Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
  • Data

Stanford Crowdsourcing Site Collects County-level Policy Data To Inform Decisions About Easing Social-distancing

  • April 15, 2020
  • relay

Americans nationwide now have a chance to help government officials decide when to ease social-distancing policies by completing a survey on a new website that compiles information about if and when their counties implemented local shelter-in-place measures to slow the spread of COVID-19.

Visit SocialDistancing.Stanford.edu to provide information about local shelter-in-place policies to help government officials decide when it will be safe to ease such restrictions. (Image credit: Stocksy/CACTUS Creative Studios.)

The website, SocialDistancing.Stanford.edu, is part of a research collaboration that aims to provide accurate, county-level data to epidemiologists who will advise federal agencies – and, ultimately, state and local officials – when to start letting different communities resume daily activities again.

Since it went live on April 6, more than a thousand volunteers have found the site through social media alerts, but now the Stanford team hopes to get many more responses from every part of the country so they can funnel this much-needed information to their partners at the University of Virginia (UVA).

“Epidemiological models need reliable data and we have to collect it quickly,” said associate professor of computer science Michael Bernstein.

Bernstein launched the site just 15 days after he got a call from Madhav Marathe, director of UVA’s Biocomplexity Institute. Marathe’s team, which advises federal authorities on how to deal with disease outbreaks, had just received funding to track COVID-19 with unprecedented county-level accuracy. “We knew Stanford could help us get the data we needed in a hurry,” Marathe said.

Bernstein is an expert in crowdsourcing – using the internet to coordinate the actions of many volunteers, each of whom is asked to do a little work to finish a huge task quickly. Until now, most COVID-19 data collection efforts focused on states.

Read More  How Artificial Intelligence Can Help Us In Fighting The Next Big Pandemic

This project seeks to dive down to the local jurisdictions that have purview over health matters. Louisiana calls these parishes. Alaska refers to them as boroughs, but the other 48 states call these local units counties. Delaware has the fewest, with three, and Texas has the most with 254. Even after discounting the 300 or so most populous counties clustered around cities, for which there is already abundant information, epidemiologists still desperately need data from about 2,800 local jurisdictions nationwide.

SocialDistancing.Stanford.edu aims to be that data collection point. Volunteers are asked to answer questions about whether local authorities have ordered schools, stores, and non-essential businesses to close, and if religious gatherings have been suspended. They are also asked to attach a link to a government order, news story or other source, both to verify their answers and, crucially, to date when the restriction took effect. Knowing when social-distancing policies took effect will enable the researchers to determine how those measures affected the trajectory of COVID-19 within each county, and across many counties that took different steps at different times.

The UVA epidemiologists are anxious to begin incorporating this field data into their own models and begin sharing it with other academic and governmental labs that will also help advise government officials at every level about how to ease the current shelter-in-place restrictions. “We’re already getting inquiries from other countries about how we’re doing this,” Marathe said.

For their part, the Stanford computer scientists are glad to answer the call. “When one of the nation’s top epidemiological experts contacts you for help, you say ‘Yes!’,” Bernstein said.

Stanford graduate student Jacob Ritchie led the data collection project, along with Tum Chaturapruek, a recent computer science PhD graduate. Current Stanford team members include postdoctoral scholar Amy Zhang and graduate student Mitchell Gordon. Former Stanford researchers Mark Whiting and J.D. Zamfirescu-Pereira also are taking part.

This project is supported by a grant from the National Science Foundation.

To read all stories about Stanford science, subscribe to the biweekly Stanford Science Digest.

Read More  Inaugural AI Research Grants Advance Transformational Projects In Education, Health Care And Government

 

BY TOM ABATE

relay

Related Topics
  • Coronavirus
  • COVID-19
  • Social Distancing
  • Stanford Science Digest
  • Stanford University
You May Also Like
View Post
  • Data
  • Platforms
  • Technology

How Osmo Is Digitizing Smell With Google Cloud AI Technology

  • March 20, 2023
View Post
  • Data
  • Engineering
  • Tools

Built With BigQuery: How Sift Delivers Fraud Detection Workflow Backtesting At Scale

  • March 20, 2023
View Post
  • Data

Understand And Trust Data With Dataplex Data Lineage

  • March 17, 2023
View Post
  • Big Data
  • Data

The Benefits And Core Processes Of Data Wrangling

  • March 17, 2023
View Post
  • Artificial Intelligence
  • Data
  • Machine Learning
  • Technology

ChatGPT: How To Prevent It Becoming A Nightmare For Professional Writers

  • March 16, 2023
View Post
  • Data
  • Engineering
  • Machine Learning

Sentiment Analysis With BigQuery ML

  • March 13, 2023
View Post
  • Artificial Intelligence
  • Data

Introducing Casual Conversations v2: A More Inclusive Dataset To measure Fairness

  • March 13, 2023
View Post
  • Data
  • Engineering

Shorten The Path To Insights With Aiven For Apache Kafka And Google BigQuery

  • March 9, 2023

Leave a Reply

Your email address will not be published. Required fields are marked *

Stay Connected!
LATEST
  • 1
    How Osmo Is Digitizing Smell With Google Cloud AI Technology
    • March 20, 2023
  • 2
    Built With BigQuery: How Sift Delivers Fraud Detection Workflow Backtesting At Scale
    • March 20, 2023
  • 3
    Building The Most Open And Innovative AI Ecosystem
    • March 20, 2023
  • 4
    Understand And Trust Data With Dataplex Data Lineage
    • March 17, 2023
  • 5
    Limits To Computing: A Computer Scientist Explains Why Even In The Age Of AI, Some Problems Are Just Too Difficult
    • March 17, 2023
  • 6
    The Benefits And Core Processes Of Data Wrangling
    • March 17, 2023
  • 7
    We Cannot Even Agree On Dates…
    • March 17, 2023
  • 8
    Financial Crisis: It’s A Game & We’re All Being Played
    • March 17, 2023
  • 9
    Using ML To Predict The Weather And Climate Risk
    • March 16, 2023
  • 10
    Google Is A Leader In The 2023 Gartner® Magic Quadrant™ For Enterprise Conversational AI Platforms
    • March 16, 2023

about
About
Hello World!

We are liwaiwai.com. Created by programmers for programmers.

Our site aims to provide materials, guides, programming how-tos, and resources relating to artificial intelligence, machine learning and the likes.

We would like to hear from you.

If you have any questions, enquiries or would like to sponsor content, kindly reach out to us at:

[email protected]

Live long & prosper!
Most Popular
  • 1
    The Future Of AI Is Promising Yet Turbulent
    • March 16, 2023
  • 2
    ChatGPT: How To Prevent It Becoming A Nightmare For Professional Writers
    • March 16, 2023
  • 3
    Midjourney Selects Google Cloud To Power AI-Generated Creative Platform
    • March 8, 2023
  • 4
    A Guide To Managing Your Agile Engineering Team
    • March 15, 2023
  • 5
    10 Ways Wikimedia Does Developer Advocacy
    • March 15, 2023
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
  • About

Input your search keywords and press Enter.