Is R0 an oversimplified measure of disease spread?

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In summary, the reproducibility of scientific findings is an issue that has been raised by some scientists. The R0 value is a statistic that is used to compare the performance of different countries in terms of spread of a virus. The R0 value is arrived at from the statistics and it assumes that this 'effective' value is the same as the 'basic' value. The measured values could be the same for two different populations in which one population is taking precautions and the other population is taking none; the difference would be 'just' due to luck and perhaps some genetic differences. However, the R0 value does give some indication of the virus's exponential growth without any interference from hindering the spread of the virus. So all the
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sophiecentaur
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I understand that R0(The reproduction number) is dimensionless but I cannot help feeling that the timescale for these things must be relevant, at least in some instances, when trying to compare the performance in different countries. R0 is arrived at from the statistics and I think it assumes that this 'effective' value is the same as the 'basic' value. The measured values could be the same for two different populations in which one population is taking precautions and the other population is taking none; the difference would be 'just' due to luck and perhaps some genetic differences.

Basically, I am asking if it is an oversimplified measure.

I think it was the UK health minister who I heard say "We want to flatten the curve in order to reduce the number of deaths" Cart before horse or what??

I also heard, years ago, an education minister say "We will conduct a study to show that . . . . . whatever" They all have their cause and effect the wrong way round and the history they write justifies the decisions they took in the past.
 
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##R_0## is an important benchmark, but not the only one. And yes, time spans have to be considered, too.
sophiecentaur said:
I think it was the UK health minister who I heard say "We want to flatten the curve in order to reduce the number of deaths" Cart before horse or what??
No. There are a few hidden assumptions in this statement:
  • the number of deaths depends on the infection rate
  • the number of deaths depends on the number of available ICU
So the total number of fatalities is lower, if sufficiently many ICU are available, which is the fact, if the infection rate is low, which means, that the curve of totally infected people per time has to be flat.
 
  • #3
sophiecentaur said:
I am asking if it is an oversimplified measure.
Yes, that's it's value. It does depend on lots of factors, like population density, behavior, treatment, etc.
 
  • #4
There are several good explanations of Ro and the basic SIR model on YouTube. Here's one I thought was pretty good.
 
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sophiecentaur said:
Basically, I am asking if it is an oversimplified measure.
Yes.
But it does give some indication of spreading of a disease - ie its exponential growth without any interference from hindering the spread of the disease.
Hence all the testing and what not that was attempted early in the pandemic to get some statistics.
Attempts to lower Ro with social distancing measures, and quarantining, and the like seem to not have had the ultimate effect that the people in the know wished it would have had. Otherwise I do not think the harm done to the economy, businesses, and individual workers with loose designations of essential services would have been so willingly accepted, but rather thought out more.
As one newspaper artist had in his commentary cartoon of trying to fix the plane while it is flying.
The modelling based on an assumed Ro was probably initially as good as a guess.

The differential equation modelling of Ro does has its problems.
 
  • #6
The R0 value indicates how likely the virus's offspring are to reach a new host, at some point (or period) in time.
As the virus's life becomes more (or less) difficult (offspring less (or more) likely to find a new host), the R0 value will change, based on its new circumstances.
Its not a static number.
It is not something just determined by the biology of the virus in isolation of may other factors.

As virus spread limiting actions are taken, as more people in a population become immune, the R0 value will become smaller.
If the R0 value is small enough, for long enough, the virus will go extinct (in the wild).
 
  • #7
sophiecentaur said:
I understand that R0(The reproduction number) is dimensionless but I cannot help feeling that the timescale for these things must be relevant, at least in some instances, when trying to compare the performance in different countries. R0 is arrived at from the statistics and I think it assumes that this 'effective' value is the same as the 'basic' value. The measured values could be the same for two different populations in which one population is taking precautions and the other population is taking none; the difference would be 'just' due to luck and perhaps some genetic differences.

Basically, I am asking if it is an oversimplified measure.

There are models that take into account behaviour, etc. There are also other numbers that are sometimes called effective reproduction numbers.
https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(17)30307-9/fulltext
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084966/
 

1. What is R0 and why is it important?

R0, or the basic reproduction number, is a measure of how contagious a disease is. It represents the average number of people that one infected person will pass the disease onto in a population where everyone is susceptible. A higher R0 indicates a more contagious disease, while a lower R0 suggests a less contagious disease.

2. What are the units for R0 and why are they important?

R0 is a dimensionless number, meaning it has no units. This is because it represents a ratio between the number of new cases and the number of existing cases. The lack of units also makes it easier to compare R0 values across different diseases.

3. What are the potential problems with missing units for R0?

The main problem with missing units for R0 is that it can lead to confusion and misinterpretation of the data. Without units, it may be unclear what exactly the R0 value represents and how it should be interpreted. It can also make it difficult to compare R0 values across different studies or diseases.

4. How can missing units for R0 be addressed?

To address the issue of missing units for R0, it is important for researchers to clearly define and report their methods for calculating R0. This includes specifying the population and time period used, as well as any assumptions made. Additionally, using a standardized unit, such as the number of new cases per infected person, can help make R0 values more comparable.

5. Are there any alternative measures to R0 that can be used?

Yes, there are alternative measures to R0 that can be used to assess the contagiousness of a disease. These include the effective reproduction number (Re), which takes into account factors such as immunity and control measures, and the secondary attack rate, which measures the proportion of people exposed to an infected individual who become infected themselves. It is important to consider these alternative measures in addition to R0 to get a more complete understanding of disease transmission.

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