Can we predict a stroke event?

Our newest paper suggests an intriguing possibility: We may be able to predict a stroke event by observing people’s activity on a search engine.

What does the evidence show?

We started with a group of anonymous Bing users who, at some point, indicated in their queries that they had undergone a stroke. We filtered these users to those who were active pretty much every day, then they were inactive for between one and several days, and indicated their stroke just after that inactivity period. We hypothesize that the inactivity was due to their stroke which happened just after they disappeared. We then tried to separate these users from other users, some who were of similar ages and others who indicated having other medical conditions.

To separate the users we represented them through a variety of attributes such as the time of day of queries, the time since their previous session, etc., but more importantly, attributes which were previously linked to cognitive decline such as the complexity of queries, the deepest link that was clicked, and more.

We found was that it was quite easy to separate these populations of users. Of course, it may be that there were other things that were different between these populations even though we took care to select them in the same way that we chose the stroke population. However, we did find that people with cardiovascular diseases were harder to differentiate from the stroke population than people with other conditions.

We also applied our model to data that was collected a year later. Here we didn’t have many people who indicated a stroke, so used a weaker label, which was the number of times each user was interested in stroke. This is an indicator that was used in the past to find people who are suffering from cancer. The model successfully found those people who are interested in stroke, just by looking at the meta data of their queries, through attributes such as those described above.

Predicting when a stroke will occur

It seems that it’s possible to differentiate populations of users who will undergo stroke from others. Can we also localize the stroke in time? That is, can we predict if a stroke will occur within the next few days?

The results here are not as strong, but they do indicate the possibility of localizing the stroke event. According to our findings, in in the 3-4 months prior to the stroke event something begins to change and peoples attributes begin to be more similar to those of people who will undergo a stroke. This could be because of microstrokes or other cardiovascular events.

The summary of our findings is the intriguing possibility that stroke causes cognitive changes some time before a stroke happens, and that these changes can be identified through people’s interactions with search engines. If this is true, the upshot could be dramatic: We may be able to prevent stroke by analyzing people’s queries and, if they indicate a possible event in future, have doctors prescribe simple medications such as aspirin. As our medical partners (Prof. Stern and Dr. Shaklai) said, there’s a lot to do before stroke and not a lot after it.

However, all our data is derived from queries of people who indicated their health conditions. We don’t have their medical records. Therefore, we’re now trying to set up a clinical trial which will collect both query data and medical records from people and validates our hypothesis.

What do you want to do after you get your COVID19 vaccine?

 As I write this blog post (May 18th, 2021), more and more people have been vaccinated against COVID-19. In the US, 47% of the population ever seized the first dose of the vaccine and another 37% are fully vaccinated ( In Israel around 70% of the population are fully vaccinated.

I thought to try and find out what people were most looking for now that COVID-19 will not be a risk for them. I started with Google’s autocomplete:

As you can see, some people want to know how to deal with the immediate aftermath of the vaccine. They ask about Tylenol and other pain medications, but also how soon they can eat, drink, or smoke. Many people ask about things they could do before COVID-19 but not during the pandemic. These include travel and exercise (presumably at the gym).

A fun exercise is to look at these needs across U.S. states and across different countries of the world. To do this, I queried Google Trends for the volume of queries for each of these needs (e.g., “after covid vaccine can I smoke?”) during the past 3 months and also for the volume of queries beginning “after covid vaccine”. The latter served as a baseline. I calculated the ratio between these two volume indicators given for each state. On a technical note, Google only gives a normalized score for each of the volumes, so we can’t treat this as excess searches per-se. Also, if the volume of queries is too low Google does not provide a number and these are missing data for us.

Interestingly, the correlation between query volume for “after covid vaccine” and the percentage of fully vaccinated people in each state is quite high at 0.80, and only sightly lower (0.78) with the percentage of people who received at least one shot. Therefore, this does seem like interest by people who are getting their vaccines.

Here are maps for these ratios, first for the immediate interests and then for the longer-term ones:

Gray countries are those for which there were too few queries. Colors represent how much more volume there was for the query in the title compared to the query “after covid vaccine” (scale is on the right of each image).

Side effects seem to worry everyone, but the least likely to be worried are people from South Dakota, Maine, Montana and Nevada. Californians and New Jerseyites really want their Tylenol. Once they stop worrying about their vaccines, many Texans would like a smoke and a drink (but drinking is also a favorite in California and Ohio).

As for the longer-term wants:

Gray countries are those for which there were too few queries. Colors represent how much more volume there was for the query in the title compared to the query “after covid vaccine” (scale is on the right of each image).

Californians (of course?) want to go back to the gym. Travel is yearned for in Georgia, New York and Washington.

Worldwide the data is much sparser. This is probably because I’m looking at queries in English. Nevertheless, here are some findings of note: Folks in the Philippines would like to go back to the gym. Alcohol is sought by people in Mexico, UK, India and (presumably expats) in the UAE. This is also true, albeit to a lesser extent, in Canada and Australia. Travel features high on the list for UAE, Canada and Australia.

What does all this mean? Probably not much beyond the obvious, but it’s still fun to see it in the data.