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Welcome to this Medmastery coronavirus update, I'm Franz Wiesbauer.
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I'm an internist, trained in epidemiology and public health at Johns Hopkins, and
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the founder of Medmastery, where we teach important clinical skills to doctors and
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other healthcare providers around the world.
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Today we're going to talk about herd immunity and how to stop an epidemic.
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Let's get started.
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So what is herd immunity?
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Well, it's a basic principle that's used in combating epidemics.
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Herd immunity occurs when a significant proportion of the population or the herd
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have been vaccinated or are immune by some other mechanism, resulting in protection
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for susceptible individuals.
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Let's see how this works in action.
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In a previous video we talked about R naught, the basic reproductive ratio.
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Let's look at this example where we have one diseased or infected individual and 18
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susceptible individuals.
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As you might remember, R naught is the average number of individuals an infected
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person gives the disease to.
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R naught is fairly constant for a given disease.
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R naught for the novel coronavirus SARS-Co-2 has been estimated to range
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somewhere between two and three.
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So let's say this COVID-19 patient gives the disease to these three individuals.
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And let's say these three individuals give the disease to three other individuals in
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turn.
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Then this is what the situation will look like after some time.
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Now, let's assume that we vaccinated some of these susceptible populations, such
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that they became immune to the virus.
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Now the virus can't infect individuals it infected in the previous scenario.
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Now our index case only infects one other person, and due to the immunity or herd
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immunity of the group, this newly infected case can also only infect one other
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person.
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What we've done here is to reduce the basic reproductive ratio of three to an
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effective reproductive ratio of one.
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As we've seen in a previous video, when R is equal to one, the disease remains
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stable and won't grow.
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The herd immunity threshold is the proportion of a population that needs to
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be immune in order for an infectious disease to become stable in that
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community.
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Or in other words, in order for R to become equal to or lower than one.
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If this is reached, for example, through immunization, then each case leads to a
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single new case and the infection will become stable within that population.
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So how do we know what proportion of the population needs to be immunized in order
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to reach herd immunity?
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Let's look at a disease with an R naught of eight, or one infected individual
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infects eight others on average.
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What would need to happen for them to only be able to infect one other person?
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Well, we would need to immunize these seven over here.
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So seven divided by eight or seven eighths is the herd immunity.
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It's calculated as R naught minus one divided by R naught.
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As we've learned previously R naught for SARS-KoV-2 is between two and three.
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So how many people would we have to vaccinate, if there was a vaccine in order
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for the epidemic to stop?
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Well, that's two minus one divided by two, which is one half or 50% if R naught was
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assumed to be equal to two.
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And three minus one divided by three or two thirds if R naught was assumed to be
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equal to three.
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So according to this calculation, we'd have to vaccinate between 50 and 66% of
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the population.
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Now, I recently heard Marc Lipsitch an epidemiologist from Harvard mention in a
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podcast interview that the herd immunity of COVID-19 according to his data, was
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around 40%.
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I'm sure he has more complex tools to factor in other variables that could
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influence herd immunity.
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But if you want to go by the books, the calculation of herd immunity according to
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the formula we provided is valuable and valid.
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By the way, I really recommend you follow Marc on Twitter.
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He provides great insights about the epidemic and seems to be a super smart
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guy.
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That's it for now.
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