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Even though there is plenty of public data, I cannot find a source for the global infection chains of Corona. In other words, I am interested in the data that shows from where each infection has been imported (e.g. country A's patient 0 has imported Corona from country B).

You can find information about that here and there in various news articles. However, I hope for a data source that can be used automatically.

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I'm not sure anybody in the world has this information.

I live in Italy, not far from the largest coronavirus spreading in Europe. Patient 1 (the guy who started the epidemic in all Italy) used to live about one hour from my town. No one has still a clue on how he got it, and how it all started. I'm quite sure there's no such data at all. I'm sorry about this.

I suggest you to take the coronavirus dataset available on Kaggle and maybe try to estimate it by combining it with geo-data. That's the only thing I can think ok. Hope this helps.

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  • Thanks for the link! Of course there is no such data. Otherwise the official institutions wouldn't struggle at all. Mapping confirmed cases and geo data won't work - I think - because all you know is when it pops up in some country. However, news say something like "first patient was travelling from xy country". So there is a strong possibility that it got imported from xy country.
    – AmonNascaroth
    Mar 6, 2020 at 10:29
  • I see. In that case you might try to do it by scraping news websites, I guess? It's hard work, but the results would be extremely interesting.
    – Leevo
    Mar 6, 2020 at 10:43
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So on Kaggle there is a "line list" data source which is quite interesting. https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset

In this list you will find a column showing whether it's the first case in a particular country, if the patient was visiting or coming from Wuhan.

However, there are cases where it's not that binary. Take Germany for example:

new confirmed COVID-19 patient in Germany: 1/28-No.1 male, 33, caught from Chinese colleague during conference in Munich from 1/20-1/21, first human-to-human transmission in Europe, confirmed 1/27/202...

Or Italy

new confirmed COVID-19 patient in Rome, Italy: male, Chinese tourist, arrived in Milan over a week ago

Both are first cases, so therefore the number of cases is 1 and can be filtered easily. However, there are nth confirmed cases which have been imported too. Therefore, some automation filtering those entries would be helpful.

Could NLP help? I am a novice in these topics and started learning, so excuse me if I haven't tried yet.

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