Measuring the Internet during Novel Coronavirus to Evaluate Quarantine (RAPID-MINCEQ)

Project Description

Measuring the Internet during Novel Coronavirus to Evaluate Quarantine (RAPID-MINCEQ) is a project to measure changes in Internet use during the COVID-19 outbreak of 2020.

Until availability of early detection and a vaccine for COVID-19, the world is employing social distancing, work-from-home, and study-from-home to limit COVID’s spread. Implementation of these policies varies across the U.S. and globally due to local circumstances. A common consequence is a huge shift in Internet use, with schools and workplaces emptying and home Internet use increasing. The goal of this project is to observe this shift, globally, through changes in Internet address usage, allowing observation of early reactions to COVID and, one hopes, a future shift back.

This project plans to develop two complementary methods of assessing Internet use by measuring address activity and how it changes relative to historical trends. The project will directly measure Internet address use globally based on continuous, ongoing measurements of more than 4 million IPv4 networks. The project will also directly measure Internet address use in network traffic at a regional Internet exchange point where multiple Internet providers interconnect. The first approach provides a global picture, while the second provides a more detailed but regional picture; together they will help evaluate measurement accuracy.

The broader impact of this project is an improved global picture of how different parts of the world react to COVID-19, as seen through their use of the Internet. The project will make our datasets available at no cost to researchers, and plans to visualize our data in a publicly available website.


MINCEQ is supported by NSF/CISE as an NSF RAPID award in reponse to COVID-19 as award NSF-2028279. (Note that some NSF paperwork identifies this project as “MINSEQ”.)

This work is also partially supported by a USC Zumberge award for understanding Covid-19-WFH.


  • John Heidemann, PI on this project, project leader and professor (USC/ISI)
  • Xiao Song, MS student (USC CS Dept. and ISI)
  • Erica Stutz, undergraduate researcher (USC/SURE Program, visiting from Swarthmore College) elstutz (at)


We have some early results

  • Erica Stutz, Yuri Pradkin, Xiao Song and John Heidemann 2021. Visualizing Internet Measurements of Covid-19 Work-from-Home. Proceedings of the National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium) (Virtual Workshop, Dec. 2021), 5633–5638. [DOI] [PDF] Details
  • Guillermo Baltra and John Heidemann 2021. What Is The Internet? (Considering Partial Connectivity). Technical Report arXiv:2107.11439v2. USC/Information Sciences Institute. [DOI] [PDF] Details
  • John Heidemann 2021. Observing the Global IPv4 Internet: What IP Addresses Show. Invited talk at the SKC Science and Technology Webinar Series. [PDF] Details
  • Xiao Song and John Heidemann 2021. Measuring the Internet during Covid-19 to Evaluate Work-from-Home. Technical Report arXiv:2102.07433v4 [cs.NI]. USC/ISI. [PDF] Details
  • Xiao Song and John Heidemann 2020. Measuring the Internet during Covid-19 to Evaluate Work-from-Home (poster). Poster at the NSF PREPARE-VO Workshop. [PDF] Details
  • John Heidemann 2020. A First Look at Measuring the Internet during Novel Coronavirus to Evaluate Quarantine (MINCEQ). Invited talk at Digital Technologies for COVID-19 Webinar Series hosted by USC Viterbi School of Engineering. [PDF] Details

In Dec. 2020 we released a video from our poster at the NSF PREPARE-VO Workshop summarizing our early work.

For related publications, please see the ANT publications web page.


See also the see the ANT distribution web page.


We make all datasets available through our dataset page.

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