What if Pokerus could spread to humans?
What if Pokerus could spread to humans?
A lot of people have been talking about this weird disease called SARS-CoV-2 for some reason, but I think we need to focus on a more pressing and insufficiently discussed disease that might be on the horizon— Pokerus. We know that it’s been affecting pokemon with little to no real side effects, but what if it turned into a zoonotic disease, that is, an infectious disease that was first transmitted from an animal (or in this case, pokemon) to a human? After all, if COVID-19 was a zoonotic disease (and SARS, and MERS, and so many other devastating epidemics), why not Pokerus?
Let’s imagine a scenario where a zoonotic transmission event occurred, where a human interacting with a pokemon infected with Pokerus managed to catch the disease. There’s not much really known about Pokerus and human biology, but let’s assume that it acts in a similar fashion, albeit being much more fatal. In the Pokemon games, Pokerus transmission is a bit of a strange phenomenon. It can only be spread if the infected pokemon is in your party, and if the infected pokemon is directly adjacent to a vulnerable pokemon after you win a battle (if any pokemon adjacent to the infected pokemon has already been infected or has been cured, they are unable to be infected).
If you’ve never played in the Pokemon games, this can be a little confusing, so let me try to be a little more clear. There are six pokemon in a party, and they can be ordered however you want, from first to sixth. They would look, for example, something like this:
The “directly adjacent” part means that, for instance, a pokemon in slot 2 (in the image above, Charmander) could infect the pokemon in slot 1 or 3 (Bulbasaur and Squirtle respectively) after winning a battle, given that the adjacent pokemon don’t have Pokerus and haven’t been cured of it before. To elaborate, if a pokemon were in slot 1 or 6, they could only possibly infect one other pokemon, with a transmission rate of 1 out of 3. We can probably assume, based on this, that transmission is pretty direct, perhaps through air or contact.
Now, let’s say that the Kanto Public Health Department (KPHD) have known and prepared for this possibility, and have already developed a vaccine against it— however, their stingy higher-ups only want to vaccine the minimum number of people so that herd immunity effectively renders the entire Kanto population safe from Pokerus. In order to calculate that, we need to find a little something called R0- otherwise known as the basic reproduction number. The R0 (pronounced “are-naught”) is “the expected number of secondary cases produced by a single (typical) infection in a completely susceptible population” (Jones 1). Essentially, how many people can one person with the disease infect.
We can calculate R0 using this formula (Jones):
Where r is the probability of infection given exposure between a vulnerable and infected individual, c is the average rate of contact between infected and vulnerable individuals, and d is the duration of infectiousness. We established earlier that the transmission rate is 1 out of 3, so we can use that for the r value. That’s the easy part— the other two require a little more digging and a few more assumptions.
Where r is the probability of infection given exposure between a vulnerable and infected individual, c is the average rate of contact between infected and vulnerable individuals, and d is the duration of infectiousness. We established earlier that the transmission rate is 1 out of 3, so we can use that for the r value. That’s the easy part— the other two require a little more digging and a few more assumptions.
First, the d value. According to Bulbapedia (the Wikipedia for Pokemon), the duration of the disease depends on the strain of Pokerus, of which there are four. Let’s assume the worst possible scenario, Strain D, which lasts for four days. Other strains that have shorter durations exist, but it’s safer to use the most likely extreme scenario to ensure safety in creating precautionary measures for the KPHD. We’re also assuming that people will be completely contagious for the entire duration of their time sick. With most diseases, you usually have something called the incubation period (the time between exposure and onset of disease) and the latency period (the time between exposure and infectiousness) before infectiousness, but we’re gonna pretend like that doesn’t exist. After all, all models are wrong, and this one especially so— let’s not talk about it’s usefulness. The d value is 4.
The c value is where we’ll have to think a little more critically. In a pokemon party of 6 members, the average rate of contact between diseased and susceptible pokemon is a little easier to think about, but in an entire human population, we’ll have to look at how the region is structured, and how often people “encounter” each other and allow for possible transmission events. This post on Reddit outlines the entirety of the Kanto population according to the original game, and so we’ll be using the data there as reference.
Using this paper by Del Valle et al, we can roughly determine how many transmissions occur during one infected person’s normal encounters during the four days that they have Pokerus. The article gives us a handy matrix that tells us the daily number of adequate contact per person between aggregated age groups. We can then use the Reddit post’s age breakdown to determine how many people one individual could infect. Let’s assume that the Pokrus infection begins through a trainer interacting with an infected pokemon. Using the data, we can find that the average age of a trainer in Kanto is a little older than a young adult, which I’m gonna assume is age 20-29 (that way, it lines up easier with the transmission matrix). We find that throughout an average day for the average trainer in Kanto, they will encounter around 10.36 people. However, of those 10.36 people, it’s likely that only around half of those encounters will be long or meaningful enough to be a genuine transmission event— let’s drag that number down to 5.18 and call that the c value.
And if we plug in our values into the formula above, we find that the R0 of Pokerus is around 6.91 (nice). That is a very high figure— for context, the R0 of COVID-19 is estimated to be between 2-3, SARS is 4, and measles is around 18. This is a highly infectious disease, and one that would rip through the Kanto population like wildfire if proper precautions are not taken. So, for the KPHD, how many vaccines would they need to prepare and administer in order to maintain public safety?
To answer, we can calculate the herd immunity threshold, which is 1 - (1 / R0). So, if we stick our R0 into the equation, we find that for the entire Kanto region to be safe via herd immunity, we would need approximately 85.5% of the population to be vaccinated (or immune) in order to be safe (assuming the vaccine is 100% effective for life, transmission is direct, and there isn’t any cross-species shenanigans going around). Great! Because the total population of Kanto is 697, that means around 581 vaccine doses total. Problem solved, and crisis averted!
But let’s throw one final wrench in the equation. I’m assuming here that the entire Kanto population is eligible to be vaccinated, when that’s almost never the case in real life. If we avoid giving the vaccine to young children, our eligible population dwindles from 679 to 667. Still plenty to go on, but it makes sense to also not vaccinate the extremely elderly and sick— I’m going to assume that around a quarter of the population listed as “elderly” in the data are ineligible, bringing our figure from 667 to 650. Still comfortable.
But how about the anti-vaxxers? Anti-vaccine proponents have become more and more common, and they’ve come over to infect the Kanto region as well! All of Team Rocket fiercely believe that the vaccine will cause pneumonoultramicroscopicsilicovolcanoconiosis, so they will not be taking the vaccine. There are 50 members in Team Rocket including Giovanni, which knocks down the possible population to get vaccinated from 667 to 617. Suddenly, our buffer has shrunk to 36 people.
This is just one example of how easy it is for a disease to continue being a nuisance (or worse, a life-threatening danger) to a population even if a vaccine is present and being administered. There are going to be groups out there with legitimate reasons to not get vaccinated, and there inevitably will (unfortunately) be groups out there that will religiously be opposed. Combine that with laziness, human error, procrastination, forgetfulness, work issues, and a whole other host of reasons for why people might not get vaccinated in a timely manner, it’s not a surprising outcome that even if a vaccine is readily distributed and available, the disease will continue to be a threat.
And don’t even get me started on how colossally fucked the government-side of vaccine distribution can be (shoutout Moon Jae-in).
Sources: Notes on R0 (Jones): https://web.stanford.edu/~jhj1/teachingdocs/Jones-on-R0.pdf
Reddit post on Kanto Population: https://www.reddit.com/r/pokemon/comments/n3wesv/the_population_of_kanto_in_pokemon_red_and_blue_oc/
Mixing Patterns Between Age Groups: https://www.researchgate.net/publication/228649013_Mixing_patterns_between_age_groups_in_social_networks
