technology, technology

About Sai Sharma

Writer, Business strategist, AI Geek

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!