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Oh this is great, Jofre! Super interesting and well done, thank you for sharing :)
This is a very cool investigation. Would you consider doing something similar for the flu in the United States, given that over 40 million people were sick, over 800,000 people were hospitalized, and over 61,000 people died in the 2017-2018 season in the US, according to the CDC? I'm not sure if you can get similarly detailed data for these illnesses, though, for whatever reason.
Thank you! Yes, it would be quite interesting to compare such analysis with less exotic viruses like the flu in the US. If you find a more detailed dataset with specific dates let us know. In the near future, I would also like to do some analysis on the swine African fever and maybe other diseases spread by ticks.
Lyme disease is spread by deer ticks. It started near Lyme, CT about 30 years ago, and has spread throughout the northeast US. See this EPA publication for a place to start for background & data.
Thank you @Robert Nachbar ! This is very interesting. Recently, I explored the distribution of ticks species in North America using citizen scientists observations. One could combine both datasets to find some correlations. Hope to find some time soon and share it here. :)
Great post. Could you share the code you used to create the dataset file nCov_dataset.wl ?
Hi @Icy Toc , See attached the nCov_dataset.wl file at the bottom of the post. I've just updated the file to the most recent data obtained from here. In case you want to know how I actually created the dataset from raw data; I basically downloaded their spreadsheets as comma-separated values ".csv" files and then I used SemanticImport to obtain a proper format dataset with data ready for this analysis.
Hi @Jofre Espigule-Pons I did not know about SemanticImport. Thanks for the pointer.
Can you detail how you downloaded the data from google sheets? I am stuck on right-click and save as HTML.
The online spreadsheet data shows data including Feb 2nd but oddly the map page stops at Jan 31st. I am interested in keeping current.
Just yesterday we published a Wolfram Data Repository resource that makes the data immediately computable: https://datarepository.wolframcloud.com/resources/Novel-Coronavirus
More to come
Hi @Danielle, I think that in the GeoBubbleChart example of the Wolfram Data Repository resource, the code:
should be changed to:
thank you. it's very convenient to import the data from WDR.
in this link  not sure, if the second line needs to assign the output to the variable data
data =ResourceData["Epidemic Data for Novel Coronavirus 2019-nCoV from \
To import each sheet (one per date) as individual datasets
Thanks @Rohit Namjoshi, I was having the same issue that @Douglas Kubler had. Thanks again.
The nCov_dataset.wl code is alraedy attached by the a/m nb. code by
Jofre Espigule-Pons, Wolfram Research.
Have you tried using this data to parameterize/fit a modl in the style of
Thanks, I saw the post, but I haven't tried to parametrize/fit a model with current data from 2019-nCoV virus. It would be interesting to compare them. :)
Hello! So I used to think I was the only person interested in ecology and conservation biology who used Mathematica. Now there are two of us we should start a club! But seriously, it's great to have someone promoting this kind of use on the community (and indeed within Wolfram itself). I'll try to make some time to contribute my own posts.
Hi @Gareth Russell, it's great to see that power users doing research in such topics do exist. Looking forward to know more about your computational ecology contributions. :)
Maybe there are 2.5 of us! I do a lot of epidemiology modeling, and that is very similar to ecological population modeling. Think Lotka-Voltera preditor-prey models on steroids. :-) I'd like to see what could be done in that area with the systems of ODEs. I'd also like to try simulations on a spatial network. So, if you have any favorite examples, I'd love to hear about them.
Well, I have a complete Mathematica course in Computational Ecology! Including metapopulation and L-V community ODE systems. Plus some basic epidemiological models and some simple simulations of spread on a network.
Two point five?! Hey, this Mathematica type of usage could...go viral!
(I crack me up.)