Tag: influenza

283 tweets about flu today

I wanted to use the TwitteR package for R since a long time, I tried but didn’t do much of it. Today I found a few minutes, followed simple recipes (I admit), and looked at the number of tweets about flu today (November 13, 2018). Result: 283 tweets in English (I wanted to focus on the USA but, for some reason, I couldn’t … yet!). That’s not a lot. But remember we are only at the beginning of the influenza season 2018-2019 in the Northern hemisphere.

After some very basic cleaning, here are the words most used: flu, influenza (obviously: I was looking for them!), rt (note to self: remove this indication of a retweet), vaccine, health and get. As I mentioned: we are at the beginning of the flu season in the Northern hemisphere, it’s still time to get vaccinated and protected against flu!

Now of course, I wanted a word cloud 😉 Here it is:

It’s basically the same graph as above. You don’t get the count but you get the feeling of how important each word is (and you get more words).

I also recently read the recent WIRED article about the need of less stats and more stories about the success of vaccines. And I was wondering if, by following tweets and people on Twitter, tweeting about flu, we could reconstruct stories about influenza and vaccination against it. I’ll try to dedicate a few minutes every now and then, during this season, to this. In the meantime, if you have additional ideas, don’t hesitate to send them to me, comment below, or contact me … on Twitter, obviously! (I’m @jepoirrier)

Increasing certainty in flu vaccine effectiveness

According to CDC data, studies are getting better at estimating the influenza vaccine effectiveness.

With the 2017-2018 flu season still going on in the USA, there are already some indication that vaccines have some effectiveness (although its target strains were mismatched). The CDC reports how it measures vaccine effectiveness here and I was interested in their confidence intervals (the interval that takes into account uncertainties to extrapolate to the broader, unknown population).

Here is the same graph as on the CDC page, but with confidence interval:

180223-Flu-vaccine-effectiveness-USA-influenza-season
* 2016-2017 VE are still estimates. ** 2017-2018 interim early estimates may differ from final end-of-season estimates.

You can already notice it above but the graph below confirms that the confidence interval becomes narrower with the various flu season. This can come from various reasons. One obvious reason is that early seasons (< 2007-08) had a very small sample size (< 1,000). But overall, we can notice a gain of certainty around the effectiveness (the lower the line below, the more certainty).

180223-Flu-vaccine-effectiveness-USA-confidence-interval-influenza-season
* 2016-2017 VE are still estimates. ** 2017-2018 interim early estimates may differ from final end-of-season estimates.

As usual, the dataset (and code to generate the graphs above) are on my Github repo.

FluTE makefile for wxDev-C++ (Windows)

FluTE is an influenza epidemic simulation model written by Dennis L. Chao at CSQUID. It works out-of-the box on GNU/Linux (just type make and run it).

I wanted to see how it works. But since I’m temporarily stuck with a Windows laptop, I downloaded a free C++ compiler for Windows (wxDev-C++), imported all the files in a project and compiled. For those who want to try, here is the project file and the specific makefile in a zip file (2 kb). Just decompress the FluTE archive (I used version 1.15), copy the two files from the zip file above and launch the IDE. In the project options (Alt+P), specify the custom makefile (in the "Makefile" tab) as the one from the zip file above. Compile (Ctrl+F9). Done.

On my Intel Core2 Duo T5450 (2Gb RAM), it took 6 minutes to simulate the "two-dose" example.

Please note that I didn’t try to compile with OpenMPI. Maybe for next time.

Evolution of H1N1

I needed some data to test the pChart charting library so I decided to use WHO data about swine flu (in its weekly updates). The only issue I had was that the WHO started to collect data by country and changed to gather data by regional offices from July 27th, 2009 onwards. So graphs below are only by regional offices.

Evolution of A/H1N1 cases - jepoirrier.net

Evolution of A/H1N1 deaths - jepoirrier.net

For your information:

AFRO: WHO Regional Office for Africa
AMRO: WHO Regional Office for the Americas
EMRO: WHO Regional Office for the Eastern Mediterranean
EURO: WHO Regional Office for Europe
SEARO: WHO Regional Office for South-East Asia
WPRO: WHO Regional Office for the Western Pacific

I didn’t really see such graph on the web but there is the excellent FluTracker by Dr. Niman and a lot of information about the swine flu on Wikipedia. If you want to start interpreting these curves, you might be interested in reading squareCircleZ’s post about the H1N1 and the Logistic Equation.