Disclaimer. I am not a Scientist through I have scientific background. Over the last month I have read numerous scientific papers and I thought I would try and take all that information and boil it down into what is R0, why the concept matters and how different modelling assumptions around R0 might help explains what our elected leaders might do. Consider everything to be illustrative only.

There are lots of terms going around and ideas about what needs to be done. Do nothing, Flatten the curve, bend the curve, extinguish Exterminate the disease and lots of nice graphs and charts to try and explain it. All these concepts are basically around what to do to adjust the infection rate to a point where the spread of the virus is at level where we can avoid a catastrophic impact on human life.

Technical Definition of R0

R0 is pronounced “R naught.” It’s a mathematical term that indicates how contagious an infectious disease is. It’s also referred to as the reproduction number. As an infection spreads to new people, it reproduces itself. R0 tells you the average number of people who will catch a disease from one contagious person. It specifically applies to a population of people who were previously free of infection and haven’t been vaccinated. If a disease has an R0 of 18, a person who has the disease will transmit it to an average of 18 other people, as long as no one has been vaccinated against it or is already immune to it in their community.

R0 of Different Diseases

R0 is a statistical average

R0 is a statistical average across the whole population. Scientists understands that different people transmit the disease a different amount of times, but the concept is useful as a way of understanding the speed and ferocity of disease spread. When scientists model changes to R0 they break it down into the underlying components, predominantly

1) The number of interactions you have i.e.

· Handshakes · Monetary Transaction · Sitting on the bus · Chatting over the garden fence

2) And, the chance of passing on the virus with each interaction i.e.

· Time of interaction · Degree of Physical contact · Level of personal protective equipment

If you have a busy life with lots of interactions and you face kiss everyone Italian style when you meet, then you probably are going to personally pass it onto heaps of people. Where heaps is clearly a widely accepted scientific term.

If you are hermit living on an island getting food air dropped to you then you have zero interactions and you are not passing on squat.

All the extreme examples and the downright average 9 to 5 worker bee examples are summed together to contribute to R0. The R0 averages this out. There will be extremes but across the population they all average out to a single number

Case Study — Super Spreader

Lets first look at a high-powered Marketing Executive’s interactions. Let’s call him Scotty.

Then Scotty catches COVID After 4.5 days he becomes infectious but is not showing any symptoms

Scotty does not know he is sick, so he does his usual routine

Scotty has now infected 5 people. He is mostly responsible for these infections as he should have been carrying out better social distancing.

The next day he becomes symptomatic. He thinks his job is really important, he thinks he just has a cold or at worse the flu, so he goes to work. As he is symptomatic his chance of passing on the virus has increased

Scotty infects 10 people on his second day for a total of 15. These second ten are completely his fault. We are no longer in a business as usual state where no one cares if you pass on a cold. If you pass this virus on to a random 30 people when hospitals systems are overloaded statistically you are going to kill one of them. If you are sick you need to stay at home. Over the next two days Scotty infects a further 15 people.

Case Study 2

R0 as mentioned earlier is about statistical averages.

Mrs Smith the lovely grandmother from across the street has a different number of interactions.

She has a morning routine of Shopping, Green Grocers, Butcher, a quick Chat with Mrs Henderson and then has few words with a neighbors. On average she has 5 quick interactions per day.

She gets the virus and on the first day interacts with 5 people but as she is practicing good social distance she only has a 1 percent chance of passing on the virus with each interaction. Luckily she does not infect anyone.

The next days she is symptomatic and quarantine herself and the virus does not spread further.

Examples Across Society

R0 is about the average transmission.

If we are going to flatten or to eradicate, we have to get R0 down close to 1 or below 1. If we get it to 1 it stops growing if we get it well below 1, we eradicate like China.

R0 expressed across society

At a society level we can imagine how R0 is built by attributing bits of the 2.5 R0 to different interactions within our society. A lot of the published articles tend to break down disease spread into Household, Work / School and Social interactions. They then build complicated models to understand how tweaking one lever may affect the overall spread of the disease. These models are calibrated utilizing recorded interactions in real life and can be intelligent enough to model the difference between people staying home when sick vs pushing through and going to work.

However, the virus is new and may not behave the same as theoretical influenza-based pathogen. What we know is that the best guess is that the R0 is around 2.5. Which part of society spreads the virus most effectively is not known so our R0 of 2.5 could be broken up in a number of different ways.

I have put together Three different flavours for illustrative purposes of how R0 may be imagined across the society

Work and School Spread — This is where society level spread is concentrated via work channels and via schools with only a small part being contributed to by household spread and social activities

High Social Spread — This category is intended to capture if the disease mainly spreads within households and events such as Parties & Sports

Work and Social Spread — This category is intended to capture the situation where spread of the virus mainly occurs in workplace, household and social settings with only a small amount of spreads within school

I have shown this illustratively in the diagram below. Each person represents 0.1 of R0 spread

Potential spread in a society

What Social Isolating is attempting to do cut out the spots where the disease can spread.

China successfully cut out spread

Full lock down might get you something like the China results which reduced R0 to 0.3. We do not have clear stats where the 0.3 were generated but some of it would have been through the work place (essential services were maintained) and some through the household / Social both spread in households and also spread in the shopping households completed every three days

Australian Approach

Various countries have implemented different lock downs. In Australia we have implemented numerous strategies

· Shut Down 10% of workplaces · Shut Down service industries (Bars, Retail shopping) · Shut Down Sport and Recreation · Encouraged aggressive social distancing

Confusingly Australia has not shut down schools.

Scenarios capturing impact of Australian changes

As you can see under the scenario’s outlines R0 is still above 1 so under these specific scenarios the disease will continue to spread exponentially (Through very slowly). I am not proposing that the Australian Governments lockdown is insufficient as I am just trying to give a conceptual view around how the lockdowns work. I am confident that Australian Government health systems and most countries around the world will have specific pandemic models for their country which they are using to inform their decisions.

Regarding schools I have read academic studies which suggests the impact of school closures for an influenza like disease with an R0 ~ 2.5 is around 1. My assumption is that the Australian government has more advanced modelling specific for Australian context which suggests the R0 contribution of kids is well below what was identified in the studies that I have read.

Given different cultural differences between Countries and the ‘Novel’ nature of the COVID-19 virus this lower impact of schools is plausible.

Summary

· R0 is a society measure that effectively applies across societal activities. Work / School, Parties, Households.

· Complicated models exist that the Australian Government will be using to influence their decisions

· The failure to close schools is not necessary a mistake and is probably based on Pandemic models specific to Australia

· The Government is aiming to keep as much of society going as possible while neutering this threat

A few other points which will probably come out in future articles

· Infection Fatality Rate is going to be above 1.5% because everyone can get this and there is no massive group of asymptomatic patients that China missed

· Infection Fatality Rate will be significantly above 1.5% (2 times, 3 times, 4 times as much) if the hospital system fails

· This is not the flu. If this goes through as unchecked a pandemic, then fatality is at least 10 (up to 40) times more than flu and furthermore 3 to 10 times as many people will be impacted. This virus could easy kill 30 to 400 times as many people as the flu

· South Korea, China have been successful at stopping spread through social isolation, but it takes the whole society to ensure it works.

Please do everything you can to stop this through reducing your interactions outside of your household

Links

https://www.healthline.com/health/r-nought-reproduction-number