Of twitter and mastodon

I joined Twitter almost ten years ago (@kgeographer) in order to connect with members of my professional communities, Digital Humanities and Geographic Information Science. It has been occasionally annoying but extremely beneficial, and over 1200 folks have chosen to follow my feed.

In 2015, when a certain politician became a presumptive nominee for US President, another community became equally important to me, the #NeverTrump crowd, because I view that utterly disgraceful individual as a mortal threat to the “noble experiment” that is the United States of America. Over the years I’ve been a frequent critic of the US and many of its past policies and action, but I learned that I am much more patriotic than I thought.

Twitter has become essential to me, and I am hard pressed to imagine doing without it. Because a growing number of my professional colleagues and friends are moving to Mastodon servers from Twitter, I have established the account, @kgeographer@mast.o. In the coming weeks I plan to gradually follow the hundreds of colleagues and friends I follow who have made this switch, or like me, are transitioning to it. Let’s see how this goes.

But I will remain on Twitter, and reserve my politically-oriented tweets for that forum. Any Mastodon followers I gain will see the stuff I post related to #DigitalGeoHumanities, #Place, #WorldHistoricalGazetteer, travel photos, etc. They will be spared those responses of outrage to what’s happening in my (current) country.

Asked Twitter historians about ancient epidemiology and…

…got a ton of valuable information, references and links recently. A colleague I hadn’t seen in a while reached out to me on behalf of a student of his at Lafayette College, due to my involvement with the ORBIS project. The student is “interested in modelling the spread of disease in the ancient Roman world” and he “suggested that she investigate building cost surfaces with ORBIS and see if that could be used as an input in some sort of epidemiological model.” He asked me:

“…are you aware of any scholars…using ORBIS while investigating epidemiology in the ancient world?”

I tweeted an inquiry and within minutes, a stream of answers came back. I’ve pulled together most of them in quick and dirty fashion here, and made this post for quick reference by my friend and his student…and whomever. Also to note the generosity of people in this community I’ve had the enormous pleasure to be somewhat connected with.

From Monica Green (https://asu.academia.edu/MonicaHGreen) @monicaMedHist

The field of historical epidemiology is in the middle of a paradigm shift. Retrieval of pathogen #aDNA (for the ancient world, that includes thus far #YersiniaPestis & #HBV & 2 malaria parasites) is the new gold standard for identifying historical disease confidently. Beyond that

… we can make plausible inferences from paleopathological indicators (e.g., bone lesions, intestinal parasite eggs) about the types of disease that were present. A major project is underway at Harvard to research the ancient Mediterranean:  At Princeton (archaeoscience.org)

… a new database has been launched that focuses on plague in late antiquity:  I can’t say anything specific about the mapping components of either project yet. Deciding when & where specific diseases are found in specific populations is next challenge. (climatechangeandhistory.princeton.edu/justinianic-pl…)

You’ll need to communicate w/ the folks at Princeton about what their plans are. The Keller et al. study shared all their data on sites where they checked for #YersiniaPestis but couldn’t retrieve any. (Doesn’t mean there was no plague, only that DNA capture wasn’t successful.)

For an overview of what’s going on in #aDNA pathogen research, see this: annualreviews.org/doi/abs/10.114…, and this: nature.com/articles/s4157…. I’d also recommend your student dig deep into the Supplemental Data of Keller et al. 2019: pnas.org/content/116/25…. It’s a trove of information.

I would add that if your student has not yet discovered the network analysis work of @Byzanzforscher (e.g., academia.edu/40238623/Small…), it would be very good to look at. Again, applying this work to disease history is only as good as our disease data, which is mostly inferential.

From Johannes Preiser-Kapeller (http://oeaw.academia.edu/JohannesPreiserKapeller) @Byzanzforscher

I dealt with some aspects of using the Orbis Network for epidemic Diffusion here: . Of interest is also the work of Marek Vlach, who presented a paper on modelling the Diffusion of the Antonine Plague in Brno last year: (arxiv.org/abs/1809.08937) (arup-cas.academia.edu/MarekVlach/Pap…)

He gave a paper last year at the historical Network conference in Brno on the Antonine Plague, but as far as I see, it is still unpublished. But it was really impressive, maybe one can contact him directly, if interested.

reply from Monica Green

Thanks very much for this, Johannes. Obviously, there will be need to talk about these issues sooner rather than later, as dialogue grows btw palaeogenetics & the other historical fields. We’re trying to launch a #BlackDeath Digital Archive (#BDDA) which aims to move beyond

… the centuries of plague histories that keep parroting the same data & go back to original sources. The project just won the @CARMENmedieval Prize. In the meantime, on the issue of data quality there’s this must-read from our contributor @joris_roosen: (wwwnc.cdc.gov/eid/article/24…)

BTW, Johannes, just to confirm: this () is the study by Vlach you were referring to, right? It only mentions the #AntoninePlague once, but yes, I can see where the possibilities of this might be leading. (academia.edu/38083198/Demog…)

From Ryan Horne (https://rmhorne.org/) @RyanMHorne

Not so much in the ancient world, but we did have a @WHCPitt intern do some geospatial modeling of Ebola. A good primer for the networked aspect of epidemiology: (cs.cornell.edu/home/kleinber/…)

Using some @BigAncientMed code w/@Gephi is a good place to start

I have used an effective combination of @Gephi / @cytoscape with network / r/outes data from #ORBIS / @AWMC_UNC, #pgRouting, and @BigAncientMed / custom code to combine force-directed graphs w/ spatial data to study this type of thing. I can send an article I am finishing up for #Classics@ about this very thing (great timing!) that is a fairly high-level overview about social-spatial networks, and can send more code / bibliography about the component parts if you want.