Published in


The Unexpected Coronavirus Lessons from Online Candle Reviews

Looking for Covid-19 in unusual places

Photo: John Greim/LightRocket/Getty Images

Early on in the pandemic, I looked at Google Trends and found that you could see signs of the pandemic from Google searches such as “loss of smell.” Here is the most recent trend for the United States, where anosmia is the general topic for these types of searches.

Source: Google

You’ll notice that the topic peaked in March—around the time that news of this symptom became public—although there was a little rise before. But it is rising again. This is interesting but also noisy. Drill down to subregions and the data is harder to parse.

Then, the other day I was alerted to the following tweetstorm by economist Craig Palsson. He had come across another person, Kate Petrova, who was inspired by another tweet to delve into Amazon reviews of scented candles—in particular, those complaining that the scented candles they received were, in fact, unscented. That makes for interesting reading.

This is the most interesting graph.

Now, this all might not be perfect. There is a certain type of person who buys a candle, and mostly likely there are seasonal elements. But it is an interesting potential window on the pandemic. It shows that we have many more tools for pandemic surveillance, and there might be fruitful ways of having A.I. work through a ton of data to find other indicators. To be sure, this is less useful for Covid-19 than it may be to get early warnings of trends for the next pandemic.

Some of this work is already being done. A recent paper by Cornelia Ilin, Sébastien E. Annan-Phan, Xiao Hui Tai, Shikhar Mehra, Solomon M. Hsiang, and Joshua E. Blumenstock takes mobility data from Google, Facebook, Baidu, and SafeGraph. With this data, the researchers were able to generate a more accurate short-term forecast of Covid-19 cases than with epidemiological approaches alone. This is because mobility can cause infections (although it can also go the other way).

Source: National Bureau of Economic Research

This type of analysis will likely be useful for the current pandemic. The point here is that in today’s world, there is an opportunity to greatly build up surveillance of public health-related information. Some years ago, Google thought it could do this for the flu. It turned out the company’s predictive algorithm wasn’t stable, but the idea was solid. We just need to continue to push to find the right approach.




Debugger is a publication from Medium about consumer technology and gadgets.

Recommended from Medium

Sharing Memes is a Quick, Easy Way to Help Boost the Moods of Depressed People

Communities Are Molded by the Shape of their Platform

Tumblr Tells Us What Needs Fixing in Social Media

A Digital Detox Won’t Work Unless You Ask Yourself This Question

The Bright Light of the Internet

Our New American Gods

The Vaccinated Are Now Tinder’s Hottest Commodity

To Kill a Community

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Joshua Gans

Joshua Gans

Skoll Chair in Innovation & Entrepreneurship at the Rotman School of Management, University of Toronto and Chief Economist, Creative Destruction Lab.

More from Medium

Breaking 18-Minute 5K #1

Fitbit’s New Feature Could Save Your Life

6 Underrated Reasons to Visit Estepona, Spain

Image taken of author, smiling against a backdrop of a mountain view and a very blue sky. Maybe the rock of Gibraltar in the background. A great thing to see in Estepona!

Make Your Gift Your Superpower and Change Your Trajectory in Life