In my last post, I talked about why COVID-19 science is so confusing and how we can cut through the noise. Now I'm going to put my money (or at least my virtual word count) where my mouth is and follow my own advice: look at the science behind the numbers in the media. We … Continue reading COVID-19: What do we really know about the virus? Part 1
The fatality ratio is 5%, no it's 0.5%, no it's 0.01% but only in France. Masks will not protect you, but wear them because they will. Don't touch the surfaces because COVID-19 likes to rest on them, but it actually disappears almost as soon as it settles on the surface. Why is COVID-19 science so … Continue reading COVID-19: Why is the science so confusing?
"Gendered" is a new series of posts which look at gender stereotypes with data. The goal is to expose the stereotypes and equip people with tools that will help recognize them in everyday life. Because they are everywhere. Really. A few months ago a friend posted a picture that was traversing the internets a couple … Continue reading Gendered: Girls’ life vs Boys’ life magazines
You've got data, you've got a hypothesis, you even gathered the courage to test it. But how do you choose the right test? Well, really you should have thought about this before you collected the data. Maybe you did and maybe you didn't. I won't judge (ok, maybe a little). Instead, I'll offer you a … Continue reading Statistics cheat sheet – Part 1
Many people are wondering why New York is taking such a heavy hit while in states like Florida or California COVID-19 spreads much slower. After all California has as much tourism and immigration and in Florida the population is older and the quarantine was announced later. What is going on? What really affects the spread … Continue reading Why is Florida doing better than New York? The factors affecting the spread of COVID-19
Recently, Google released Mobility reports based on Google maps data, that show changes in different types of activities such as shopping and park visits during shelter-in-place. This data provided an opportunity to understand how we are doing and if what we are doing is working. Below, I describe a combined analysis of two data sources: … Continue reading Are we good at sheltering in place? And is it working? A deeper look at new data from Google
When you think "pandemic", bright sides is not what comes to mind. But there is the proverbial silver lining even in these less than cheerful times. Having to stay at home "sheltering in place" en masse, causes some unintended positive consequences of significant proportions. Let's see what the data has to say. Fewer traffic accidents … Continue reading The bright side: unintended consequences of the COVID-19 pandemic
CDC and other government orgs discourage regular citizens from using face masks at work and outside: "CDC does not recommend the routine use of respirators outside of workplace settings (in the community)." However, people still buy them en masse and we are currently experiencing a shortage. It has gotten so bad that folks are starting … Continue reading To mask or not to mask and what about cloth?
Coronavirus crystal ball is not about modelling the progression of the disease, there are many models already out there, but rather guesstimating what social and economic changes we will experience a year from now as a consequence of the pandemic. And it's not really based on data (gasp), ok maybe some data, but mostly rooted … Continue reading Coronavirus crystal ball: predicting the effects of the pandemic
Another coronavirus pandemic post that I'm planning to update frequently to keep track of how we and a few other countries in the world are doing. Updated on 04/17: You've probably seen many incarnations of this plot, but it's a good one so here is one more instance. I'm now showing the number of deaths … Continue reading Tracking COVID-19 cases and tests in the US