Modelling 🦠 Coronavirus – Quarantine?!

As coronavirus is threatening to become a global pandemic, I’ve built seven epidemiological models of increasing complexity in order to illustrate how infectious diseases get transmitted over time. Among others, I try to answer the questions of what is the scientific rationale behind a surgical mask or an all-out quarantine. This is a video commentary of a simulation modelling exercise using system dynamics – if you like it, maybe I’ll make some others in the future 😃.

Here I’ve linked the video, and below there is another link to the actual live simulator that I have built – you can go and a have a play yourselves as well. At the bottom of the page, I’ve included some other useful links regarding tracking the coronavirus epidemic.

Video


🕹 Simulator


📊 DATA + CODE: The simulator was created in Anylogic, using principles of system dynamics, as presented in John Sterman’s Business Dynamics book. The base SIR model structure is along the lines of MIT Sloan School of Management‘s System Dynamics course, as taught in 2013. I’m using the first and the second homework assignments. Here you can download the AnyLogic alp source files.


📈 From an information design and data visualization perspective Andy Kirk made an awesome list about what do we have to pay attention to in the information war surrounding the coronavirus.

💊 The official epidemic site of the World Health Organization, is also quite good. Very detailed and they have several informative videos explaining prevention and conduct.

🧩 In my opinion, the top expert in network modelling of epidemics is Alessandro Vespignani and his mobs-lab at Northeastern University‘s Network Science Institute (netsi). They have a coronavirus summary page – albeit not so complete as the JHU CSSE I’ve linked below. However, their EpiRisk page is really great: it forecasts the spread of an infectious disease taking into account the connections in the global fight network. As i talk about it in my video, localizing the disease is super crucial in the beginning – and the nonlinear nature of the system means that even a few more accurate kilometers can lead to thousands less of infected people in final cases.

✳ For staying up to date with the latest data on the coronavirus, the best resource in my opinion is the virus tracker by Johns Hopkins University‘s The Center for Systems Science and Engineering (CSSE):

Published by Dénes Csala

AI | DATA | ENERGY | SYSTEMS researcher | thinker | modeler | blogger | traveller https://csaladen.es

2 thoughts on “Modelling 🦠 Coronavirus – Quarantine?!

  1. What about modelling with a rogue element. Everything modelled to date is pure.
    What about a mass shooter type personality who deliberately goes about mass spreading the virus.

    Can we see a model showing social distancing and a rogue element competing at the same time.

    Also what about terrorists freezing the virus only to unleash when everyone is back to normal but they unleash it with maximum force.

    Also people keep talking about flattening the curve but no one is modelling how long that flat curve is in real time.

    Liked by 1 person

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