R0: How scientists quantify the intensity of an outbreak like coronavirus and its pandemic potential

R0: How scientists quantify the intensity of an outbreak like coronavirus and its pandemic potential:

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R0 describes how many cases of a disease an infected person will go on to cause – in this imagined scenario R0=2. The Conversation, CC BY-ND The term is used in two different ways.

The basic reproduction number represents the maximum epidemic potential of a pathogen. It describes what would happen if an infectious person were to enter a fully susceptible community, and therefore is an estimate based on an idealized scenario.

The effective reproduction number depends on the population’s current susceptibility. This measure of transmission potential is likely lower than the basic reproduction number, based on factors like whether some of the people are vaccinated against the disease, or whether some people have immunity due to prior exposure with the pathogen. Therefore, the effective R0 changes over time and is an estimate based on a more realistic situation within the population.

It’s important to realize that both the basic and effective R0 are situation-dependent. It’s affected by the properties of the pathogen, such as how infectious it is. It’s affected by the host population – for instance, how susceptible people are due to nutritional status or other illnesses that may compromise one’s immune system. And it’s affected by the environment, including things like demographics, socioeconomic and climatic factors.

For example, R0 for measles ranges from 12 to 18, depending on factors like population density and life expectancy. This is a large R0, mainly because the measles virus is highly infectious.

On the other hand, the influenza virus is less infectious, with its R0 ranging from 2 to 3. Influenza, therefore, does not cause the same explosive outbreaks as measles, but it persists due to its ability to mutate and evade the human immune system.

What makes R0 useful in public health?

Demographer Alfred Lotka proposed the reproduction number in the 1920s, as a measure of the rate of reproduction in a given population.

In the 1950s, epidemiologist George MacDonald suggested using it to describe the transmission potential of malaria. He proposed that, if R0 is less than 1, the disease will die out in a population, because on average an infectious person will transmit to fewer than one other susceptible person. On the other hand, if R0 is greater than 1, the disease will spread.

When public health agencies are figuring out how to deal with an outbreak, they are trying to bring R0 down to less than 1. This is tough for diseases like measles that have a high R0. It is especially challenging for measles in densely populated regions like India and China, where R0 is higher, compared to places where people are more spread out.

For the SARS pandemic in 2003, scientists estimated the original R0 to be around 2.75. A month or two later, the effective R0 dropped below 1, thanks to the tremendous effort that went into intervention strategies, including isolation and quarantine activities.

However, the pandemic continued. While on average, an infectious person transmitted to fewer than one susceptible individual, occasionally one person transmitted to tens or even hundreds of other cases. This phenomenon is called super spreading. Officials documented super spreader events a number of times during the SARS epidemic in Singapore, Hong Kong and Beijing.