The need for software testing: Neil Ferguson's unstable epidemiologic model

FORTRAN with implicit none is generally fine, this does things like disabling implicit creation of new variables, making I,J,K not implicitly be integer counters, requiring array size bounds, etc. In implicit mode there are many ways to shoot yourself in the foot (and unfortunately, lots of legacy codes are written like this) but you can do that in modern languages , e.g.,:

for i in range (10):
    .... # doing some work
    i = 4 - input[i] # shadow loop variable
    output[i] = sin(i)

There’s nothing inherently wrong with FORTRAN, but I’ll take C or C++ any day.

Edit: honestly the worst thing about FORTRAN is that the language spec is behind a paywall, so you don’t have an equivalent to things like: https://en.cppreference.com/w/

That’s a roundabout way of saying, if I’ve interpreted what implicit none does incorrectly, it’s because what documentation I’ve found is not great :p

You could easily argue the other way, that too-low predictions would result in dangerous complacency. But I think focusing on public reaction to predictions in this way is missing the point of doing science. It's important to separate figuring out what's going on with communicating those results.

It's particularly important to communicate about uncertainty. The total death toll is the area under a curve and it's very difficult to predict the peak or back side of the curve in advance. Due to parameter sensitivity, it's based on little more than guesses. The main message was accurate: if we don't stop it, this is going to be very bad.

In such circumstances, giving out any single number is misleading - it should be a wide range.

I've come to understand the same thing. Like any language, good Fortran can be written.

I'm not sure what machines this code was being written on, but I want to note that a lot of academic code is written in C or Fortran simply because compiler support for other languages is pretty non-existent on high performance machines. And, of course, Fortran is blazing fast and the recent updates to the language make it way more usable than like Fortran77.

I actually find this whole thing kind of humorous, as I never realized that others thought academics were writing deployment-ready software packages for their research. Most academic code is never touched by anyone other than the person who wrote it, and coding practices like we see here are pretty much the norm. I don't think it's a huge issue overall as the code is a means in this case and an ends.

I think if that's a prevailing view, it needs communicating that corona is probably a lot less severe than previously thought. The original Wuhan reports indicated a 3% fatality rate, which combined with an expected ~60% infection rate in an improperly mitigated scenario, gives you 2% of population dead. For the US, that's 6 million. That's just completely staggering. With a bit of optimism, you can convince yourself that currently, the infection fatality rate is as low as 0.3% (certainly isn't 1% at this point). That gives you 600000 dead. In other words, if the government fails to contain this, we expect at least that many. More if hospital overload is increasing fatality rates. If we scale down how we judge the government reaction appropriately, that 10k death toll came and went for the US. Compare too, that Germany exceeded that target death toll (adjusted for population) by a factor of ~2, and we've generally done a good job; so by that metric, that 100k/10k goal is quite optimistic.

In any case, I don't think the US govt did a good job at all. How do we communicate that? Ahh, that seems to be the question we have to ask at every corner here, isn't it? Nothing about this pandemic is simple enough for how our news work these days.