What Happens Next? COVID-19 Futures, Explained With Playable Simulations @@ -119,7 +126,7 @@
It's estimated that, at the start of a COVID-19 outbreak, the virus jumps from an
If we simulate "double every 4 days" and nothing else, on a population starting with just 0.001%
If we simulate "double every 4 days" and nothing else, on a population starting with just 0.001%
Click "Start" to play the simulation! You can re-play it later with different settings: (technical caveats: 3)
@@ -135,7 +142,7 @@
The more
The more
How's this change the growth of an epidemic? Let's find out:
@@ -147,9 +154,9 @@But, this simulation is still wrong. We're missing the fact that
For simplicity's sake, let's pretend that all
For simplicity's sake, let's pretend that all
With COVID-19, it's estimated you're
With COVID-19, it's estimated you're
Let's find out.
-Red curve is current cases
- Gray curve is total cases (current + recovered
Red curve is current cases
+ Gray curve is total cases (current + recovered
NOTE: The simulations that inform policy are way, way more sophisticated than this! But the SIR Model can still explain the same general findings, even if missing the nuances.
-Actually, let's add one more nuance: before an
Actually, let's add one more nuance: before an
For COVID-19, it's estimated that you're
Red + Pink curve is current cases (infectious
- Gray curve is total cases (current + recovered
Red + Pink curve is current cases (infectious
+ Gray curve is total cases (current + recovered
Not much changes! How long you stay
Not much changes! How long you stay
Why's that? Because of the first-most important idea in Epidemiology 101:
@@ -224,7 +231,7 @@But remember, the fewer
But remember, the fewer
NOTE: Total cases does not stop at herd immunity, but overshoots it! And it crosses the threshold exactly when current cases peak. (This happens no matter how you change the settings – try it for yourself!)
-This is because when there are more non-
This is because when there are more non-
If there's only one lesson you take away from this guide, here it is – it's an extremely complex diagram so please take time to fully absorb it:
@@ -300,7 +307,7 @@Increased handwashing cuts flus & colds in high-income countries by ~25%16, while the city-wide lockdown in London cut close contacts by ~70%17. So, let's assume handwashing can reduce R by up to 25%, and distancing can reduce R by up to 70%:
-Play with this calculator to see how % of non-
Play with this calculator to see how % of non-
Oh.
-This is the "second wave" everyone's talking about. As soon as we remove the lockdown, we get R > 1 again. So, a single leftover
This is the "second wave" everyone's talking about. As soon as we remove the lockdown, we get R > 1 again. So, a single leftover
A lockdown isn't a cure, it's just a restart.
@@ -388,7 +395,7 @@This is called contact tracing. It's an old idea, was used at an unprecedented scale to contain Ebola23, and now it's core part of how Taiwan & South Korea are containing COVID-19!
-(It also lets us use our limited tests more efficiently, to find pre-symptomatic
(It also lets us use our limited tests more efficiently, to find pre-symptomatic
Traditionally, contacts are found with in-person interviews, but those alone are too slow for COVID-19's ~48 hour window. That's why contact tracers need help, and be supported by – NOT replaced by – contact tracing apps.
@@ -402,15 +409,15 @@
(Here's the full comic. Details about "pranking"/false positives/etc in footnote:24)
-Along with similar teams like TCN Protocol24 and MIT PACT25, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.26 (Don't trust Google/Apple? Good! The beauty of this system is it doesn't need trust!) Soon, your local public health agency may ask you to download an app. If it's privacy-first with publicly-available code, please do!
+Along with similar teams like TCN Protocol25 and MIT PACT26, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.27 (Don't trust Google/Apple? Good! The beauty of this system is it doesn't need trust!) Soon, your local public health agency may ask you to download an app. If it's privacy-first with publicly-available code, please do!
But what about folks without smartphones? Or infections through doorknobs? Or "true" asymptomatic cases? Contact tracing apps can't catch all transmissions... and that's okay! We don't need to catch all transmissions, just 60%+ to get R < 1.
-(Rant about the confusion about pre-symptomatic vs "true" asymptomatic. "True" asymptomatics are rare:27)
+(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:28)
-Isolating symptomatic cases would reduce R by up to 40%, and quarantining their pre/a-symptomatic contacts would reduce R by up to 50%28:
+Isolating symptomatic cases would reduce R by up to 40%, and quarantining their pre/a-symptomatic contacts would reduce R by up to 50%29:
Thus, even without 100% contact quarantining, we can get R < 1 without a lockdown! Much better for our mental & financial health. (As for the cost to folks who have to self-isolate/quarantine, governments should support them – pay for the tests, job protection, subsidized paid leave, etc. Still way cheaper than intermittent lockdown.)
-We then keep R < 1 until we have a vaccine, which turns susceptible
We then keep R < 1 until we have a vaccine, which turns susceptible
"Wait," you might ask, "I thought face masks don't stop you from getting sick?"
-You're right. Masks don't stop you from getting sick29... they stop you from getting others sick.
+You're right. Masks don't stop you from getting sick30... they stop you from getting others sick.
To put a number on it: surgical masks on the sick person reduce cold & flu viruses in aerosols by 70%.30 Reducing transmissions by 70% would be as large an impact as a lockdown!
+To put a number on it: surgical masks on the infectious person reduce cold & flu viruses in aerosols by 70%.31 Reducing transmissions by 70% would be as large an impact as a lockdown!
-However, we don't know for sure the impact of masks on COVID-19 specifically. In science, one should only publish a finding if you're 95% sure of it. (...should.31) Masks, as of May 1st 2020, are less than "95% sure".
+However, we don't know for sure the impact of masks on COVID-19 specifically. In science, one should only publish a finding if you're 95% sure of it. (...should.32) Masks, as of May 1st 2020, are less than "95% sure".
-However, pandemics are like poker. Make bets only when you're 95% sure, and you'll lose everything at stake. As a recent article on masks in the British Medical Journal notes,32 we have to make cost/benefit analyses under uncertainty. Like so:
+However, pandemics are like poker. Make bets only when you're 95% sure, and you'll lose everything at stake. As a recent article on masks in the British Medical Journal notes,33 we have to make cost/benefit analyses under uncertainty. Like so:
-Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks33), super cheap. If surgical masks, more expensive but still pretty cheap.
+Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks34), super cheap. If surgical masks, more expensive but still pretty cheap.
Benefit: Even if it's a 50–50 chance of surgical masks reducing transmission by 0% or 70%, the average "expected value" is still 35%, same as a half-lockdown! So let's guess-timate that surgical masks reduce R by up to 35%, discounted for our uncertainty. (Again, you can challenge our assumptions by turning the sliders up/down)
@@ -477,7 +484,7 @@(other arguments for/against masks:34)
+(other arguments for/against masks:35)
Masks alone won't get R < 1. But if handwashing & "Test, Trace, Isolate" only gets us to R = 1.10, having just 1/3 of people wear masks would tip that over to R < 1, virus contained!
@@ -485,7 +492,7 @@Okay, this isn't an "intervention" we can control, but it will help! Some news outlets report that summer won't do anything to COVID-19. They're half right: summer won't get R < 1, but it will reduce R.
-For COVID-19, every extra 1° Celsius (2.2° Fahrenheit) makes R drop by 1.2%.35 The summer-winter difference in New York City is 15°C (60°F), so summer will make R drop by 18%.
+For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.36 The summer-winter difference in New York City is 26°C (47°F),37 so summer will make R drop by ~31%.
But we wouldn't have to be 2-months-closed / 1-month-open over & over! Because R is reduced, we'd only need one or two more "circuit breaker" lockdowns before a vaccine is available. (Singapore had to do this recently, "despite" having controlled COVID-19 for 4 months. That's not failure: this is what success takes.)
-Here's a simulation a "lazy case" scenario:
+Here's a simulation of a "lazy case" scenario:
- Lockdown, then @@ -545,16 +552,16 @@
- COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.36 -
- The coronaviruses that cause "the" common cold give you 8 months of immunity.37 -
- There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.38 -
- One not-yet-peer-reviewed study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.39 +
- COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.38 +
- The coronaviruses that cause "the" common cold give you 8 months of immunity.39 +
- There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.40 +
- One not-yet-peer-reviewed study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.41
...for how long?
-
-
But for COVID-19 in humans, as of May 1st 2020, "how long" is the big unknown.
For these simulations, let's say it's 1 year.
- Here's a simulation starting with 100%
Oh.
-Counterintuitively, summer makes the spikes worse and regular! This is because summer reduces new
Counterintuitively, summer makes the spikes worse and regular! This is because summer reduces new
Thankfully, the solution to this is pretty straightforward – just vaccinate people every fall/winter, like we do with flu shots:
@@ -600,7 +607,7 @@To be clear: this is unlikely. Most epidemiologists expect a vaccine in 1 to 2 years. Sure, there's never been a vaccine for any of the other coronaviruses before, but that's because SARS was eradicated quickly, and "the" common cold wasn't worth the investment.
-Still, infectious disease researchers have expressed worries: What if we can't make enough?40 What if we rush it, and it's not safe?41
+Still, infectious disease researchers have expressed worries: What if we can't make enough?42 What if we rush it, and it's not safe?43
Even in the nightmare "no-vaccine" scenario, we still have 3 ways out. From most to least terrible:
@@ -639,7 +646,7 @@Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.42
+Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.44
Teams of epidemiologists and policymakers (left, right, and multi-partisan) have come to a consensus on how to beat COVID-19, while protecting our lives and liberties.
@@ -778,27 +785,35 @@Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol ↩
+To prevent "pranking" (people falsely claiming to be infected), the DP-3T Protocol requires that the hospital first give you a One-Time Passcode that lets you upload your messages. ↩
+ +False positives are a problem in both manual & digital contact tracing. Still, we can reduce false positives in 2 ways: 1) By notifying Bobs only if they heard, say, 30+ min worth of messages, not just one message in passing. And 2) If the app does think Bob's been exposed, it can refer Bob to a manual contact tracer, for an in-depth follow-up interview.
+ +For other issues like data bandwidth, source integrity, and other security issues, check out the open-source DP-3T whitepapers!
PACT: Private Automated Contact Tracing ↩
+Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol ↩
Apple and Google partner on COVID-19 contact tracing technology . Note they're not making the apps themselves, just creating the systems that will support those apps. ↩
+Lots of news reports – and honestly, many research papers – did not distinguish between "cases who showed no symptoms when we tested them" (pre-symptomatic) and "cases who showed no symptoms ever" (true asymptomatic). The only way you could tell the difference is by following up with cases later. ↩
+Apple and Google partner on COVID-19 contact tracing technology . Note they're not making the apps themselves, just creating the systems that will support those apps. ↩
+Lots of news reports – and honestly, many research papers – did not distinguish between "cases who showed no symptoms when we tested them" (pre-symptomatic) and "cases who showed no symptoms ever" (true asymptomatic). The only way you could tell the difference is by following up with cases later. ↩
Which is what this study did. (Disclaimer: "Early release articles are not considered as final versions.") In a call center in South Korea that had a COVID-19 outbreak, "only 4 (1.9%) remained asymptomatic within 14 days of quarantine, and none of their household contacts acquired secondary infections."
So that means "true asymptomatics" are rare, and catching the disease from a true asymptomatic may be even rarer!
From the same Oxford study that first recommended apps to fight COVID-19: Luca Ferretti & Chris Wymant et al See Figure 2. Assuming R0 = 2.0, they found that: ↩
+From the same Oxford study that first recommended apps to fight COVID-19: Luca Ferretti & Chris Wymant et al See Figure 2. Assuming R0 = 2.0, they found that: ↩
- Symptomatics contribute R = 0.8 (40%) @@ -810,64 +825,68 @@
And add up the pre- & a-symptomatic contacts (45% + 5%) and you get 50% of R!
“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” Tara Oberg & Lisa M. Brosseau ↩
-“The overall 3.4 fold reduction [70% reduction] in aerosol copy numbers we observed combined with a nearly complete elimination of large droplet spray demonstrated by Johnson et al. suggests that surgical masks worn by infected persons could have a clinically significant impact on transmission.” Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ ↩
+“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” Tara Oberg & Lisa M. Brosseau ↩
Any actual scientist who read that last sentence is probably laugh-crying right now. See: p-hacking, the replication crisis) ↩
+“The overall 3.4 fold reduction [70% reduction] in aerosol copy numbers we observed combined with a nearly complete elimination of large droplet spray demonstrated by Johnson et al. suggests that surgical masks worn by infected persons could have a clinically significant impact on transmission.” Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ ↩
“It is time to apply the precautionary principle” Trisha Greenhalgh et al [PDF] ↩
+Any actual scientist who read that last sentence is probably laugh-crying right now. See: p-hacking, the replication crisis) ↩
Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A See Table 1: a 100% cotton T-shirt has around 2/3 the filtration efficiency as a surgical mask, for the two bacterial aerosols they tested. ↩
+“It is time to apply the precautionary principle” Trisha Greenhalgh et al [PDF] ↩
"We need to save supplies for hospitals." Absolutely agreed. But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. ↩
+Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A See Table 1: a 100% cotton T-shirt has around 2/3 the filtration efficiency as a surgical mask, for the two bacterial aerosols they tested. ↩
+"We need to save supplies for hospitals." Absolutely agreed. But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. ↩
"They're hard to wear correctly." It's also hard to wash your hands according to the WHO Guidelines – seriously, "Step 3) right palm over left dorsum"?! – but we still recommend handwashing, because imperfect is still better than nothing.
"It'll make people more reckless with handwashing & social distancing." Sure, and safety belts make people ignore stop signs, and flossing makes people eat rocks. But seriously, we'd argue the opposite: masks are a constant physical reminder to be careful – and in East Asia, masks are also a symbol of solidarity!
“One-degree Celsius increase in temperature [...] lower[s] R by 0.0225” and “The average R-value of these 100 cities is 1.83”. 0.0225 ÷ 1.83 = ~1.2%. Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng ↩
-“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” Wu LP, Wang NC, Chang YH, et al. "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. ↩
+“One-degree Celsius increase in temperature [...] lower[s] R by 0.0225” and “The average R-value of these 100 cities is 1.83”. 0.0225 ÷ 1.83 = ~1.2%. Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng ↩
“We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the beta-coronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection.” Marta Galanti & Jeffrey Shaman (PDF) ↩
+In 2019 at Central Park, hottest month (July) was 79.6°F, coldest month (Jan) was 32.5°F. Difference is 47.1°F, or ~26°C. PDF from Weather.gov ↩
“Once a person fights off a virus, viral particles tend to linger for some time. These cannot cause infections, but they can trigger a positive test.” from STAT News by Andrew Joseph ↩
+“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” Wu LP, Wang NC, Chang YH, et al. "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. ↩
From Bao et al. Disclaimer: This article is a preprint and has not been certified by peer review (yet). Also, to emphasize: they only tested re-infection 28 days later. ↩
+“We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the beta-coronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection.” Marta Galanti & Jeffrey Shaman (PDF) ↩
“If a coronavirus vaccine arrives, can the world make enough?” by Roxanne Khamsi, on Nature ↩
+“Once a person fights off a virus, viral particles tend to linger for some time. These cannot cause infections, but they can trigger a positive test.” from STAT News by Andrew Joseph ↩
“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” by Shibo Jiang, on Nature ↩
+From Bao et al. Disclaimer: This article is a preprint and has not been certified by peer review (yet). Also, to emphasize: they only tested re-infection 28 days later. ↩
Dry land metaphor from Marc Lipsitch & Yonatan Grad, on STAT News ↩
+“If a coronavirus vaccine arrives, can the world make enough?” by Roxanne Khamsi, on Nature ↩
+“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” by Shibo Jiang, on Nature ↩
+Dry land metaphor from Marc Lipsitch & Yonatan Grad, on STAT News ↩
This guide is
diff --git a/sim/index.html b/sim/index.html index 1bad274..a4496d1 100644 --- a/sim/index.html +++ b/sim/index.html @@ -96,7 +96,7 @@
- Лето + Сила лета
diff --git a/sim/js/Model.js b/sim/js/Model.js index 72d4c1f..3631637 100644 --- a/sim/js/Model.js +++ b/sim/js/Model.js @@ -25,8 +25,8 @@ let interventionStrengths = [ ['distancing', 0.7], ['isolate', 0.4], ['quarantine', 0.5], - ['masks', 0.35], // 3.4 fold reduction (70%) (what CI?), subtract points for... improper usage? https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591312/ // cloth masks... - ['summer', 0.4] // 15°C diff * 0.0225 (Wang et al) + ['masks', 0.35], + ['summer', 0.31] // ACK ]; let updateModel = (days, fake)=>{ diff --git a/words/words.html b/words/words.html index 396aa37..755c833 100644 --- a/words/words.html +++ b/words/words.html @@ -69,7 +69,7 @@
It's estimated that, at the start of a COVID-19 outbreak, the virus jumps from an
If we simulate "double every 4 days" and nothing else, on a population starting with just 0.001%
If we simulate "double every 4 days" and nothing else, on a population starting with just 0.001%
Click "Start" to play the simulation! You can re-play it later with different settings: (technical caveats: 3)
@@ -85,7 +85,7 @@
The more
The more
How's this change the growth of an epidemic? Let's find out:
@@ -97,9 +97,9 @@But, this simulation is still wrong. We're missing the fact that
For simplicity's sake, let's pretend that all
For simplicity's sake, let's pretend that all
With COVID-19, it's estimated you're
With COVID-19, it's estimated you're
Let's find out.
-Red curve is current cases
-Gray curve is total cases (current + recovered
Red curve is current cases
+Gray curve is total cases (current + recovered
NOTE: The simulations that inform policy are way, way more sophisticated than this! But the SIR Model can still explain the same general findings, even if missing the nuances.
-Actually, let's add one more nuance: before an
Actually, let's add one more nuance: before an
For COVID-19, it's estimated that you're
Red + Pink curve is current cases (infectious
-Gray curve is total cases (current + recovered
Red + Pink curve is current cases (infectious
+Gray curve is total cases (current + recovered
Not much changes! How long you stay
Not much changes! How long you stay
Why's that? Because of the first-most important idea in Epidemiology 101:
@@ -174,7 +174,7 @@ the second-most important idea in Epidemiology 101:But remember, the fewer
But remember, the fewer
NOTE: Total cases does not stop at herd immunity, but overshoots it! And it crosses the threshold exactly when current cases peak. (This happens no matter how you change the settings – try it for yourself!)
-This is because when there are more non-
This is because when there are more non-
If there's only one lesson you take away from this guide, here it is – it's an extremely complex diagram so please take time to fully absorb it:
@@ -250,7 +250,7 @@ the second-most important idea in Epidemiology 101:Increased handwashing cuts flus & colds in high-income countries by ~25%16, while the city-wide lockdown in London cut close contacts by ~70%17. So, let's assume handwashing can reduce R by up to 25%, and distancing can reduce R by up to 70%:
-Play with this calculator to see how % of non-
Play with this calculator to see how % of non-
Oh.
-This is the "second wave" everyone's talking about. As soon as we remove the lockdown, we get R > 1 again. So, a single leftover
This is the "second wave" everyone's talking about. As soon as we remove the lockdown, we get R > 1 again. So, a single leftover
A lockdown isn't a cure, it's just a restart.
@@ -338,7 +338,7 @@ the second-most important idea in Epidemiology 101:This is called contact tracing. It's an old idea, was used at an unprecedented scale to contain Ebola23, and now it's core part of how Taiwan & South Korea are containing COVID-19!
-(It also lets us use our limited tests more efficiently, to find pre-symptomatic
(It also lets us use our limited tests more efficiently, to find pre-symptomatic
Traditionally, contacts are found with in-person interviews, but those alone are too slow for COVID-19's ~48 hour window. That's why contact tracers need help, and be supported by – NOT replaced by – contact tracing apps.
@@ -352,15 +352,15 @@ the second-most important idea in Epidemiology 101:
(Here's the full comic. Details about "pranking"/false positives/etc in footnote:24)
-Along with similar teams like TCN Protocol24 and MIT PACT25, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.26 (Don't trust Google/Apple? Good! The beauty of this system is it doesn't need trust!) Soon, your local public health agency may ask you to download an app. If it's privacy-first with publicly-available code, please do!
+Along with similar teams like TCN Protocol25 and MIT PACT26, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.27 (Don't trust Google/Apple? Good! The beauty of this system is it doesn't need trust!) Soon, your local public health agency may ask you to download an app. If it's privacy-first with publicly-available code, please do!
But what about folks without smartphones? Or infections through doorknobs? Or "true" asymptomatic cases? Contact tracing apps can't catch all transmissions... and that's okay! We don't need to catch all transmissions, just 60%+ to get R < 1.
-(Rant about the confusion about pre-symptomatic vs "true" asymptomatic. "True" asymptomatics are rare:27)
+(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:28)
-Isolating symptomatic cases would reduce R by up to 40%, and quarantining their pre/a-symptomatic contacts would reduce R by up to 50%28:
+Isolating symptomatic cases would reduce R by up to 40%, and quarantining their pre/a-symptomatic contacts would reduce R by up to 50%29:
Thus, even without 100% contact quarantining, we can get R < 1 without a lockdown! Much better for our mental & financial health. (As for the cost to folks who have to self-isolate/quarantine, governments should support them – pay for the tests, job protection, subsidized paid leave, etc. Still way cheaper than intermittent lockdown.)
-We then keep R < 1 until we have a vaccine, which turns susceptible
We then keep R < 1 until we have a vaccine, which turns susceptible
"Wait," you might ask, "I thought face masks don't stop you from getting sick?"
-You're right. Masks don't stop you from getting sick29... they stop you from getting others sick.
+You're right. Masks don't stop you from getting sick30... they stop you from getting others sick.
To put a number on it: surgical masks on the sick person reduce cold & flu viruses in aerosols by 70%.30 Reducing transmissions by 70% would be as large an impact as a lockdown!
+To put a number on it: surgical masks on the infectious person reduce cold & flu viruses in aerosols by 70%.31 Reducing transmissions by 70% would be as large an impact as a lockdown!
-However, we don't know for sure the impact of masks on COVID-19 specifically. In science, one should only publish a finding if you're 95% sure of it. (...should.31) Masks, as of May 1st 2020, are less than "95% sure".
+However, we don't know for sure the impact of masks on COVID-19 specifically. In science, one should only publish a finding if you're 95% sure of it. (...should.32) Masks, as of May 1st 2020, are less than "95% sure".
-However, pandemics are like poker. Make bets only when you're 95% sure, and you'll lose everything at stake. As a recent article on masks in the British Medical Journal notes,32 we have to make cost/benefit analyses under uncertainty. Like so:
+However, pandemics are like poker. Make bets only when you're 95% sure, and you'll lose everything at stake. As a recent article on masks in the British Medical Journal notes,33 we have to make cost/benefit analyses under uncertainty. Like so:
-Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks33), super cheap. If surgical masks, more expensive but still pretty cheap.
+Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks34), super cheap. If surgical masks, more expensive but still pretty cheap.
Benefit: Even if it's a 50–50 chance of surgical masks reducing transmission by 0% or 70%, the average "expected value" is still 35%, same as a half-lockdown! So let's guess-timate that surgical masks reduce R by up to 35%, discounted for our uncertainty. (Again, you can challenge our assumptions by turning the sliders up/down)
@@ -427,7 +427,7 @@ the second-most important idea in Epidemiology 101:(other arguments for/against masks:34)
+(other arguments for/against masks:35)
Masks alone won't get R < 1. But if handwashing & "Test, Trace, Isolate" only gets us to R = 1.10, having just 1/3 of people wear masks would tip that over to R < 1, virus contained!
@@ -435,7 +435,7 @@ the second-most important idea in Epidemiology 101:Okay, this isn't an "intervention" we can control, but it will help! Some news outlets report that summer won't do anything to COVID-19. They're half right: summer won't get R < 1, but it will reduce R.
-For COVID-19, every extra 1° Celsius (2.2° Fahrenheit) makes R drop by 1.2%.35 The summer-winter difference in New York City is 15°C (60°F), so summer will make R drop by 18%.
+For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.36 The summer-winter difference in New York City is 26°C (47°F),37 so summer will make R drop by ~31%.
But we wouldn't have to be 2-months-closed / 1-month-open over & over! Because R is reduced, we'd only need one or two more "circuit breaker" lockdowns before a vaccine is available. (Singapore had to do this recently, "despite" having controlled COVID-19 for 4 months. That's not failure: this is what success takes.)
-Here's a simulation a "lazy case" scenario:
+Here's a simulation of a "lazy case" scenario:
- Lockdown, then @@ -495,16 +495,16 @@ the second-most important idea in Epidemiology 101:
- COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.36 -
- The coronaviruses that cause "the" common cold give you 8 months of immunity.37 -
- There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.38 -
- One not-yet-peer-reviewed study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.39 +
- COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.38 +
- The coronaviruses that cause "the" common cold give you 8 months of immunity.39 +
- There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.40 +
- One not-yet-peer-reviewed study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.41
...for how long?
-
-
But for COVID-19 in humans, as of May 1st 2020, "how long" is the big unknown.
For these simulations, let's say it's 1 year.
-Here's a simulation starting with 100%
Oh.
-Counterintuitively, summer makes the spikes worse and regular! This is because summer reduces new
Counterintuitively, summer makes the spikes worse and regular! This is because summer reduces new
Thankfully, the solution to this is pretty straightforward – just vaccinate people every fall/winter, like we do with flu shots:
@@ -550,7 +550,7 @@ the second-most important idea in Epidemiology 101:To be clear: this is unlikely. Most epidemiologists expect a vaccine in 1 to 2 years. Sure, there's never been a vaccine for any of the other coronaviruses before, but that's because SARS was eradicated quickly, and "the" common cold wasn't worth the investment.
-Still, infectious disease researchers have expressed worries: What if we can't make enough?40 What if we rush it, and it's not safe?41
+Still, infectious disease researchers have expressed worries: What if we can't make enough?42 What if we rush it, and it's not safe?43
Even in the nightmare "no-vaccine" scenario, we still have 3 ways out. From most to least terrible:
@@ -589,7 +589,7 @@ the second-most important idea in Epidemiology 101:Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.42
+Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.44
Teams of epidemiologists and policymakers (left, right, and multi-partisan) have come to a consensus on how to beat COVID-19, while protecting our lives and liberties.
@@ -728,27 +728,35 @@ the second-most important idea in Epidemiology 101:Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol ↩
+To prevent "pranking" (people falsely claiming to be infected), the DP-3T Protocol requires that the hospital first give you a One-Time Passcode that lets you upload your messages. ↩
+ +False positives are a problem in both manual & digital contact tracing. Still, we can reduce false positives in 2 ways: 1) By notifying Bobs only if they heard, say, 30+ min worth of messages, not just one message in passing. And 2) If the app does think Bob's been exposed, it can refer Bob to a manual contact tracer, for an in-depth follow-up interview.
+ +For other issues like data bandwidth, source integrity, and other security issues, check out the open-source DP-3T whitepapers!
PACT: Private Automated Contact Tracing ↩
+Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol ↩
Apple and Google partner on COVID-19 contact tracing technology . Note they're not making the apps themselves, just creating the systems that will support those apps. ↩
+Lots of news reports – and honestly, many research papers – did not distinguish between "cases who showed no symptoms when we tested them" (pre-symptomatic) and "cases who showed no symptoms ever" (true asymptomatic). The only way you could tell the difference is by following up with cases later. ↩
+Apple and Google partner on COVID-19 contact tracing technology . Note they're not making the apps themselves, just creating the systems that will support those apps. ↩
+Lots of news reports – and honestly, many research papers – did not distinguish between "cases who showed no symptoms when we tested them" (pre-symptomatic) and "cases who showed no symptoms ever" (true asymptomatic). The only way you could tell the difference is by following up with cases later. ↩
Which is what this study did. (Disclaimer: "Early release articles are not considered as final versions.") In a call center in South Korea that had a COVID-19 outbreak, "only 4 (1.9%) remained asymptomatic within 14 days of quarantine, and none of their household contacts acquired secondary infections."
So that means "true asymptomatics" are rare, and catching the disease from a true asymptomatic may be even rarer!
From the same Oxford study that first recommended apps to fight COVID-19: Luca Ferretti & Chris Wymant et al See Figure 2. Assuming R0 = 2.0, they found that: ↩
+From the same Oxford study that first recommended apps to fight COVID-19: Luca Ferretti & Chris Wymant et al See Figure 2. Assuming R0 = 2.0, they found that: ↩
- Symptomatics contribute R = 0.8 (40%) @@ -760,64 +768,68 @@ the second-most important idea in Epidemiology 101:
And add up the pre- & a-symptomatic contacts (45% + 5%) and you get 50% of R!
“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” Tara Oberg & Lisa M. Brosseau ↩
-“The overall 3.4 fold reduction [70% reduction] in aerosol copy numbers we observed combined with a nearly complete elimination of large droplet spray demonstrated by Johnson et al. suggests that surgical masks worn by infected persons could have a clinically significant impact on transmission.” Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ ↩
+“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” Tara Oberg & Lisa M. Brosseau ↩
Any actual scientist who read that last sentence is probably laugh-crying right now. See: p-hacking, the replication crisis) ↩
+“The overall 3.4 fold reduction [70% reduction] in aerosol copy numbers we observed combined with a nearly complete elimination of large droplet spray demonstrated by Johnson et al. suggests that surgical masks worn by infected persons could have a clinically significant impact on transmission.” Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ ↩
“It is time to apply the precautionary principle” Trisha Greenhalgh et al [PDF] ↩
+Any actual scientist who read that last sentence is probably laugh-crying right now. See: p-hacking, the replication crisis) ↩
Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A See Table 1: a 100% cotton T-shirt has around 2/3 the filtration efficiency as a surgical mask, for the two bacterial aerosols they tested. ↩
+“It is time to apply the precautionary principle” Trisha Greenhalgh et al [PDF] ↩
"We need to save supplies for hospitals." Absolutely agreed. But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. ↩
+Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A See Table 1: a 100% cotton T-shirt has around 2/3 the filtration efficiency as a surgical mask, for the two bacterial aerosols they tested. ↩
+"We need to save supplies for hospitals." Absolutely agreed. But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. ↩
"They're hard to wear correctly." It's also hard to wash your hands according to the WHO Guidelines – seriously, "Step 3) right palm over left dorsum"?! – but we still recommend handwashing, because imperfect is still better than nothing.
"It'll make people more reckless with handwashing & social distancing." Sure, and safety belts make people ignore stop signs, and flossing makes people eat rocks. But seriously, we'd argue the opposite: masks are a constant physical reminder to be careful – and in East Asia, masks are also a symbol of solidarity!
“One-degree Celsius increase in temperature [...] lower[s] R by 0.0225” and “The average R-value of these 100 cities is 1.83”. 0.0225 ÷ 1.83 = ~1.2%. Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng ↩
-“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” Wu LP, Wang NC, Chang YH, et al. "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. ↩
+“One-degree Celsius increase in temperature [...] lower[s] R by 0.0225” and “The average R-value of these 100 cities is 1.83”. 0.0225 ÷ 1.83 = ~1.2%. Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng ↩
“We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the beta-coronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection.” Marta Galanti & Jeffrey Shaman (PDF) ↩
+In 2019 at Central Park, hottest month (July) was 79.6°F, coldest month (Jan) was 32.5°F. Difference is 47.1°F, or ~26°C. PDF from Weather.gov ↩
“Once a person fights off a virus, viral particles tend to linger for some time. These cannot cause infections, but they can trigger a positive test.” from STAT News by Andrew Joseph ↩
+“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” Wu LP, Wang NC, Chang YH, et al. "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. ↩
From Bao et al. Disclaimer: This article is a preprint and has not been certified by peer review (yet). Also, to emphasize: they only tested re-infection 28 days later. ↩
+“We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the beta-coronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection.” Marta Galanti & Jeffrey Shaman (PDF) ↩
“If a coronavirus vaccine arrives, can the world make enough?” by Roxanne Khamsi, on Nature ↩
+“Once a person fights off a virus, viral particles tend to linger for some time. These cannot cause infections, but they can trigger a positive test.” from STAT News by Andrew Joseph ↩
“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” by Shibo Jiang, on Nature ↩
+From Bao et al. Disclaimer: This article is a preprint and has not been certified by peer review (yet). Also, to emphasize: they only tested re-infection 28 days later. ↩
Dry land metaphor from Marc Lipsitch & Yonatan Grad, on STAT News ↩
+“If a coronavirus vaccine arrives, can the world make enough?” by Roxanne Khamsi, on Nature ↩
+“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” by Shibo Jiang, on Nature ↩
+Dry land metaphor from Marc Lipsitch & Yonatan Grad, on STAT News ↩