Basic reproduction number - the power of exponents
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[en.wikipedia.org]
The wiki article is fairly long and detailed and a decent read. The main take-away is how vastly different the number of infected changes with small changes to R0.
In other words, if one person gets it, how many people can ultimately be infected just from that 1 person. This decreases over time because eventually we run out of people that haven't been already infected. But the math is the interesting part because with 370M people it takes a while to slow down. We don't know enough about the Wuhan Virus for an accurate R0 so for sake of demonstration we will go with the range in the linked article (1.4 - 3.9). Notice that the 2009 flu has been well studied and sits in an narrow range of 1.4-1.6.
Reading the graph at R0 = 2. The first person infects 2 people and they infect 2 people, etc. After 10 iterations the result is 1024 infected.
Change R0 to 3 and the first person infects 3 people and they all infect 3 people, etc. and count after 10 iterations is now almost 60,000.
Social distancing, event cancellations, and the possible upcoming guidance on masks all have different effects on R0. But as we can see, even small changes have big impacts over time.
The wiki article is fairly long and detailed and a decent read. The main take-away is how vastly different the number of infected changes with small changes to R0.
Quote
In epidemiology, the basic reproduction number (sometimes called basic reproductive ratio, or incorrectly basic reproductive rate, and denoted R0, pronounced R nought or R zero[18]) of an infection can be thought of as the expected number of cases directly generated by one case in a population where all individuals are susceptible to infection.
In other words, if one person gets it, how many people can ultimately be infected just from that 1 person. This decreases over time because eventually we run out of people that haven't been already infected. But the math is the interesting part because with 370M people it takes a while to slow down. We don't know enough about the Wuhan Virus for an accurate R0 so for sake of demonstration we will go with the range in the linked article (1.4 - 3.9). Notice that the 2009 flu has been well studied and sits in an narrow range of 1.4-1.6.
Reading the graph at R0 = 2. The first person infects 2 people and they infect 2 people, etc. After 10 iterations the result is 1024 infected.
Change R0 to 3 and the first person infects 3 people and they all infect 3 people, etc. and count after 10 iterations is now almost 60,000.
Social distancing, event cancellations, and the possible upcoming guidance on masks all have different effects on R0. But as we can see, even small changes have big impacts over time.
