Model quantifies the impact of quarantine measures on Covid-19’s spread – MIT News
Posted: April 16, 2020 at 8:48 pm
The research described in this article has been published on a preprint server but has not yet been peer-reviewed by scientific or medical experts.
Every day for the past few weeks, charts and graphs plotting the projected apex of Covid-19 infections have been splashed across newspapers and cable news. Many of these models have been built using data from studies on previous outbreaks like SARS or MERS. Now, a team of engineers at MIT has developed a model that uses data from the Covid-19 pandemic in conjunction with a neural network to determine the efficacy of quarantine measures and better predict the spread of the virus.
Our model is the first which uses data from the coronavirus itself and integrates two fields: machine learning and standard epidemiology, explains Raj Dandekar, a PhD candidate studying civil and environmental engineering. Together with George Barbastathis, professor of mechanical engineering, Dandekar has spent the past few months developing the model as part of the final project in class 2.168 (Learning Machines).
Most models used to predict the spread of a disease follow what is known as the SEIR model, which groups people into susceptible, exposed, infected, and recovered. Dandekar and Barbastathis enhanced the SEIR model by training a neural network to capture the number of infected individuals who are under quarantine, and therefore no longer spreading the infection to others.
The model finds that in places like South Korea, where there was immediate government intervention in implementing strong quarantine measures, the virus spread plateaued more quickly. In places that were slower to implement government interventions, like Italy and the United States, the effective reproduction number of Covid-19 remains greater than one, meaning the virus has continued to spread exponentially.
The machine learning algorithm shows that with the current quarantine measures in place, the plateau for both Italy and the United States will arrive somewhere between April 15-20. This prediction is similar to other projections like that of the Institute for Health Metrics and Evaluation.
Our model shows that quarantine restrictions are successful in getting the effective reproduction number from larger than one to smaller than one, says Barbastathis. That corresponds to the point where we can flatten the curve and start seeing fewer infections.
Quantifying the impact of quarantine
In early February, as news of the virus troubling infection rate started dominating headlines, Barbastathis proposed a project to students in class 2.168. At the end of each semester, students in the class are tasked with developing a physical model for a problem in the real world and developing a machine learning algorithm to address it. He proposed that a team of students work on mapping the spread of what was then simply known as the coronavirus.
Students jumped at the opportunity to work on the coronavirus, immediately wanting to tackle a topical problem in typical MIT fashion, adds Barbastathis.
One of those students was Dandekar. The project really interested me because I got to apply this new field of scientific machine learning to a very pressing problem, he says.
As Covid-19 started to spread across the globe, the scope of the project expanded. What had originally started as a project looking just at spread within Wuhan, China grew to also include the spread in Italy, South Korea, and the United States.
The duo started modeling the spread of the virus in each of these four regions after the 500th case was recorded. That milestone marked a clear delineation in how different governments implemented quarantine orders.
Armed with precise data from each of these countries, the research team took the standard SEIR model and augmented it with a neural network that learns how infected individuals under quarantine impact the rate of infection. They trained the neural network through 500 iterations so it could then teach itself how to predict patterns in the infection spread.
Using this model, the research team was able to draw a direct correlation between quarantine measures and a reduction in the effective reproduction number of the virus.
The neural network is learning what we are calling the quarantine control strength function, explains Dandekar. In South Korea, where strong measures were implemented quickly, the quarantine control strength function has been effective in reducing the number of new infections. In the United States, where quarantine measures have been slowly rolled out since mid-March, it has been more difficult to stop the spread of the virus.
Predicting the plateau
As the number of cases in a particular country decreases, the forecasting model transitions from an exponential regime to a linear one. Italy began entering this linear regime in early April, with the U.S. not far behind it.
The machine learning algorithm Dandekar and Barbastathis have developed predictedthat the United States will start to shift from an exponential regime to a linear regime in the first week of April, with a stagnation in the infected case count likely betweenApril 15 and April20. It also suggests that the infection count will reach 600,000 in the United States before the rate of infection starts to stagnate.
This is a really crucial moment of time. If we relax quarantine measures, it could lead to disaster, says Barbastathis.
According to Barbastathis, one only has to look to Singapore to see the dangers that could stem from relaxing quarantine measures too quickly. While the team didnt study Singapores Covid-19 cases in their research, the second wave of infection this country is currently experiencing reflects their models finding about the correlation between quarantine measures and infection rate.
If the U.S. were to follow the same policy of relaxing quarantine measures too soon, we have predicted that the consequences would be far more catastrophic, Barbastathis adds.
The team plans to share the model with other researchers in the hopes that it can help inform Covid-19 quarantine strategies that can successfully slow the rate of infection.
View post:
Model quantifies the impact of quarantine measures on Covid-19's spread - MIT News
- Getting Started With Machine Learning: Definition and Applications - CMSWire - February 20th, 2021
- This Biotech Company Combines Single Cell Genomics with Machine Learning (ML) Algorithms To Enable High Resolution Profiling of the Immune System -... - February 20th, 2021
- Immunai Raises $60M to Decode the Immune System with Machine Learning and AI - AlleyWatch - February 20th, 2021
- Cloud Machine Learning Market: Indoor Applications Projected to be the Most Attractive Segment during 2021-2029 KSU | The Sentinel Newspaper - KSU |... - February 20th, 2021
- Machine Learning in Insurance Market: Indoor Applications Projected to be the Most Attractive Segment during 2021-2029 KSU | The Sentinel Newspaper -... - February 20th, 2021
- Carin Meier Using Machine Learning to Combat Major Illness, such as the Coronavirus - InfoQ.com - February 20th, 2021
- Moffitt Cancer Center: Why we are building the first machine learning department in oncology - The Cancer Letter - February 20th, 2021
- Machine Learning and where is it used? - Tech Guide - February 20th, 2021
- Artificial Intelligence and Machine Learning for Insurance Technology from Johnson Controls Available on the Ocean Tomo Bid-Ask Market - Yahoo Finance - February 20th, 2021
- Identifying COVID-19 Therapy Candidates With Machine Learning - Contagionlive.com - February 20th, 2021
- Machine Learning in Tax and Accounting Market gigantic revenues by 2028 with Amazon Web Services, Baidu Inc, Google, Intel, IBM, Hewlett Packard,... - February 20th, 2021
- Using AI and Machine Learning will increase in horti industry - hortidaily.com - February 13th, 2021
- The head of JPMorgan's machine learning platform explained what it's like to work there - eFinancialCareers - February 13th, 2021
- If you know nothing about deep learning with Python, start here - TechTalks - February 13th, 2021
- Mental health diagnoses and the role of machine learning - Health Europa - February 13th, 2021
- 5 Ways the IoT and Machine Learning Improve Operations - BOSS Magazine - February 13th, 2021
- There Is No Silver Bullet Machine Learning Solution - Analytics India Magazine - February 13th, 2021
- Postdoctoral Research Associate in Digital Humanities and Machine Learning job with DURHAM UNIVERSITY | 246392 - Times Higher Education (THE) - February 13th, 2021
- The Collision of AI's Machine Learning and Manipulation: Deepfake Litigation Risks to Companies from a Product Liability, Privacy, and Cyber... - February 13th, 2021
- Parascript and SFORCE Partner to Leverage Machine Learning Eliminating Barriers to Automation - GlobeNewswire - February 13th, 2021
- Rackspace Technology Study uncovers AI and Machine Learning knowledge gap in the UAE - Intelligent CIO ME - February 13th, 2021
- How Blockchain and Machine Learning Impact on education system - ABCmoney.co.uk - February 13th, 2021
- Mission Healthcare of San Diego Adopts Muse Healthcare's Machine Learning Tool - Southernminn.com - January 19th, 2021
- Deep Learning Outperforms Standard Machine Learning in Biomedical Research Applications, Research Shows - Georgia State University News - January 19th, 2021
- Project MEDAL to apply machine learning to aero innovation - The Engineer - January 19th, 2021
- Forecast On Machine Learning (ML) Intelligent Process Automation Market Witness the Growth of Great Billion by 2027 With Top Companies Like Automation... - January 19th, 2021
- Machine Learning Shown to Identify Patient Response to Sarilumab in Rheumatoid Arthritis - AJMC.com Managed Markets Network - January 19th, 2021
- Bangalore based Great Learning can help you unleash the potential of an M-Tech in Data Science & Machine - Times of India - January 19th, 2021
- CERC plans to embrace AI, machine learning to improve functioning - Business Standard - January 19th, 2021
- NTT Co-authored Papers at NeurIPS to Advance Machine Learning Efficiency and Performance - Business Wire - December 7th, 2020
- Why Intel believes confidential computing will boost AI and machine learning - VentureBeat - December 3rd, 2020
- Machine Learning Market to Grow Notably Attributed to Increasing Adoption of Analytics-driven Solutions by Developing Economies, says Fortune Business... - December 3rd, 2020
- Machine learning: The new language of data and analytics - ITProPortal - December 3rd, 2020
- Injecting Machine Learning And Bayesian Optimization Into HPC - The Next Platform - December 3rd, 2020
- QA Increasingly Benefits from AI and Machine Learning - RTInsights - December 3rd, 2020
- Everything to Know About Machine Learning as a Service (MLaaS) - Analytics Insight - December 3rd, 2020
- How the Food and Beverage Industry is Affected by Machine Learning and AI - IoT For All - December 3rd, 2020
- Amazon announces new machine learning tools to help customers monitor machines and worker safety - www.computing.co.uk - December 3rd, 2020
- Machine Learning and Location Data Applications Market 2020 Top Companies report covers, Industry Outlook, Top Countries Analysis & Top... - December 3rd, 2020
- Commentary: Chain of Demand applies AI, machine learning to retail supply chain profitability - FreightWaves - December 3rd, 2020
- Machine learning - it's all about the data - KHL Group - December 3rd, 2020
- Product Portfolio Analysis and Technological Development of Machine Learning in Medical Imaging Market during the forecasted period - Murphy's Hockey... - December 3rd, 2020
- Imaging AI and Machine Learning Beyond the Hype, Upcoming Webinar Hosted by Xtalks - PR Web - December 3rd, 2020
- Veritone aiWARE Now Supports NVIDIA CUDA for GPU-based AI and Machine Learning - Business Wire - December 3rd, 2020
- Exactech Launches Predict+, First Machine Learning-Based Software that Informs Surgeons with Patient-Specific Outcomes Predictions After Shoulder... - December 3rd, 2020
- How To Choose The Best Machine Learning Algorithm For A Particular Problem? - Analytics India Magazine - October 19th, 2020
- Lantronix Brings Advanced AI and Machine Learning to Smart Cameras With New Open-Q 610 SOM Based on the Powerful Qualcomm QCS610 System on Chip (SOC)... - October 19th, 2020
- AI and Machine Learning Technologies Expected to Play a Key Role in Expanding Multi Billion Dollar Digital Banking Sector: Report - Crowdfund Insider - October 19th, 2020
- AutoML Alleviates the Process of Machine Learning Analysis - Analytics Insight - October 19th, 2020
- Futurism Reinforces Its Next-Gen Business Commerce Platform With Advanced Machine Learning and Artificial Intelligence Capabilities - Yahoo Finance - October 19th, 2020
- Purebase Enhances Its Board of Advisors with An Expert on Machine Learning and Cheminformatics - GlobeNewswire - October 19th, 2020
- COVID-19 And The Role Of AI, Machine Learning In Logistics: A Conversation With Delhivery CTO Kapil Bharati - Mashable India - October 19th, 2020
- How to Beat Analysts and the Stock Market with Machine Learning - Knowledge@Wharton - October 19th, 2020
- AI and Machine Learning Can Help Fintechs if We Focus on Practical Implementation and Move Away from Overhyped Narratives, Researcher Says - Crowdfund... - October 19th, 2020
- Proximity matters: Using machine learning and geospatial analytics to reduce COVID-19 exposure risk - Healthcare IT News - September 20th, 2020
- PREDICTING THE OPTIMUM PATH - Port Strategy - September 20th, 2020
- What is 'custom machine learning' and why is it important for programmatic optimisation? - The Drum - September 20th, 2020
- How Machine Learning is Set to Transform the Online Gaming Community - Techiexpert.com - TechiExpert.com - September 20th, 2020
- Current and future regulatory landscape for AI and machine learning in the investment management sector - Lexology - September 20th, 2020
- Global Machine Learning Courses Market Research Report 2015-2027 of Major Types, Applications and Competitive Vendors in Top Regions and Countries -... - September 20th, 2020
- When AI in healthcare goes wrong, who is responsible? - Quartz - September 20th, 2020
- Is Wide-Spread Use of AI & Machine Intelligence in Manufacturing Still Years Away? - Automation World - September 20th, 2020
- How do we know AI is ready to be in the wild? Maybe a critic is needed - ZDNet - September 20th, 2020
- Solving the crux behind Apple's Silicon Strategy - Medium - September 20th, 2020
- Boost Your Animation To 60 FPS Using AI - Hackaday - September 20th, 2020
- 50 Latest Data Science And Analytics Jobs That Opened Last Week - Analytics India Magazine - September 20th, 2020
- Algorithms may never really figure us out thank goodness - The Boston Globe - September 20th, 2020
- Why Deep Learning DevCon Comes At The Right Time - Analytics India Magazine - September 20th, 2020
- Six notable benefits of AI in finance, and what they mean for humans - Daily Maverick - September 20th, 2020
- Twitter is looking into why its photo preview appears to favor white faces over Black faces - The Verge - September 20th, 2020
- 8 Trending skills you need to be a good Python Developer - iLounge - September 20th, 2020
- Automation Continuum - Leveraging AI and ML to Optimise RPA - Analytics Insight - September 20th, 2020
- UT Austin Selected as Home of National AI Institute Focused on Machine Learning - UT News | The University of Texas at Austin - August 27th, 2020
- Participation-washing could be the next dangerous fad in machine learning - MIT Technology Review - August 27th, 2020
- Getting to the heart of machine learning and complex humans - The Irish Times - August 27th, 2020
- Air Force Taps Machine Learning to Speed Up Flight Certifications - Nextgov - August 27th, 2020
- The Role of Artificial Intelligence and Machine Learning in the... - Insurance CIO Outlook - August 27th, 2020
- AI and Machine Learning Network Fetch.ai Partners Open-Source Blockchain Protocol Waves to Conduct R&D on DLT - Crowdfund Insider - August 27th, 2020
- AI may not predict the next pandemic, but big data and machine learning can fight this one - ZDNet - August 27th, 2020
- Machine Learning Artificial intelligence Market Size and Growth By Leading Vendors, By Types and Application, By End Users and Forecast to 2020-2027 -... - August 27th, 2020