Artash Nath, Grade 9 Student, Toronto, Canada

“Monitor My Lockdown” project keeps policymakers, health workers, and citizens updated about the effectiveness of COVID-19 lockdowns in reducing human movements. It does so by analyzing near-real time anthropogenic seismic vibrations across Canadian cities using data from the Canadian National Seismograph Network.

The project website and the web app are now live at

Since 11 March 2020, when the World Health Organization (WHO) declared COVID-19 a pandemic, countries around the world rushed to declare various states of emergencies. Canada was no different. By 22 March 2020, all Canadian provinces and territories had enforced some forms of lockdowns, and the Canada-US border was shut.

But lockdowns are difficult decisions to make – politically and economically. Closing borders, grounding road, rail and air transport, closing schools, offices, entertainment and sports venues, and non-essential services come at a huge cost to individuals, businesses and society. But restricting human movements is essential to check the spread of the pandemic and ensure our health systems do not collapse.

I wanted to find out how to measure reductions in human movements in different Canadian cities so that policymakers can better time and target the lockdowns based on near-real time data and hard evidence.

Measuring Reduction in Human Movements During the COVID-19 Lockdown Using Seismic Data

The Geological Survey of Canada (GSC) operates a Canada-wide network of seismic stations to record ground motion because of the earthquakes. The data is collected continuously and available online. Seismographs are very sensitive instruments. Seismic stations are purposefully built outside the cities so that they do not record city-related noises such as construction, transportation and other cultural noises. But in many cases, I could locate seismic stations close to major Canadian cities.

I wrote a custom algorithm to gather, analyze and visualize 10 billion lines of seismic data from 9 seismic stations (located nearby major cities) across Canada. The initial goal was to measure seismic vibrations prior to the first lockdown (March 2020 – May 2020) and compare them to seismic vibrations during and after the lockdown for these 9 cities in 6 provinces: Calgary, Halifax, Montreal, Ottawa, Quebec City, Toronto, Vancouver, Victoria and Whitehorse. I successfully measured a drop in seismic vibrations for all these cities, ranging between 12% and 55%.

I then extended my algorithm so that it can provide near-real time analysis of anthropogenic seismic vibrations across 9 Canadian cities using data from the Canadian National Seismograph Network and send updates to policymakers.

See detailed results: the seismic silences of Canadian cities during the COVID-19 lockdown.

Monitor My Lockdown Web App: For COVID-19 pandemic planning

I have created a Web App so that my research and methodology can be used for ongoing and future pandemic management.

  • Policymakers and media can use the App to monitor effectiveness of lockdowns in different Canadian cities and compare them to different periods.
  • Healthcare workers can use the App to predict for spikes in COVID-19 cases due to increase in human movements. They can then make arrangements for additional personal protection equipment (PPEs) and testing kits.
  • Researchers can use the App to extract seismic vibrations over different frequencies.

Monitor My Lockdown Online Tutorial: from Canada to the World

The pandemic does not respect national boundaries. Every country is grappling with how to enforce lockdowns to manage the pandemic. The World Health Organization (WHO) is warning of deadlier pandemics in the future. We need to be prepared.

I created an online tutorial so that users anywhere can analyze seismic data for their cities and measure the impacts of lockdown. The tutorial takes an hour to complete and is run using Jupyter Notebook.

View Monitor My Lockdown project website, Web App and detailed results at:

Artash Nath, Founder,

Hello, Bonjour. I am a Grade 9 Student from Toronto, Canada. I work on space, robotics, machine learning, and big data projects. I love to cook, strum the guitar, and play water polo.



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