It’s pretty hard to get to grips with the scale of the solar system when Venus, the closest planet, feels really far already. But we’re practically squished together compared to Uranus and Neptune — they are a really, really, really long way away.

James O'Donoghue has made some brilliant videos about the solar system that explain this and more.

Solar system planets — distances to scale

Writing this in the middle(?) of the coronavirus outbreak I thought it might be interesting to share these charts, created from the simulations in the excellent Washington Post article “Why outbreaks like the coronavirus spread exponentially, and how to ‘flatten the curve’” by Harry Stevens.

The charts represent different strategies for containment and mitigation of the effects of a contagious outbreak.

Trying to quarantine an area — where it is difficult to attain complete quarantine — delays the effect of an outbreak somewhat, but once released the impact is still significant with a potentially high peak of cases.

Social-distancing — staying away from each other to reduce the chance of infecting others if you are infected and minimise the chance of infecting yourself — in both the bottom scenarios in the simulation manages to both delay the onset of an outbreak and reduce the peak. Not included in this simple simulation is that reducing peak infections in particular helps the healthcare system effectively treat and care for those who are infected, and look after its healthcare workers. When healthcare is not overwhelmed this further minimises both the spread of a disease and fatality rate.

Read the article, run your own simulations, and maybe consider supporting the Washington Post, here: “Why outbreaks like the coronavirus spread exponentially, and how to 'flatten the curve’”.

Disclaimer: I am not a public health professional. These charts are from my results of the simulations in the article and the simulations represent a simplified, though instructive I think, view of an outbreak and these containment methods.

Flatten the curve of an outbreak

This is the idea that people across history budget on average about an hour a day for traveling. Originally observed by Yacov Zahavi, it came from the observation that even as our means of transport sped up, instead of traveling less each day we would just travel further. As in the sketch, this leads to a conclusion that the size of our cities increases partly according to how efficiently we can travel in and out—they generally increase to a size that maintains about an hour round-trip journey.

Cesare Marchetti observed that Greek villages and ancient walking cities, for example, as marked by ancient city walls, tend to share a radius of about 2.5km. Walking at a typical 5km/hr that makes an hour round trip journey. He also pointed out that: “Even people in prison for a life sentence, having nothing to do and nowhere to go, walk around for one hour a day, in the open.”

Unfortunately, if you live in London, the average round-trip seems to be an exception of 1h30.

This is also known as the constant travel time budget hypothesis.

Also see isochrones. It might be interesting to look at these according to transport method…

Image adapted from: Marchetti, C., 1994: Anthropological Invariants in Travel Behavior, Technological Forecasting and Social Change , 47 :75–88, Internal Publication, International Institute for Applied Systems Analysis.

Marchetti’s constant

From the prefix iso meaning equal and khronos meaning time it literally means equal times. And whereas maps are usually put together with lines of equal distance you can either construct maps, or overlay maps as here, with lines of equal time. The overlay view gives you time contours rather than, say, altitude contours. Handy for checking things like commuting distance. I like how you find little islands where there is fast transport in and out like trains or planes.

You can explore time maps of London at mapumental.

Sketchplanations tagged with distance