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| Понравилось | : | 542 |
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 | Theres no such thing as a Virus! Комментарий от : @americanbornandbred5475 |
 | This reminds me of the simulations that Primer would run. Комментарий от : @LiteraIIy_Nobody |
 | 1:58 "Or if they die, they won't be able to spread it anymore" Pop up: Necrosis symptom mutated for free Комментарий от : @carloskoo7844 |
 | But the ones that have recovered can get infected again after a while. Why dont consider this? Комментарий от : @DisKeda |
 | me encanta Комментарий от : @luciafabra9084 |
 | 1:49 anyone gonna talk about how cute that pi are? Комментарий от : @decract |
 | Obvelyngetteltn Комментарий от : @user-pr6ed3ri2k |
| Bmobbldtn Комментарий от : @user-pr6ed3ri2k |
| Thelogntlargelnt Yt crash when send Комментарий от : @user-pr6ed3ri2k |
 | After watching this video again, I am curious how the regulations of the government (in the Netherlands, for example) would look like in these models. as an example: that you start with the standard situation and then implement hygiene and social distancing. then the quarantine, vaccine and reopening of social destinations. all in the order of the regulation that took place and then put that model next to the observed data. Комментарий от : @matshermens8988 |
 | would it be possible to show me how you coded these? Комментарий от : @conordolan7002 |
 | Once I get the chance I will make a game out of this idea, so you can play as a suspectible person and try and avoid the virus or be an infectious one and try to spread the disease Комментарий от : @maceleemasci9444 |
 | I am curious what would happen in the simulation if the Removed units became Susceptible again after a certain period of time, as is what happened in the real world. I had covid twice in a row with a break in between. Whole family was bouncing it around while we were isolated. I bet it would just exaggerate or drag on the curves we saw in this video, except in the simulations with proper contact tracing and isolation. Комментарий от : @jeeves31415 |
 | this has aged really, really poorly lmao Комментарий от : @darkkupo5162 |
 | Thank you very much. 😊 Комментарий от : @martinoblues |
 | China took some inspiration Комментарий от : @FreeDerry |
 | This video inspired me to make my own infection code on Khan Academy. Комментарий от : @bennyl9228 |
 | I guess removed can mean two things, you got immune or you are dead. And that is solely up to the type of virus and how it works. Great explanation! Комментарий от : @sanjinred |
 | Could you do a follow-up that includes animal reservoirs as a method of incubation and its possible effect on proliferation? Or the odds that a portion of the population would not be immune after contracting the virus, therefore not placed into the "recovered/removed" category? Mutations that make immune people susceptible again? My gut feeling is that those factors would effectively result in an inability to ever fully eradicate it. Комментарий от : @cdmcfall |
 | 5,065,282nd view. Комментарий от : @simonsloth1306 |
 | A virus is God's way of telling you idiots that you're going about your business wrong. You reap what you sow including the irony of not being able to recognize the solution. Комментарий от : @danielbloom2470 |
 | Nice model. It is overly simplistic and incomplete. It applies to every virus regardless of severity. It doesn't take into account the way our immune systems actually work or the way viral load factors into something being an outbreak vs an endemic spread of a mild contagion, and it doesn't model how a relatively mild virus spreads in population of people with robust immune systems who aren't afraid of germs. Using models like this to justify infringing on people's rights is a dangerous game and I hate everything about it. Комментарий от : @awsomenesscaleb |
 | Gotta ask, what say you now? Bahahaha Комментарий от : @A55Hol3_Actual |
 | Solution: Replace your assumed value (= guess) for P (probability of infection by being in a certain radius of a so-called 'infectious' person ), by my assumed value, 0 (zero) Комментарий от : @TheAverageOne178 |
 | 15:49 Комментарий от : @samcutter7042 |
 | 2:13 R ≈ π Комментарий от : @exyr8013 |
 | 0:35 central Location / Grocery or store. Комментарий от : @Canvas58027 |
 | 22:30 I'm pessimistic about it because I already lost faith in humanity. Комментарий от : @floppy8568 |
 | It's too bad people aren't exactly the same and have different immune systems to handle the problem Комментарий от : @terryhughes7196 |
 | Gotta love the people in the comment section that now think that mathematics itself is a Jewish conspiracy just so they can hold onto their crazy beliefs. Either these people don't remember what they say in-between clauses, or they don't care about truth in the slightest. Anyway, really interesting vid. Комментарий от : @fotnite_ |
 | i love how the 50 percent social distancing is literally just america Комментарий от : @skyrotechnics3245 |
 | looking through this video and i see all the things we did wrong. but couldn't prevent. 1. not every social distanced. 2. people need food and water thus stores had to stay open. (yes we had rules in effect to try and slow/prevent infection but that doesn't mean much when an infected person walks in coughing up a storm without any prevenitive measure in place) 3. Testing was to broad you could have been infected and already passed the effects but still test positive from it. (i heard it was 9 months) and alot of other things as the news got old and people just stopped caring. Комментарий от : @DaMetaEX |
 | There needs to be a component where during social distancing the rate of other diseases increases and so does suicide so that is relevant to the removed or dead component . Комментарий от : @noompsieOG |
 | Australia saw the isolation box, and was like, hold my beer. Комментарий от : @joshuavanzyl6536 |
 | Uh Комментарий от : @deleted-something |
 | Thanks for this video! Комментарий от : @khannansundar6914 |
 | I hate how generalized this algorithm is. Each action is infinitely complex, having variable we do not know. I wish you would have done a better job of demonstrating the actions one takes to infect, remove, or move around. Комментарий от : @justinfleagle |
 | I remember watching this two years ago and getting to the part about how letting up quarantine too early just causes a second, possibly larger, wave and thinking "Oh. That sounds horrible." As it turns out (two years later) I was right. That is completely horrible. Комментарий от : @nblack2867 |
 | 2022 and MANY people cheated on lockdowns. Very similar to your simulation. :( Комментарий от : @seandonnelly5338 |
 | covid won. Комментарий от : @xxjackirblackbloddxx7377 |
 | Alterenate title: What NOT to do when playing Plauge Inc. Комментарий от : @StarGarnet03 |
 | Did anyone include the virtual pandemic of World of Warcraft? Комментарий от : @BrainPermaDeD |
 | Very nice, love your videos, BUT here these models are just false for covid: experimentally it has been observed that the WAVES WERE CAUSED BY VARIANTS/mutants and not at all or just marginally because of social distancing stopping. In 2022 we now observed that immunity is lost very fast, and that cross immunity is weak from one variant to the next. The real mechanism for a covid wave extinction is still not a scientific consensus: the heard immunity, either natural or by vaccine is not the only candidate to explain the wave stopping. Very detailled PCR observations over the last 2 years are strongly suggesting that a variant is genetically weakened during its propagation/replication until it is unable to propagate anymore, thus stopping the wave. And also that eventually new variants comes from recombinations, not really mutations. And also that animals such as furets and felines are now endemic reservoirs. All those new experimental facts are game changer for this kind of mathematical models interpretation. The parameters of those SEIR models are very off, the models are forced to fit the real epidemics plot but is is just a false positive result. This is well know issue in chemical kinetics or plasma kinetics models. Sad that the majority of epidemilogists still refuse to admit their errors. Thanks again for your videos. Комментарий от : @poloceccati |
 | I'd be interested to see how re-infection and increased contagiousness of variants impact these models Комментарий от : @michaelessig6376 |
 | The Deep State has been telling you what they were going to do the whole time. You just weren't paying attention. Комментарий от : @jonn443 |
 | the biggest mistake humanity do is as soon as daily infection drops down every one go yo their normal life 21:18 **this what causes 500 000 000 cases global wind Комментарий от : @ziadalaoui2461 |
 | I think an important take away from this is that these measures, at the rates they can feasibly be implemented without destroying more lives than the virus itself, aren't as effective as advertised... 50% social distancing has almost the exact same effect as 90% social distancing. It is unbearable societal change for exponentially diminishing returns... it would explain why neighboring cities with radically different social distancing and lockdown policies showed almost no difference in contagion rates... we blew up whole economies for basically nothing. Комментарий от : @matheusadornidardenne8684 |
 | 1:49! Is that really good stuff😆😆 Комментарий от : @rapro9037 |
 | This was very cool, there are other factors that I wish were tested, like a vaccine, or people more vulnerable/resistant to the virus, or even the virus mutating over time. These factors would make things much more complex, but would be cool to test. Комментарий от : @trevorchilds1960 |
 | I like your toy model. Ideas I would suggest: Splitting the R group into a green Recovered group and a gray Deceased group. Green is temporary and wears off after some time. When a green person gets pinged by a red or yellow person, their timer resets. If they don't get pinged in long enough time, they go back to being blue. This represents novel strains evolving. Someone constantly exposed to the disease through the evolution of the novel strain maintains their immunity to the evolving strain, while someone who hasn't been exposed in a while becomes susceptible to those changes. And any yellow people will of course become green instead of gray when the infection runs its course, since not having symptoms means they won't die. And you could make the rate at which people turn green or gray after being red depend on how full the hospitals are at any moment. Red people who are at risk of dying turn purple, and if they can get into a hospital they have a very good chance to turn green and leave the hospital. But if they can't then they have a very high risk to turn gray. This makes it actually matter if there's a long tail or not, and can help compare what approaches are best given that the goal is to minimize the total number of times that people turn purple. It may turn out that various means of "slowing the spread" end up being detrimental in the long run because you're allowing the strain to avoid burning itself out for longer, so people recover and survive long enough to lose their immunity and get infected again. Комментарий от : @williambarnes5023 |
 | Thanks! Комментарий от : @kennethlau24 |
 | 이제 오미크론 덕분(?)에 감염자가 많아지고 치명률은 낮아졌네요. 빨리 이 코로나 사태가 종식 되는 날이 오길... Комментарий от : @utimezgd |
 | From Belgium we had really poor result against covid and it's easy to explain why : - A tiny area with many people. - Old population. - A lot of obesity. - Extremely good transports, you can reach all key cities by trains (and it's quick because most cities merge to eachothers). - Many neighboors from France, Germany, Netherlands, Luxembourg that work or study in Belgium. - Students use to come back to their familly during weekends. - Social distance was almost impossible for students that lives in the same house, they only have 1 kitchen or 1 toilet for 3 or 4 student. - Cold country and the covid arrived during the first warm week of the year. - Many covid cases in the cold season, which mean 80% of the year when people doesn't see the sun and get cold even without covid. - When it's cold this is hard to open windows - Chrismast is something important. - Europe center, people from everywhere travel and cross the country with trucks and cars, Brussels airport is also a big point. We tried everything possible but the stats are terrible, in fact it was impossible to do better, because there is no way to close a country like that, Belgium isn't self sufficent and the geography doesn't help, there is no mountains or anything, also Anvers is the second biggest port of Europe after Amsterdam, both a close to eachothers, the covid was there for sure Комментарий от : @FoXMaSteR001 |
 | Really you are very very intelligent . I am PhD student in mathematical modeling so I want to join your team and do with you Thank you Комментарий от : @jemalmuhammed1009 |
 | Still can't believe that it's been 2 years Комментарий от : @ikaz |
 | What is the tech stack? Was this made in JavaScript? Комментарий от : @rayhanali1041 |
 | Great simulation. Is it possible to have a table of values for SIR. I would like my students to use your simulator to run experiments by investigating a variable. By having values it will help students compare the independent variable by comparing SIR after a certain number of steps. Thanks. Комментарий от : @JimmyDundon |
 | covid19 the greatest scam put over on the American people since the usurper obama was put over on us Комментарий от : @azumpire |
 | Profissionalismo no mais alto grau e expertise de gráficos de alta performance, nunca vi nada parecido. Комментарий от : @carlosdeciobraga270 |
 | 17:58 "It's not a bug, it's a feature" Storytelling done by an error in your code. Nice. 👌🏽 Комментарий от : @Tepalus |
 | Based on differential equations, strict measures only postpone deaths to the future unless an effective vaccine is invented. All those people who defend and propose useless measures are either pure idiot or malevolent. Their degrees and licenses should be immediately revoked, they should never be given right to provide any opinion on public issues again. Комментарий от : @gokmenoktem87 |
 | Little just a way to explain the best strategy in plague inc Комментарий от : @Akniy |
 | Now simulate a world war Комментарий от : @davidnunes8336 |
 | this failed to predict conspiracy theories Комментарий от : @theidioticbgilson1466 |
 | Are you releasing those that are quarantined after a certain time? Комментарий от : @grandhisridevi6755 |
 | there is/was no pandemic....there was/is no diagnostic test....no metrics exists/existed....valid statistically analysis/studies were not conducted....the real pandemic was the daily reporting of useless pcr results and msm propaganda (operation mockingbird)....as for vaccines.....well, if you did not do a little research, it is your fault.......whats with all the new pharma ads about hiv and children heart issues lately...... Комментарий от : @jaym48 |
| I ran into this because I was looking at your Bayes' Theorem videos. However, it's now 2 years later. It's remarkable (or, as someone below put it, "ridiculous," how prescient this ended up being. It's so clear which paths we followed and how it ended up being just like you predicted. Комментарий от : @docpelletier6630 |
 | watching this March 2nd, 2022...still masking, still distancing, still monitoring variants. sigh. Комментарий от : @bricky-brikson9487 |
 | That's why China insists on choosing the reasonable way to prevent the disease. The video also mentions two things, which is exactly why the world needs to do it together. Population movements are inevitable and will get a backlash if the disease cannot be completely eradicated. Комментарий от : @zhwknight |
 | Hi! I'm working on my master thesis right now. (Working on the transmission of African Swine Fever in domestic swine populations) Could you share with me how you illustrated the data? What software did you use? I'd love to have some insight on this since I'm new to this field! Комментарий от : @MsMamorkuchen |
 | 11:25 Top-right graph read the way corona played out like a book. 90% of the population actually followed the regulations, the other part either made up some dumb excuse or was actually exempt from it somehow. Комментарий от : @hjag-is-also-ourplebop |
 | No politics. Simply science. I love this guy so much Комментарий от : @flubberdoodles2836 |
 | We need an update to this with the new "immunity only last 6 months version" to better represent covid as we know it today. We now know catching covid or getting vaccinated is only a temporary protection. Комментарий от : @TheFinagle |
 | Can we get access to the code? This is truly amazing... Комментарий от : @ayomikunawoseyi5226 |
 | the escaping dots were hilarious Комментарий от : @jerryy147 |
| 3blue1brow4what? 1what? 5what? 9what? 2what? 6what? 5what? 3what? 5what? 8what? 9what? 7what? 9what? 3what? 2what? 3what? 8what? 4what? 6what? 2what? Комментарий от : @jerryy147 |
 | 1:44 I always give my wife a goodbye sneeze when I step out for the day, and a slightly more sensual sneeze when I'm back after a long and tiresome day, when I'm so glad I get to spend time with someone always lights my fire. Комментарий от : @LordMarcus |
 | The government doesn’t have the facilities to quarantine the population! Hospitals and sports arenas! That’s just contaminating a public space! Комментарий от : @michaels3535 |
 | can you show how to make these kinds of simulations? Комментарий от : @newusernamelol6579 |
 | Its just amazing how you use SIR epidemic model to demonstrate different scenarios in epidemic. Did you use Agent based modeling to this simulation. Комментарий от : @ShyamDas999 |
 | If every person on earth could've watched and internalized the concepts presented in this video hundreds of thousands of lives could've been saved Комментарий от : @Philposting |
 | Informative but concerning video considering my province is about to lift all Covid restrictions and I don't see how the worst case modelling doesn't take off... Комментарий от : @ikeicer |
 | Sadpi.exe Комментарий от : @IAMASTICKSTUPIDPERSON |
 | A remake of this including re-infections would be super interesting Комментарий от : @redaxxx |
 | How are you making these amazing Animation/Simulations? Комментарий от : @canlevi8209 |
 | What packages/programming language was used in this? WOW I want to model like this Комментарий от : @retinapeg1846 |
 | Two words... Well Done! Комментарий от : @geosalatast5715 |
 | I wish more account had been given to science in choice-making during this pandemic Комментарий от : @armando4249 |
 | I wish everyone in the world saw this Комментарий от : @olivercollard8767 |
 | I saw this excellent video in March 2020, and in retrospect it was strikingly precise. I have seen all the mechanisms described during the pandemic. It would be interesting with a follow up video, now that Covid-19 has turned into something better described by an SIRS model. Комментарий от : @mortenballing1954 |
 | We need a model with 30% idiots in it Комментарий от : @chrishunter1109 |
 | You should simulate this with new people being born who don’t have immunity Комментарий от : @kevinward1538 |
 | you clearly didn't think about new scares, i mean variants Комментарий от : @ramsesbams |
 | Hello. The video is excellent. Question: Have you considered that if we could give a logarithmic growth answer to an equal growth problem that would be great? A contagious vaccine, for example. I would like to see the simulation of how the vaccination plan progresses with respect to the growth of infected. Can it be done or have you published it? Greetings. Jorge. Комментарий от : @jorgehugofigueroa |
 | What would R be for a pandemic? Комментарий от : @FutureAIDev2015 |
 | I did a similar personal project on this SIR model, too - now when I saw your video, I was relieved "what I did was right". I've watched a lot of your videos and always find them mind-blowing. Just one thing to comment on - when you talked about the novel pathogen, you used an icon of bacteriophage. I would avoid using this icon because bacteriophage has been used to develop vaccines; if such vaccines succeed, people will see the image of bacteriophage everywhere, and some might be confused whether they're good or harmful. Комментарий от : @drgothmania |
 | could you redo some simulations but this time include that number of recovered is not fixed? what i mean is that as we see today duo to mutation recovered do succumb to being reinfected and spread it to others. wonderfully complex would be to include random factor of successful mutations that appered and overtake the previous virus generations. but even just the first part where number of 'removed' is not fixed would be an interesting one to see. Комментарий от : @japanskakaratemuva5309 |
 | I don’t know why I’m watching math. But these vids are beautiful and a work of art! Комментарий от : @pavankolachoor6929 |
 | Thanks! Комментарий от : @yongmrchen |
 | 3Blue1Brown doing people's whole Bachelors paper as a video in a series :P Комментарий от : @sethnielsen3325 |
