[SystemSafety] Accuracy of COVID modeling code

Coq, Thierry Thierry.Coq at dnvgl.com
Wed May 6 14:49:06 CEST 2020

The last model is typically a stochastic model with input parameters. The modelling itself will lend to variability in outputs depending on the quality of the random generator. The input parameters are only estimates, which can vary widely depending on the assumptions on a disease which is not well known.
Any particular result should be taken with a lot of caution, and even the "average" behavior on what is essentially an exponential model may be suspect.
This looks like a best effort to give rule-of-thumb ranges of estimates. Based on the published scientific data known today, with its wide variability, this is probably the best that can be done.

A couple of years down the road, there will be much more data, of much better quality, and they will be much more capable of modelling what should have been done today...

Personally, I would not have used the SW technologies they used for reliable scientific computations, with the increased risk of software defects, but that is probably not a consideration retained by that team, for a quick prototype and a work in progress.

Best regards,

Thierry Coq
PS. This is my personal response and does not engage my employer.

-----Original Message-----
From: systemsafety <systemsafety-bounces at lists.techfak.uni-bielefeld.de> On Behalf Of Derek M Jones
Sent: mercredi 6 mai 2020 14:02
To: systemsafety at techfak.uni-bielefeld.de
Subject: [SystemSafety] Accuracy of COVID modeling code


Governments are making Coronavirus decisions based on the predictions of models.

Model predictions depend on the accuracy of the model and the accuracy of the code implementing the model.

Some comments on the original, broad brush model:

Now we have a detailed model, which I suspect is very new:

I have not had much luck in drumming up reviewers for the earlier models.

Please reach out to people with the expertise to review this new code.

Derek M. Jones           Evidence-based software engineering
tel: +44 (0)1252 520667  blog:shape-of-code.coding-guidelines.com
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