Daily Archives: April 1, 2020

Reducing infection rates – common sense

We could greatly reduce suffering, deaths, economic damage and duration of lockdown if the authorities were to apply some basic principles.

Restrict travel between high and low infection areas

Some areas are much more highly infected than others. Travel from highly infected areas to much less infected areas should be severely restricted. The gain from doing so is far higher than by restricting other travel.

Restricting travel within high infection areas will also achieve greater gains than doing so in low infection areas.

Red and green trains

Instead of all trains being made available to everyone, red trains would carry groups more likely to be infected and would be used by people who either live or work in a high-infection area. Green trains would be used by those who both live and work in low infection areas. There doesn’t need to be a very high difference before statistical gains are achieved. Any station would receive a few red trains, then a few green ones.

A further derivative would be to have red and green supermarket hours to separate those who work exposed to high risk from those who aren’t.

Both of the above rely on separating groups that have very different infection rates and both are quite robust against moderate cross-infection.

Travel profiles indicate most effective use of limited testing

We already target health workers and carers, but what about the rest of the population?

The faster we can identify infected people and isolate them, the more we can reduce the rate of spread, the number of total infections, overall suffering, and deaths. Given very limited testing capacity, we must optimise our approach. Some simple reasoning applies.

First, there is little point in testing those in lockdown. It would be nice in an ideal situation but we aren’t in one. The few who become infected will still emerge if they become ill enough.

The rest fall in two categories. One group travels mostly alone in private vehicles. A few will come into contact with large numbers of people through their work. If we can identify those high-contact groups, they can be allocated a higher priority.

Those travelling most on public transport are much more likely to become infected, coming into more frequent contact with infected strangers and once they become infected, are likely to infect many more. Concentrating testing on them will achieve the greatest efficiency at finding (and removing) infected people from the mix. The more infected people that can be found and removed from public transport, the faster the virus will be controlled. We know who uses public transport most via their payment cards. We  also know that those using red trains will have higher incidence than those on green trains.

Simple logic therefore shows that limited testing should therefore be applied in the following priority:

  1. Front line carers
  2. Most frequent travellers on red-train public transport
  3. Less frequent travellers on red-train public transport
  4. Most frequent travellers on green-train public transport
  5. Less frequent travellers on green-train public transport
  6. Those living in red areas who travel mostly using private transport
  7. Those living in  green areas who travel mostly using private transport
  8. Those in lockdown who must still venture out sometimes
  9. Those in total isolation

This isn’t 100% optimised, but it is close enough.