italian translation and updated citations
This commit is contained in:
parent
2b7559325a
commit
835ef30800
3 changed files with 197 additions and 158 deletions
169
index.html
169
index.html
|
@ -44,12 +44,12 @@
|
|||
<li><a href='https://vrruiz.github.io/covid-19'>Español</a></li>
|
||||
<li><a href='https://leonardoalcantara.github.io/covid-19-pt-br/'>Português</a></li>
|
||||
<li><a href='https://tquev.github.io/covid-19/'>Deutsch</a></li>
|
||||
<li><a href='https://harisont.github.io/covid-19/'>Italiano</a></li>
|
||||
<li><a href='https://jusplathemus.github.io/covid-19/'>Magyar</a></li>
|
||||
<li><a href='https://saskaaloric.github.io/covid-19/'>Srpski</a></li>
|
||||
<li><a href='https://asherbarak.github.io/covid-19/'>עברית</a></li>
|
||||
<li><a href='https://benbennben.github.io/covid-19/'>한국어</a></li>
|
||||
<li><a href='https://eed3si9n.github.io/covid-19/'>日本語</a></li>
|
||||
<li><a href='https://harisont.github.io/covid-19/'>Italiano</a></li>
|
||||
</ul>
|
||||
<a href='https://github.com/ncase/covid-19#how-to-translate'>
|
||||
Help make a translation?
|
||||
|
@ -186,7 +186,7 @@
|
|||
|
||||
<p>And <em>that's</em> where that famous curve comes from! It's not a bell curve, it's not even a "log-normal" curve. It has no name. But you've seen it a zillion times, and beseeched to flatten.</p>
|
||||
|
||||
<p>This is the the <strong>SIR Model</strong>,<sup id="fnref5"><a href="#fn5" rel="footnote">5</a></sup><br>
|
||||
<p>This is the <strong>SIR Model</strong>,<sup id="fnref5"><a href="#fn5" rel="footnote">5</a></sup><br>
|
||||
(<icon s></icon><strong>S</strong>usceptible <icon i></icon><strong>I</strong>nfectious <icon r></icon><strong>R</strong>ecovered)<br>
|
||||
the <em>second</em>-most important idea in Epidemiology 101:</p>
|
||||
|
||||
|
@ -286,7 +286,7 @@
|
|||
|
||||
<h3 id="toc_0">Scenario 0: Do Absolutely Nothing</h3>
|
||||
|
||||
<p>Around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).<sup id="fnref13"><a href="#fn13" rel="footnote">13</a></sup> In a rich country like the USA, there's 1 ICU bed per 3400 people.<sup id="fnref14"><a href="#fn14" rel="footnote">14</a></sup> Therefore, the USA can handle 20 out of 3400 people being <em>simultaneously</em> infected – or, 0.6% of the population.</p>
|
||||
<p><em>Roughly</em> around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).<sup id="fnref13"><a href="#fn13" rel="footnote">13</a></sup> In a rich country like the USA, there's 1 ICU bed per 3400 people.<sup id="fnref14"><a href="#fn14" rel="footnote">14</a></sup> Therefore, the USA can handle 20 out of 3400 people being <em>simultaneously</em> infected – or, 0.6% of the population.</p>
|
||||
|
||||
<p>Even if we <em>more than tripled</em> that capacity to 2%, here's what would've happened <em>if we did absolutely nothing:</em></p>
|
||||
|
||||
|
@ -296,24 +296,24 @@
|
|||
|
||||
<p>Not good.</p>
|
||||
|
||||
<p>That's what <a href="http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/">the March 16 Imperial College report</a> found: do nothing, and we run out of ICUs, with more than 80% of the population getting infected.
|
||||
<p>That's what <a href="http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/">the March 16 Imperial College report</a> found: do nothing, and we run out of ICUs, with more than 80% of the population getting infected.
|
||||
(remember: total cases <em>overshoots</em> herd immunity)</p>
|
||||
|
||||
<p>Even if only 0.5% of infected die – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... <em>IF we did nothing.</em></p>
|
||||
<p>Even if only 0.5% of infected die<sup id="fnref15"><a href="#fn15" rel="footnote">15</a></sup> – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... <em>IF we did nothing.</em></p>
|
||||
|
||||
<p>(Lots of news & social media reported "80% will be infected" <em>without</em> "IF WE DO NOTHING". Fear was channelled into clicks, not understanding. <em>Sigh.</em>)</p>
|
||||
|
||||
<h3 id="toc_1">Scenario 1: Flatten The Curve / Herd Immunity</h3>
|
||||
|
||||
<p>The "Flatten The Curve" plan was touted by every public health organization, while the United Kingdom's original "herd immunity" plan was universally booed. They were <em>the same plan.</em> The UK just communicated theirs poorly.<sup id="fnref15"><a href="#fn15" rel="footnote">15</a></sup></p>
|
||||
<p>The "Flatten The Curve" plan was touted by every public health organization, while the United Kingdom's original "herd immunity" plan was universally booed. They were <em>the same plan.</em> The UK just communicated theirs poorly.<sup id="fnref16"><a href="#fn16" rel="footnote">16</a></sup></p>
|
||||
|
||||
<p>Both plans, though, had a literally fatal flaw.</p>
|
||||
|
||||
<p>First, let's look at the two main ways to "flatten the curve": handwashing & physical distancing.</p>
|
||||
|
||||
<p>Increased handwashing cuts flus & colds in high-income countries by ~25%<sup id="fnref16"><a href="#fn16" rel="footnote">16</a></sup>, while the city-wide lockdown in London cut close contacts by ~70%<sup id="fnref17"><a href="#fn17" rel="footnote">17</a></sup>. So, let's assume handwashing can reduce R by <em>up to</em> 25%, and distancing can reduce R by <em>up to</em> 70%:</p>
|
||||
<p>Increased handwashing cuts flus & colds in high-income countries by ~25%<sup id="fnref17"><a href="#fn17" rel="footnote">17</a></sup>, while the city-wide lockdown in London cut close contacts by ~70%<sup id="fnref18"><a href="#fn18" rel="footnote">18</a></sup>. So, let's assume handwashing can reduce R by <em>up to</em> 25%, and distancing can reduce R by <em>up to</em> 70%:</p>
|
||||
|
||||
<p><strong>Play with this calculator to see how % of <span class="nowrap">non-<icon s></icon>,</span> handwashing, and distancing reduce R:</strong> (this calculator visualizes their <em>relative</em> effects, which is why increasing one <em>looks</em> like it decreases the effect of the others.<sup id="fnref18"><a href="#fn18" rel="footnote">18</a></sup>)</p>
|
||||
<p><strong>Play with this calculator to see how % of <span class="nowrap">non-<icon s></icon>,</span> handwashing, and distancing reduce R:</strong> (this calculator visualizes their <em>relative</em> effects, which is why increasing one <em>looks</em> like it decreases the effect of the others.<sup id="fnref19"><a href="#fn19" rel="footnote">19</a></sup>)</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-2a&format=calc" width="285" height="260"></iframe>
|
||||
|
@ -357,7 +357,7 @@
|
|||
|
||||
<h3 id="toc_3">Scenario 3: Intermittent Lockdown</h3>
|
||||
|
||||
<p>This solution was first suggested by the March 16 Imperial College report, and later again by a Harvard paper.<sup id="fnref19"><a href="#fn19" rel="footnote">19</a></sup></p>
|
||||
<p>This solution was first suggested by the March 16 Imperial College report, and later again by a Harvard paper.<sup id="fnref20"><a href="#fn20" rel="footnote">20</a></sup></p>
|
||||
|
||||
<p><strong>Here's a simulation:</strong> (After playing the "recorded scenario", you can try simulating your <em>own</em> lockdown schedule, by changing the sliders <em>while</em> the simulation is running! Remember you can pause & continue the sim, and change the simulation speed)</p>
|
||||
|
||||
|
@ -369,7 +369,7 @@
|
|||
|
||||
<p>Look, it's nice to draw a line saying "ICU capacity", but there's lots of important things we <em>can't</em> simulate here. Like:</p>
|
||||
|
||||
<p><strong>Mental Health:</strong> Loneliness is one of the biggest risk factors for depression, anxiety, and suicide. And it's as associated with an early death as smoking 15 cigarettes a day.<sup id="fnref20"><a href="#fn20" rel="footnote">20</a></sup></p>
|
||||
<p><strong>Mental Health:</strong> Loneliness is one of the biggest risk factors for depression, anxiety, and suicide. And it's as associated with an early death as smoking 15 cigarettes a day.<sup id="fnref21"><a href="#fn21" rel="footnote">21</a></sup></p>
|
||||
|
||||
<p><strong>Financial Health:</strong> "What about the economy" sounds like you care more about dollars than lives, but "the economy" isn't just stocks: it's people's ability to provide food & shelter for their loved ones, to invest in their kids' futures, and enjoy arts, foods, videogames – the stuff that makes life worth living. And besides, poverty <em>itself</em> has horrible impacts on mental and physical health.</p>
|
||||
|
||||
|
@ -385,7 +385,7 @@
|
|||
|
||||
<p>But that's exactly it! “A lockdown isn't a cure, it's just a restart”... <strong>and a fresh start is what we need.</strong></p>
|
||||
|
||||
<p>To understand how Taiwan & South Korea contained COVID-19, we need to understand the exact timeline of a typical COVID-19 infection<sup id="fnref21"><a href="#fn21" rel="footnote">21</a></sup>:</p>
|
||||
<p>To understand how Taiwan & South Korea contained COVID-19, we need to understand the exact timeline of a typical COVID-19 infection<sup id="fnref22"><a href="#fn22" rel="footnote">22</a></sup>:</p>
|
||||
|
||||
<p><img src="pics/timeline1.png" alt=""></p>
|
||||
|
||||
|
@ -393,13 +393,13 @@
|
|||
|
||||
<p><img src="pics/timeline2.png" alt=""></p>
|
||||
|
||||
<p>And in fact, 44% of all transmissions are like this: <em>pre</em>-symptomatic! <sup id="fnref22"><a href="#fn22" rel="footnote">22</a></sup></p>
|
||||
<p>And in fact, 44% of all transmissions are like this: <em>pre</em>-symptomatic! <sup id="fnref23"><a href="#fn23" rel="footnote">23</a></sup></p>
|
||||
|
||||
<p>But, if we find <em>and quarantine</em> a symptomatic case's recent close contacts... we stop the spread, by staying one step ahead!</p>
|
||||
|
||||
<p><img src="pics/timeline3.png" alt=""></p>
|
||||
|
||||
<p>This is called <strong>contact tracing</strong>. It's an old idea, was used at an unprecedented scale to contain Ebola<sup id="fnref23"><a href="#fn23" rel="footnote">23</a></sup>, and now it's core part of how Taiwan & South Korea are containing COVID-19!</p>
|
||||
<p>This is called <strong>contact tracing</strong>. It's an old idea, was used at an unprecedented scale to contain Ebola<sup id="fnref24"><a href="#fn24" rel="footnote">24</a></sup>, and now it's core part of how Taiwan & South Korea are containing COVID-19!</p>
|
||||
|
||||
<p>(It also lets us use our limited tests more efficiently, to find pre-symptomatic <span class="nowrap"><icon i></icon>s</span> without needing to test almost everyone.)</p>
|
||||
|
||||
|
@ -415,15 +415,15 @@
|
|||
|
||||
<p><img src="pics/dp3t.png" alt=""></p>
|
||||
|
||||
<p>(<a href="https://ncase.me/contact-tracing/">Here's the full comic</a>. Details about "pranking"/false positives/etc in footnote:<sup id="fnref24"><a href="#fn24" rel="footnote">24</a></sup>)</p>
|
||||
<p>(<a href="https://ncase.me/contact-tracing/">Here's the full comic</a>. Details about "pranking"/false positives/etc in footnote:<sup id="fnref25"><a href="#fn25" rel="footnote">25</a></sup>)</p>
|
||||
|
||||
<p>Along with similar teams like TCN Protocol<sup id="fnref25"><a href="#fn25" rel="footnote">25</a></sup> and MIT PACT<sup id="fnref26"><a href="#fn26" rel="footnote">26</a></sup>, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.<sup id="fnref27"><a href="#fn27" rel="footnote">27</a></sup> (Don't trust Google/Apple? Good! The beauty of this system is it doesn't <em>need</em> 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!</p>
|
||||
<p>Along with similar teams like TCN Protocol<sup id="fnref26"><a href="#fn26" rel="footnote">26</a></sup> and MIT PACT<sup id="fnref27"><a href="#fn27" rel="footnote">27</a></sup>, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.<sup id="fnref28"><a href="#fn28" rel="footnote">28</a></sup> (Don't trust Google/Apple? Good! The beauty of this system is it doesn't <em>need</em> 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!</p>
|
||||
|
||||
<p>But what about folks without smartphones? Or infections through doorknobs? Or "true" asymptomatic cases? Contact tracing apps can't catch all transmissions... <em>and that's okay!</em> We don't need to catch <em>all</em> transmissions, just 60%+ to get R < 1.</p>
|
||||
|
||||
<p>(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:<sup id="fnref28"><a href="#fn28" rel="footnote">28</a></sup>)</p>
|
||||
<p>(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:<sup id="fnref29"><a href="#fn29" rel="footnote">29</a></sup>)</p>
|
||||
|
||||
<p>Isolating <em>symptomatic</em> cases would reduce R by up to 40%, and quarantining their <em>pre/a-symptomatic</em> contacts would reduce R by up to 50%<sup id="fnref29"><a href="#fn29" rel="footnote">29</a></sup>:</p>
|
||||
<p>Isolating <em>symptomatic</em> cases would reduce R by up to 40%, and quarantining their <em>pre/a-symptomatic</em> contacts would reduce R by up to 50%<sup id="fnref30"><a href="#fn30" rel="footnote">30</a></sup>:</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-4a&format=calc" width="285" height="340"></iframe>
|
||||
|
@ -472,17 +472,17 @@
|
|||
|
||||
<p><em>"Wait,"</em> you might ask, <em>"I thought face masks don't stop you from getting sick?"</em></p>
|
||||
|
||||
<p>You're right. Masks don't stop you from getting sick<sup id="fnref30"><a href="#fn30" rel="footnote">30</a></sup>... they stop you from getting <em>others</em> sick.</p>
|
||||
<p>You're right. Masks don't stop you from getting sick<sup id="fnref31"><a href="#fn31" rel="footnote">31</a></sup>... they stop you from getting <em>others</em> sick.</p>
|
||||
|
||||
<p><img src="pics/masks.png" alt=""></p>
|
||||
|
||||
<p>To put a number on it: surgical masks <em>on the infectious person</em> reduce cold & flu viruses in aerosols by 70%.<sup id="fnref31"><a href="#fn31" rel="footnote">31</a></sup> Reducing transmissions by 70% would be as large an impact as a lockdown!</p>
|
||||
<p>To put a number on it: surgical masks <em>on the infectious person</em> reduce cold & flu viruses in aerosols by 70%.<sup id="fnref32"><a href="#fn32" rel="footnote">32</a></sup> Reducing transmissions by 70% would be as large an impact as a lockdown!</p>
|
||||
|
||||
<p>However, we don't know for sure the impact of masks on COVID-19 <em>specifically</em>. In science, one should only publish a finding if you're 95% sure of it. (...should.<sup id="fnref32"><a href="#fn32" rel="footnote">32</a></sup>) Masks, as of May 1st 2020, are less than "95% sure".</p>
|
||||
<p>However, we don't know for sure the impact of masks on COVID-19 <em>specifically</em>. In science, one should only publish a finding if you're 95% sure of it. (...should.<sup id="fnref33"><a href="#fn33" rel="footnote">33</a></sup>) Masks, as of May 1st 2020, are less than "95% sure".</p>
|
||||
|
||||
<p>However, pandemics are like poker. <strong>Make bets only when you're 95% sure, and you'll lose everything at stake.</strong> As a recent article on masks in the British Medical Journal notes,<sup id="fnref33"><a href="#fn33" rel="footnote">33</a></sup> we <em>have</em> to make cost/benefit analyses under uncertainty. Like so:</p>
|
||||
<p>However, pandemics are like poker. <strong>Make bets only when you're 95% sure, and you'll lose everything at stake.</strong> As a recent article on masks in the British Medical Journal notes,<sup id="fnref34"><a href="#fn34" rel="footnote">34</a></sup> we <em>have</em> to make cost/benefit analyses under uncertainty. Like so:</p>
|
||||
|
||||
<p>Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks<sup id="fnref34"><a href="#fn34" rel="footnote">34</a></sup>), super cheap. If surgical masks, more expensive but still pretty cheap.</p>
|
||||
<p>Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks<sup id="fnref35"><a href="#fn35" rel="footnote">35</a></sup>), super cheap. If surgical masks, more expensive but still pretty cheap.</p>
|
||||
|
||||
<p>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)</p>
|
||||
|
||||
|
@ -490,7 +490,7 @@
|
|||
<iframe src="sim?stage=int-6a&format=calc" width="285" height="380"></iframe>
|
||||
</div>
|
||||
|
||||
<p>(other arguments for/against masks:<sup id="fnref35"><a href="#fn35" rel="footnote">35</a></sup>)</p>
|
||||
<p>(other arguments for/against masks:<sup id="fnref36"><a href="#fn36" rel="footnote">36</a></sup>)</p>
|
||||
|
||||
<p>Masks <em>alone</em> 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!</p>
|
||||
|
||||
|
@ -498,7 +498,7 @@
|
|||
|
||||
<p>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 <em>will</em> reduce R.</p>
|
||||
|
||||
<p>For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.<sup id="fnref36"><a href="#fn36" rel="footnote">36</a></sup> The summer-winter difference in New York City is 26°C (47°F),<sup id="fnref37"><a href="#fn37" rel="footnote">37</a></sup> so summer will make R drop by ~31%.</p>
|
||||
<p>For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.<sup id="fnref37"><a href="#fn37" rel="footnote">37</a></sup> The summer-winter difference in New York City is 26°C (47°F),<sup id="fnref38"><a href="#fn38" rel="footnote">38</a></sup> so summer will make R drop by ~31%.</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-6b&format=calc" width="285" height="220"></iframe>
|
||||
|
@ -558,10 +558,10 @@
|
|||
<p>...<em>for how long?</em></p>
|
||||
|
||||
<ul>
|
||||
<li>COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.<sup id="fnref38"><a href="#fn38" rel="footnote">38</a></sup></li>
|
||||
<li>The coronaviruses that cause "the" common cold give you 8 months of immunity.<sup id="fnref39"><a href="#fn39" rel="footnote">39</a></sup></li>
|
||||
<li>There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.<sup id="fnref40"><a href="#fn40" rel="footnote">40</a></sup></li>
|
||||
<li>One <em>not-yet-peer-reviewed</em> study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.<sup id="fnref41"><a href="#fn41" rel="footnote">41</a></sup></li>
|
||||
<li>COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.<sup id="fnref39"><a href="#fn39" rel="footnote">39</a></sup></li>
|
||||
<li>The coronaviruses that cause "the" common cold give you 8 months of immunity.<sup id="fnref40"><a href="#fn40" rel="footnote">40</a></sup></li>
|
||||
<li>There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.<sup id="fnref41"><a href="#fn41" rel="footnote">41</a></sup></li>
|
||||
<li>One <em>not-yet-peer-reviewed</em> study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.<sup id="fnref42"><a href="#fn42" rel="footnote">42</a></sup></li>
|
||||
</ul>
|
||||
|
||||
<p>But for COVID-19 <em>in humans</em>, as of May 1st 2020, "how long" is the big unknown.</p>
|
||||
|
@ -613,7 +613,7 @@
|
|||
|
||||
<p><strong>To be clear: this is unlikely.</strong> 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. </p>
|
||||
|
||||
<p>Still, infectious disease researchers have expressed worries: What if we can't make enough?<sup id="fnref42"><a href="#fn42" rel="footnote">42</a></sup> What if we rush it, and it's not safe?<sup id="fnref43"><a href="#fn43" rel="footnote">43</a></sup></p>
|
||||
<p>Still, infectious disease researchers have expressed worries: What if we can't make enough?<sup id="fnref43"><a href="#fn43" rel="footnote">43</a></sup> What if we rush it, and it's not safe?<sup id="fnref44"><a href="#fn44" rel="footnote">44</a></sup></p>
|
||||
|
||||
<p>Even in the nightmare "no-vaccine" scenario, we still have 3 ways out. From most to least terrible:</p>
|
||||
|
||||
|
@ -652,7 +652,7 @@
|
|||
</div>
|
||||
</div>
|
||||
|
||||
<p>Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.<sup id="fnref44"><a href="#fn44" rel="footnote">44</a></sup></p>
|
||||
<p>Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.<sup id="fnref45"><a href="#fn45" rel="footnote">45</a></sup></p>
|
||||
|
||||
<p>Teams of epidemiologists and policymakers (<a href="https://www.americanprogress.org/issues/healthcare/news/2020/04/03/482613/national-state-plan-end-coronavirus-crisis/">left</a>, <a href="https://www.aei.org/research-products/report/national-coronavirus-response-a-road-map-to-reopening/">right</a>, and <a href="https://ethics.harvard.edu/covid-roadmap">multi-partisan</a>) have come to a consensus on how to beat COVID-19, while protecting our lives <em>and</em> liberties.</p>
|
||||
|
||||
|
@ -680,6 +680,8 @@
|
|||
<p>These footnotes will have sources, links, or bonus commentary. Like this commentary! <a href="#fnref1" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>This guide was published on May 1st, 2020.</strong> Many details will become outdated, but we're confident this guide will cover 95% of possible futures, and that Epidemiology 101 will remain forever useful.</p>
|
||||
|
||||
<p>(Update May 15: Added citations for "1 in 20 of infected are hospitalized" and "0.5% of infected die")</p>
|
||||
</li>
|
||||
|
||||
<li id="fn2">
|
||||
|
@ -741,7 +743,15 @@
|
|||
</li>
|
||||
|
||||
<li id="fn13">
|
||||
<p><a href="https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/">"Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"</a>. Between 4.9% to 11.5% of <em>all</em> COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations. <a href="#fnref13" rev="footnote">↩</a></p>
|
||||
<p><strong>[UPDATED MAY 15]</strong> Many of you rightly pointed out that our previous citation for "<strong>1 in 20</strong> need hospitalization" was based off old USA data on <em>confirmed</em> cases – which was way lower than the <em>real</em> number of cases, due to lack of tests. <a href="#fnref13" rev="footnote">↩</a></p>
|
||||
|
||||
<p>So, let's look at the country with the <em>most</em> tests per capita: Iceland. As of May 15th, 2020, they had 115 hospitalized among 1802 confirmed cases ≈ 6.4% hospitalization rate, or <strong>1 in 16</strong>.</p>
|
||||
|
||||
<p><a href="https://science.sciencemag.org/content/early/2020/05/12/science.abc3517">A more recent study of COVID-19 in France</a> – using not just official confirmed cases but also antibody test data – found that “3.6% of infected individuals are hospitalized”. Or, <strong>1 in 28.</strong></p>
|
||||
|
||||
<p>Overall, there's a lot of uncertainty, but "1 in 20" is roughly close. Besides, for the rest of these simulations, we <em>triple</em> hospital capacity – so, even if "1 in 20" is three times too high, the point still stands.</p>
|
||||
|
||||
<p>Old citation: <del><a href="https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/">"Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"</a>. Between 4.9% to 11.5% of <em>all</em> COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations.</del></p>
|
||||
</li>
|
||||
|
||||
<li id="fn14">
|
||||
|
@ -749,77 +759,81 @@
|
|||
</li>
|
||||
|
||||
<li id="fn15">
|
||||
<p>“He says that the actual goal is the same as that of other countries: flatten the curve by staggering the onset of infections. As a consequence, the nation may achieve herd immunity; it’s a side effect, not an aim. [...] The government’s actual coronavirus action plan, available online, doesn’t mention herd immunity at all.” <a href="#fnref15" rev="footnote">↩</a></p>
|
||||
<p><strong>[UPDATED MAY 15]</strong> <a href="https://news.iu.edu/stories/2020/05/iupui/releases/13-preliminary-findings-impact-covid-19-indiana-coronavirus.html">Researchers in Indiana, USA</a> did a random-sample test of the population, and found an infection-fatality rate (IFR) of 0.58%. <a href="#fnref15" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn16">
|
||||
<p>“He says that the actual goal is the same as that of other countries: flatten the curve by staggering the onset of infections. As a consequence, the nation may achieve herd immunity; it’s a side effect, not an aim. [...] The government’s actual coronavirus action plan, available online, doesn’t mention herd immunity at all.” <a href="#fnref16" rev="footnote">↩</a></p>
|
||||
|
||||
<p>From a <a href="https://www.theatlantic.com/health/archive/2020/03/coronavirus-pandemic-herd-immunity-uk-boris-johnson/608065/">The Atlantic article by Ed Yong</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn16">
|
||||
<p>“All eight eligible studies reported that handwashing lowered risks of respiratory infection, with risk reductions ranging from 6% to 44% [pooled value 24% (95% CI 6–40%)].” We rounded up the pooled value to 25% in these simulations for simplicity. <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-3156.2006.01568.x">Rabie, T. and Curtis, V.</a> Note: as this meta-analysis points out, the quality of studies for handwashing (at least in high-income countries) are awful. <a href="#fnref16" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn17">
|
||||
<p>“We found a 73% reduction in the average daily number of contacts observed per participant. This would be sufficient to reduce R0 from a value from 2.6 before the lockdown to 0.62 (0.37 - 0.89) during the lockdown”. We rounded it down to 70% in these simulations for simplicity. <a href="https://cmmid.github.io/topics/covid19/comix-impact-of-physical-distance-measures-on-transmission-in-the-UK.html">Jarvis and Zandvoort et al</a> <a href="#fnref17" rev="footnote">↩</a></p>
|
||||
<p>“All eight eligible studies reported that handwashing lowered risks of respiratory infection, with risk reductions ranging from 6% to 44% [pooled value 24% (95% CI 6–40%)].” We rounded up the pooled value to 25% in these simulations for simplicity. <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-3156.2006.01568.x">Rabie, T. and Curtis, V.</a> Note: as this meta-analysis points out, the quality of studies for handwashing (at least in high-income countries) are awful. <a href="#fnref17" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn18">
|
||||
<p>This distortion would go away if we plotted R on a logarithmic scale... but then we'd have to explain <em>logarithmic scales.</em> <a href="#fnref18" rev="footnote">↩</a></p>
|
||||
<p>“We found a 73% reduction in the average daily number of contacts observed per participant. This would be sufficient to reduce R0 from a value from 2.6 before the lockdown to 0.62 (0.37 - 0.89) during the lockdown”. We rounded it down to 70% in these simulations for simplicity. <a href="https://cmmid.github.io/topics/covid19/comix-impact-of-physical-distance-measures-on-transmission-in-the-UK.html">Jarvis and Zandvoort et al</a> <a href="#fnref18" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn19">
|
||||
<p>“Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022.” <a href="https://science.sciencemag.org/content/early/2020/04/14/science.abb5793">Kissler and Tedijanto et al</a> <a href="#fnref19" rev="footnote">↩</a></p>
|
||||
<p>This distortion would go away if we plotted R on a logarithmic scale... but then we'd have to explain <em>logarithmic scales.</em> <a href="#fnref19" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn20">
|
||||
<p>See <a href="https://journals.sagepub.com/doi/abs/10.1177/1745691614568352">Figure 6 from Holt-Lunstad & Smith 2010</a>. Of course, big disclaimer that they found a <em>correlation</em>. But unless you want to try randomly assigning people to be lonely for life, observational evidence is all you're gonna get. <a href="#fnref20" rev="footnote">↩</a></p>
|
||||
<p>“Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022.” <a href="https://science.sciencemag.org/content/early/2020/04/14/science.abb5793">Kissler and Tedijanto et al</a> <a href="#fnref20" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn21">
|
||||
<p><strong>3 days on average to infectiousness:</strong> “Assuming an incubation period distribution of mean 5.2 days from a separate study of early COVID-19 cases, we inferred that infectiousness started from 2.3 days (95% CI, 0.8–3.0 days) before symptom onset” (translation: Assuming symptoms start at 5 days, infectiousness starts 2 days before = Infectiousness starts at 3 days) <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al.</a> <a href="#fnref21" rev="footnote">↩</a></p>
|
||||
<p>See <a href="https://journals.sagepub.com/doi/abs/10.1177/1745691614568352">Figure 6 from Holt-Lunstad & Smith 2010</a>. Of course, big disclaimer that they found a <em>correlation</em>. But unless you want to try randomly assigning people to be lonely for life, observational evidence is all you're gonna get. <a href="#fnref21" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn22">
|
||||
<p><strong>3 days on average to infectiousness:</strong> “Assuming an incubation period distribution of mean 5.2 days from a separate study of early COVID-19 cases, we inferred that infectiousness started from 2.3 days (95% CI, 0.8–3.0 days) before symptom onset” (translation: Assuming symptoms start at 5 days, infectiousness starts 2 days before = Infectiousness starts at 3 days) <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al.</a> <a href="#fnref22" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>4 days on average to infecting someone else:</strong> “The mean [serial] interval was 3.96 days (95% CI 3.53–4.39 days)” <a href="https://wwwnc.cdc.gov/eid/article/26/6/20-0357_article">Du Z, Xu X, Wu Y, Wang L, Cowling BJ, Ancel Meyers L</a></p>
|
||||
|
||||
<p><strong>5 days on average to feeling symptoms:</strong> “The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days)” <a href="https://annals.org/AIM/FULLARTICLE/2762808/INCUBATION-PERIOD-CORONAVIRUS-DISEASE-2019-COVID-19-FROM-PUBLICLY-REPORTED">Lauer SA, Grantz KH, Bi Q, et al</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn22">
|
||||
<p>“We estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage” <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al</a> <a href="#fnref22" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn23">
|
||||
<p>“Contact tracing was a critical intervention in Liberia and represented one of the largest contact tracing efforts during an epidemic in history.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152989/">Swanson KC, Altare C, Wesseh CS, et al.</a> <a href="#fnref23" rev="footnote">↩</a></p>
|
||||
<p>“We estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage” <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al</a> <a href="#fnref23" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn24">
|
||||
<p>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. <a href="#fnref24" rev="footnote">↩</a></p>
|
||||
<p>“Contact tracing was a critical intervention in Liberia and represented one of the largest contact tracing efforts during an epidemic in history.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152989/">Swanson KC, Altare C, Wesseh CS, et al.</a> <a href="#fnref24" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn25">
|
||||
<p>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. <a href="#fnref25" rev="footnote">↩</a></p>
|
||||
|
||||
<p>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 <em>does</em> think Bob's been exposed, it can refer Bob to a <em>manual</em> contact tracer, for an in-depth follow-up interview.</p>
|
||||
|
||||
<p>For other issues like data bandwidth, source integrity, and other security issues, check out <a href="https://github.com/DP-3T/documents#decentralized-privacy-preserving-proximity-tracing">the open-source DP-3T whitepapers!</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn25">
|
||||
<p><a href="https://github.com/TCNCoalition/TCN#tcn-protocol">Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol</a> <a href="#fnref25" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn26">
|
||||
<p><a href="https://pact.mit.edu/">PACT: Private Automated Contact Tracing</a> <a href="#fnref26" rev="footnote">↩</a></p>
|
||||
<p><a href="https://github.com/TCNCoalition/TCN#tcn-protocol">Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol</a> <a href="#fnref26" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn27">
|
||||
<p><a href="https://www.apple.com/ca/newsroom/2020/04/apple-and-google-partner-on-covid-19-contact-tracing-technology/">Apple and Google partner on COVID-19 contact tracing technology </a>. Note they're not making the apps <em>themselves</em>, just creating the systems that will <em>support</em> those apps. <a href="#fnref27" rev="footnote">↩</a></p>
|
||||
<p><a href="https://pact.mit.edu/">PACT: Private Automated Contact Tracing</a> <a href="#fnref27" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn28">
|
||||
<p>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 <em>ever</em>" (true asymptomatic). The only way you could tell the difference is by following up with cases later. <a href="#fnref28" rev="footnote">↩</a></p>
|
||||
<p><a href="https://www.apple.com/ca/newsroom/2020/04/apple-and-google-partner-on-covid-19-contact-tracing-technology/">Apple and Google partner on COVID-19 contact tracing technology </a>. Note they're not making the apps <em>themselves</em>, just creating the systems that will <em>support</em> those apps. <a href="#fnref28" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn29">
|
||||
<p>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 <em>ever</em>" (true asymptomatic). The only way you could tell the difference is by following up with cases later. <a href="#fnref29" rev="footnote">↩</a></p>
|
||||
|
||||
<p>Which is what <a href="https://wwwnc.cdc.gov/eid/article/26/8/20-1274_article">this study</a> 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."</p>
|
||||
|
||||
<p>So that means "true asymptomatics" are rare, and catching the disease from a true asymptomatic may be even rarer!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn29">
|
||||
<p>From the same Oxford study that first recommended apps to fight COVID-19: <a href="https://science.sciencemag.org/content/early/2020/04/09/science.abb6936/tab-figures-data">Luca Ferretti & Chris Wymant et al</a> See Figure 2. Assuming R<sub>0</sub> = 2.0, they found that: <a href="#fnref29" rev="footnote">↩</a></p>
|
||||
<li id="fn30">
|
||||
<p>From the same Oxford study that first recommended apps to fight COVID-19: <a href="https://science.sciencemag.org/content/early/2020/04/09/science.abb6936/tab-figures-data">Luca Ferretti & Chris Wymant et al</a> See Figure 2. Assuming R<sub>0</sub> = 2.0, they found that: <a href="#fnref30" rev="footnote">↩</a></p>
|
||||
|
||||
<ul>
|
||||
<li>Symptomatics contribute R = 0.8 (40%)</li>
|
||||
|
@ -831,73 +845,72 @@
|
|||
<p>And add up the pre- & a-symptomatic contacts (45% + 5%) and you get 50% of R!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn30">
|
||||
<p>“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” <a href="https://www.sciencedirect.com/science/article/pii/S0196655307007742">Tara Oberg & Lisa M. Brosseau</a> <a href="#fnref30" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn31">
|
||||
<p>“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.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591312/">Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ</a> <a href="#fnref31" rev="footnote">↩</a></p>
|
||||
<p>“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” <a href="https://www.sciencedirect.com/science/article/pii/S0196655307007742">Tara Oberg & Lisa M. Brosseau</a> <a href="#fnref31" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn32">
|
||||
<p>Any actual scientist who read that last sentence is probably laugh-crying right now. See: <a href="https://en.wikipedia.org/wiki/Data_dredging">p-hacking</a>, <a href="https://en.wikipedia.org/wiki/Replication_crisis">the replication crisis</a>) <a href="#fnref32" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591312/">Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ</a> <a href="#fnref32" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn33">
|
||||
<p>“It is time to apply the precautionary principle” <a href="https://www.bmj.com/content/bmj/369/bmj.m1435.full.pdf">Trisha Greenhalgh et al [PDF]</a> <a href="#fnref33" rev="footnote">↩</a></p>
|
||||
<p>Any actual scientist who read that last sentence is probably laugh-crying right now. See: <a href="https://en.wikipedia.org/wiki/Data_dredging">p-hacking</a>, <a href="https://en.wikipedia.org/wiki/Replication_crisis">the replication crisis</a>) <a href="#fnref33" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn34">
|
||||
<p><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/testing-the-efficacy-of-homemade-masks-would-they-protect-in-an-influenza-pandemic/0921A05A69A9419C862FA2F35F819D55">Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A</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. <a href="#fnref34" rev="footnote">↩</a></p>
|
||||
<p>“It is time to apply the precautionary principle” <a href="https://www.bmj.com/content/bmj/369/bmj.m1435.full.pdf">Trisha Greenhalgh et al [PDF]</a> <a href="#fnref34" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn35">
|
||||
<p><strong>"We need to save supplies for hospitals."</strong> <em>Absolutely agreed.</em> But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. <a href="#fnref35" rev="footnote">↩</a></p>
|
||||
<p><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/testing-the-efficacy-of-homemade-masks-would-they-protect-in-an-influenza-pandemic/0921A05A69A9419C862FA2F35F819D55">Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A</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. <a href="#fnref35" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn36">
|
||||
<p><strong>"We need to save supplies for hospitals."</strong> <em>Absolutely agreed.</em> But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. <a href="#fnref36" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>"They're hard to wear correctly."</strong> 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.</p>
|
||||
|
||||
<p><strong>"It'll make people more reckless with handwashing & social distancing."</strong> 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 <em>constant physical reminder</em> to be careful – and in East Asia, masks are also a symbol of solidarity!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn36">
|
||||
<p>“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%. <a href="https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3551767">Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng</a> <a href="#fnref36" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn37">
|
||||
<p>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. <a href="https://www.weather.gov/media/okx/Climate/CentralPark/monthlyannualtemp.pdf">PDF from Weather.gov</a> <a href="#fnref37" rev="footnote">↩</a></p>
|
||||
<p>“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%. <a href="https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3551767">Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng</a> <a href="#fnref37" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn38">
|
||||
<p>“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851497/">Wu LP, Wang NC, Chang YH, et al.</a> "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. <a href="#fnref38" rev="footnote">↩</a></p>
|
||||
<p>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. <a href="https://www.weather.gov/media/okx/Climate/CentralPark/monthlyannualtemp.pdf">PDF from Weather.gov</a> <a href="#fnref38" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn39">
|
||||
<p>“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.” <a href="http://www.columbia.edu/%7Ejls106/galanti_shaman_ms_supp.pdf">Marta Galanti & Jeffrey Shaman (PDF)</a> <a href="#fnref39" rev="footnote">↩</a></p>
|
||||
<p>“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851497/">Wu LP, Wang NC, Chang YH, et al.</a> "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. <a href="#fnref39" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn40">
|
||||
<p>“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.” <a href="https://www.statnews.com/2020/04/20/everything-we-know-about-coronavirus-immunity-and-antibodies-and-plenty-we-still-dont/">from STAT News by Andrew Joseph</a> <a href="#fnref40" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="http://www.columbia.edu/%7Ejls106/galanti_shaman_ms_supp.pdf">Marta Galanti & Jeffrey Shaman (PDF)</a> <a href="#fnref40" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn41">
|
||||
<p>From <a href="https://www.biorxiv.org/content/10.1101/2020.03.13.990226v1.abstract">Bao et al.</a> <em>Disclaimer: This article is a preprint and has not been certified by peer review (yet).</em> Also, to emphasize: they only tested re-infection 28 days later. <a href="#fnref41" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="https://www.statnews.com/2020/04/20/everything-we-know-about-coronavirus-immunity-and-antibodies-and-plenty-we-still-dont/">from STAT News by Andrew Joseph</a> <a href="#fnref41" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn42">
|
||||
<p>“If a coronavirus vaccine arrives, can the world make enough?” <a href="https://www.nature.com/articles/d41586-020-01063-8">by Roxanne Khamsi, on Nature</a> <a href="#fnref42" rev="footnote">↩</a></p>
|
||||
<p>From <a href="https://www.biorxiv.org/content/10.1101/2020.03.13.990226v1.abstract">Bao et al.</a> <em>Disclaimer: This article is a preprint and has not been certified by peer review (yet).</em> Also, to emphasize: they only tested re-infection 28 days later. <a href="#fnref42" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn43">
|
||||
<p>“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” <a href="https://www.nature.com/articles/d41586-020-00751-9">by Shibo Jiang, on Nature</a> <a href="#fnref43" rev="footnote">↩</a></p>
|
||||
<p>“If a coronavirus vaccine arrives, can the world make enough?” <a href="https://www.nature.com/articles/d41586-020-01063-8">by Roxanne Khamsi, on Nature</a> <a href="#fnref43" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn44">
|
||||
<p>Dry land metaphor <a href="https://www.statnews.com/2020/04/01/navigating-covid-19-pandemic/">from Marc Lipsitch & Yonatan Grad, on STAT News</a> <a href="#fnref44" rev="footnote">↩</a></p>
|
||||
<p>“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” <a href="https://www.nature.com/articles/d41586-020-00751-9">by Shibo Jiang, on Nature</a> <a href="#fnref44" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn45">
|
||||
<p>Dry land metaphor <a href="https://www.statnews.com/2020/04/01/navigating-covid-19-pandemic/">from Marc Lipsitch & Yonatan Grad, on STAT News</a> <a href="#fnref45" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
</ol>
|
||||
</div>
|
||||
|
||||
</article>
|
||||
|
||||
<!-- - - - - - - - - - - - - - - - - - - - - - - -->
|
||||
|
|
166
words/words.html
166
words/words.html
|
@ -123,7 +123,7 @@ starts at just 0.001% <span class="nowrap"><icon i></icon>:</span></p>
|
|||
|
||||
<p>And <em>that's</em> where that famous curve comes from! It's not a bell curve, it's not even a "log-normal" curve. It has no name. But you've seen it a zillion times, and beseeched to flatten.</p>
|
||||
|
||||
<p>This is the the <strong>SIR Model</strong>,<sup id="fnref5"><a href="#fn5" rel="footnote">5</a></sup><br>
|
||||
<p>This is the <strong>SIR Model</strong>,<sup id="fnref5"><a href="#fn5" rel="footnote">5</a></sup><br>
|
||||
(<icon s></icon><strong>S</strong>usceptible <icon i></icon><strong>I</strong>nfectious <icon r></icon><strong>R</strong>ecovered)<br>
|
||||
the <em>second</em>-most important idea in Epidemiology 101:</p>
|
||||
|
||||
|
@ -223,7 +223,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<h3 id="toc_0">Scenario 0: Do Absolutely Nothing</h3>
|
||||
|
||||
<p>Around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).<sup id="fnref13"><a href="#fn13" rel="footnote">13</a></sup> In a rich country like the USA, there's 1 ICU bed per 3400 people.<sup id="fnref14"><a href="#fn14" rel="footnote">14</a></sup> Therefore, the USA can handle 20 out of 3400 people being <em>simultaneously</em> infected – or, 0.6% of the population.</p>
|
||||
<p><em>Roughly</em> around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).<sup id="fnref13"><a href="#fn13" rel="footnote">13</a></sup> In a rich country like the USA, there's 1 ICU bed per 3400 people.<sup id="fnref14"><a href="#fn14" rel="footnote">14</a></sup> Therefore, the USA can handle 20 out of 3400 people being <em>simultaneously</em> infected – or, 0.6% of the population.</p>
|
||||
|
||||
<p>Even if we <em>more than tripled</em> that capacity to 2%, here's what would've happened <em>if we did absolutely nothing:</em></p>
|
||||
|
||||
|
@ -236,21 +236,21 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
<p>That's what <a href="http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/">the March 16 Imperial College report</a> found: do nothing, and we run out of ICUs, with more than 80% of the population getting infected.
|
||||
(remember: total cases <em>overshoots</em> herd immunity)</p>
|
||||
|
||||
<p>Even if only 0.5% of infected die – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... <em>IF we did nothing.</em></p>
|
||||
<p>Even if only 0.5% of infected die<sup id="fnref15"><a href="#fn15" rel="footnote">15</a></sup> – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... <em>IF we did nothing.</em></p>
|
||||
|
||||
<p>(Lots of news & social media reported "80% will be infected" <em>without</em> "IF WE DO NOTHING". Fear was channelled into clicks, not understanding. <em>Sigh.</em>)</p>
|
||||
|
||||
<h3 id="toc_1">Scenario 1: Flatten The Curve / Herd Immunity</h3>
|
||||
|
||||
<p>The "Flatten The Curve" plan was touted by every public health organization, while the United Kingdom's original "herd immunity" plan was universally booed. They were <em>the same plan.</em> The UK just communicated theirs poorly.<sup id="fnref15"><a href="#fn15" rel="footnote">15</a></sup></p>
|
||||
<p>The "Flatten The Curve" plan was touted by every public health organization, while the United Kingdom's original "herd immunity" plan was universally booed. They were <em>the same plan.</em> The UK just communicated theirs poorly.<sup id="fnref16"><a href="#fn16" rel="footnote">16</a></sup></p>
|
||||
|
||||
<p>Both plans, though, had a literally fatal flaw.</p>
|
||||
|
||||
<p>First, let's look at the two main ways to "flatten the curve": handwashing & physical distancing.</p>
|
||||
|
||||
<p>Increased handwashing cuts flus & colds in high-income countries by ~25%<sup id="fnref16"><a href="#fn16" rel="footnote">16</a></sup>, while the city-wide lockdown in London cut close contacts by ~70%<sup id="fnref17"><a href="#fn17" rel="footnote">17</a></sup>. So, let's assume handwashing can reduce R by <em>up to</em> 25%, and distancing can reduce R by <em>up to</em> 70%:</p>
|
||||
<p>Increased handwashing cuts flus & colds in high-income countries by ~25%<sup id="fnref17"><a href="#fn17" rel="footnote">17</a></sup>, while the city-wide lockdown in London cut close contacts by ~70%<sup id="fnref18"><a href="#fn18" rel="footnote">18</a></sup>. So, let's assume handwashing can reduce R by <em>up to</em> 25%, and distancing can reduce R by <em>up to</em> 70%:</p>
|
||||
|
||||
<p><strong>Play with this calculator to see how % of <span class="nowrap">non-<icon s></icon>,</span> handwashing, and distancing reduce R:</strong> (this calculator visualizes their <em>relative</em> effects, which is why increasing one <em>looks</em> like it decreases the effect of the others.<sup id="fnref18"><a href="#fn18" rel="footnote">18</a></sup>)</p>
|
||||
<p><strong>Play with this calculator to see how % of <span class="nowrap">non-<icon s></icon>,</span> handwashing, and distancing reduce R:</strong> (this calculator visualizes their <em>relative</em> effects, which is why increasing one <em>looks</em> like it decreases the effect of the others.<sup id="fnref19"><a href="#fn19" rel="footnote">19</a></sup>)</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-2a&format=calc" width="285" height="260"></iframe>
|
||||
|
@ -294,7 +294,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<h3 id="toc_3">Scenario 3: Intermittent Lockdown</h3>
|
||||
|
||||
<p>This solution was first suggested by the March 16 Imperial College report, and later again by a Harvard paper.<sup id="fnref19"><a href="#fn19" rel="footnote">19</a></sup></p>
|
||||
<p>This solution was first suggested by the March 16 Imperial College report, and later again by a Harvard paper.<sup id="fnref20"><a href="#fn20" rel="footnote">20</a></sup></p>
|
||||
|
||||
<p><strong>Here's a simulation:</strong> (After playing the "recorded scenario", you can try simulating your <em>own</em> lockdown schedule, by changing the sliders <em>while</em> the simulation is running! Remember you can pause & continue the sim, and change the simulation speed)</p>
|
||||
|
||||
|
@ -306,7 +306,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p>Look, it's nice to draw a line saying "ICU capacity", but there's lots of important things we <em>can't</em> simulate here. Like:</p>
|
||||
|
||||
<p><strong>Mental Health:</strong> Loneliness is one of the biggest risk factors for depression, anxiety, and suicide. And it's as associated with an early death as smoking 15 cigarettes a day.<sup id="fnref20"><a href="#fn20" rel="footnote">20</a></sup></p>
|
||||
<p><strong>Mental Health:</strong> Loneliness is one of the biggest risk factors for depression, anxiety, and suicide. And it's as associated with an early death as smoking 15 cigarettes a day.<sup id="fnref21"><a href="#fn21" rel="footnote">21</a></sup></p>
|
||||
|
||||
<p><strong>Financial Health:</strong> "What about the economy" sounds like you care more about dollars than lives, but "the economy" isn't just stocks: it's people's ability to provide food & shelter for their loved ones, to invest in their kids' futures, and enjoy arts, foods, videogames – the stuff that makes life worth living. And besides, poverty <em>itself</em> has horrible impacts on mental and physical health.</p>
|
||||
|
||||
|
@ -322,7 +322,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p>But that's exactly it! “A lockdown isn't a cure, it's just a restart”... <strong>and a fresh start is what we need.</strong></p>
|
||||
|
||||
<p>To understand how Taiwan & South Korea contained COVID-19, we need to understand the exact timeline of a typical COVID-19 infection<sup id="fnref21"><a href="#fn21" rel="footnote">21</a></sup>:</p>
|
||||
<p>To understand how Taiwan & South Korea contained COVID-19, we need to understand the exact timeline of a typical COVID-19 infection<sup id="fnref22"><a href="#fn22" rel="footnote">22</a></sup>:</p>
|
||||
|
||||
<p><img src="pics/timeline1.png" alt=""></p>
|
||||
|
||||
|
@ -330,13 +330,13 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p><img src="pics/timeline2.png" alt=""></p>
|
||||
|
||||
<p>And in fact, 44% of all transmissions are like this: <em>pre</em>-symptomatic! <sup id="fnref22"><a href="#fn22" rel="footnote">22</a></sup></p>
|
||||
<p>And in fact, 44% of all transmissions are like this: <em>pre</em>-symptomatic! <sup id="fnref23"><a href="#fn23" rel="footnote">23</a></sup></p>
|
||||
|
||||
<p>But, if we find <em>and quarantine</em> a symptomatic case's recent close contacts... we stop the spread, by staying one step ahead!</p>
|
||||
|
||||
<p><img src="pics/timeline3.png" alt=""></p>
|
||||
|
||||
<p>This is called <strong>contact tracing</strong>. It's an old idea, was used at an unprecedented scale to contain Ebola<sup id="fnref23"><a href="#fn23" rel="footnote">23</a></sup>, and now it's core part of how Taiwan & South Korea are containing COVID-19!</p>
|
||||
<p>This is called <strong>contact tracing</strong>. It's an old idea, was used at an unprecedented scale to contain Ebola<sup id="fnref24"><a href="#fn24" rel="footnote">24</a></sup>, and now it's core part of how Taiwan & South Korea are containing COVID-19!</p>
|
||||
|
||||
<p>(It also lets us use our limited tests more efficiently, to find pre-symptomatic <span class="nowrap"><icon i></icon>s</span> without needing to test almost everyone.)</p>
|
||||
|
||||
|
@ -352,15 +352,15 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p><img src="pics/dp3t.png" alt=""></p>
|
||||
|
||||
<p>(<a href="https://ncase.me/contact-tracing/">Here's the full comic</a>. Details about "pranking"/false positives/etc in footnote:<sup id="fnref24"><a href="#fn24" rel="footnote">24</a></sup>)</p>
|
||||
<p>(<a href="https://ncase.me/contact-tracing/">Here's the full comic</a>. Details about "pranking"/false positives/etc in footnote:<sup id="fnref25"><a href="#fn25" rel="footnote">25</a></sup>)</p>
|
||||
|
||||
<p>Along with similar teams like TCN Protocol<sup id="fnref25"><a href="#fn25" rel="footnote">25</a></sup> and MIT PACT<sup id="fnref26"><a href="#fn26" rel="footnote">26</a></sup>, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.<sup id="fnref27"><a href="#fn27" rel="footnote">27</a></sup> (Don't trust Google/Apple? Good! The beauty of this system is it doesn't <em>need</em> 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!</p>
|
||||
<p>Along with similar teams like TCN Protocol<sup id="fnref26"><a href="#fn26" rel="footnote">26</a></sup> and MIT PACT<sup id="fnref27"><a href="#fn27" rel="footnote">27</a></sup>, they've inspired Apple & Google to bake privacy-first contact tracing directly into Android/iOS.<sup id="fnref28"><a href="#fn28" rel="footnote">28</a></sup> (Don't trust Google/Apple? Good! The beauty of this system is it doesn't <em>need</em> 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!</p>
|
||||
|
||||
<p>But what about folks without smartphones? Or infections through doorknobs? Or "true" asymptomatic cases? Contact tracing apps can't catch all transmissions... <em>and that's okay!</em> We don't need to catch <em>all</em> transmissions, just 60%+ to get R < 1.</p>
|
||||
|
||||
<p>(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:<sup id="fnref28"><a href="#fn28" rel="footnote">28</a></sup>)</p>
|
||||
<p>(Footnote rant about the confusion between pre-symptomatic vs "true" asymptomatic – "true" asymptomatics are rare:<sup id="fnref29"><a href="#fn29" rel="footnote">29</a></sup>)</p>
|
||||
|
||||
<p>Isolating <em>symptomatic</em> cases would reduce R by up to 40%, and quarantining their <em>pre/a-symptomatic</em> contacts would reduce R by up to 50%<sup id="fnref29"><a href="#fn29" rel="footnote">29</a></sup>:</p>
|
||||
<p>Isolating <em>symptomatic</em> cases would reduce R by up to 40%, and quarantining their <em>pre/a-symptomatic</em> contacts would reduce R by up to 50%<sup id="fnref30"><a href="#fn30" rel="footnote">30</a></sup>:</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-4a&format=calc" width="285" height="340"></iframe>
|
||||
|
@ -409,17 +409,17 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p><em>"Wait,"</em> you might ask, <em>"I thought face masks don't stop you from getting sick?"</em></p>
|
||||
|
||||
<p>You're right. Masks don't stop you from getting sick<sup id="fnref30"><a href="#fn30" rel="footnote">30</a></sup>... they stop you from getting <em>others</em> sick.</p>
|
||||
<p>You're right. Masks don't stop you from getting sick<sup id="fnref31"><a href="#fn31" rel="footnote">31</a></sup>... they stop you from getting <em>others</em> sick.</p>
|
||||
|
||||
<p><img src="pics/masks.png" alt=""></p>
|
||||
|
||||
<p>To put a number on it: surgical masks <em>on the infectious person</em> reduce cold & flu viruses in aerosols by 70%.<sup id="fnref31"><a href="#fn31" rel="footnote">31</a></sup> Reducing transmissions by 70% would be as large an impact as a lockdown!</p>
|
||||
<p>To put a number on it: surgical masks <em>on the infectious person</em> reduce cold & flu viruses in aerosols by 70%.<sup id="fnref32"><a href="#fn32" rel="footnote">32</a></sup> Reducing transmissions by 70% would be as large an impact as a lockdown!</p>
|
||||
|
||||
<p>However, we don't know for sure the impact of masks on COVID-19 <em>specifically</em>. In science, one should only publish a finding if you're 95% sure of it. (...should.<sup id="fnref32"><a href="#fn32" rel="footnote">32</a></sup>) Masks, as of May 1st 2020, are less than "95% sure".</p>
|
||||
<p>However, we don't know for sure the impact of masks on COVID-19 <em>specifically</em>. In science, one should only publish a finding if you're 95% sure of it. (...should.<sup id="fnref33"><a href="#fn33" rel="footnote">33</a></sup>) Masks, as of May 1st 2020, are less than "95% sure".</p>
|
||||
|
||||
<p>However, pandemics are like poker. <strong>Make bets only when you're 95% sure, and you'll lose everything at stake.</strong> As a recent article on masks in the British Medical Journal notes,<sup id="fnref33"><a href="#fn33" rel="footnote">33</a></sup> we <em>have</em> to make cost/benefit analyses under uncertainty. Like so:</p>
|
||||
<p>However, pandemics are like poker. <strong>Make bets only when you're 95% sure, and you'll lose everything at stake.</strong> As a recent article on masks in the British Medical Journal notes,<sup id="fnref34"><a href="#fn34" rel="footnote">34</a></sup> we <em>have</em> to make cost/benefit analyses under uncertainty. Like so:</p>
|
||||
|
||||
<p>Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks<sup id="fnref34"><a href="#fn34" rel="footnote">34</a></sup>), super cheap. If surgical masks, more expensive but still pretty cheap.</p>
|
||||
<p>Cost: If homemade cloth masks (which are ~2/3 as effective as surgical masks<sup id="fnref35"><a href="#fn35" rel="footnote">35</a></sup>), super cheap. If surgical masks, more expensive but still pretty cheap.</p>
|
||||
|
||||
<p>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)</p>
|
||||
|
||||
|
@ -427,7 +427,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
<iframe src="sim?stage=int-6a&format=calc" width="285" height="380"></iframe>
|
||||
</div>
|
||||
|
||||
<p>(other arguments for/against masks:<sup id="fnref35"><a href="#fn35" rel="footnote">35</a></sup>)</p>
|
||||
<p>(other arguments for/against masks:<sup id="fnref36"><a href="#fn36" rel="footnote">36</a></sup>)</p>
|
||||
|
||||
<p>Masks <em>alone</em> 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!</p>
|
||||
|
||||
|
@ -435,7 +435,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p>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 <em>will</em> reduce R.</p>
|
||||
|
||||
<p>For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.<sup id="fnref36"><a href="#fn36" rel="footnote">36</a></sup> The summer-winter difference in New York City is 26°C (47°F),<sup id="fnref37"><a href="#fn37" rel="footnote">37</a></sup> so summer will make R drop by ~31%.</p>
|
||||
<p>For COVID-19, every extra 1° Celsius (1.8° Fahrenheit) makes R drop by 1.2%.<sup id="fnref37"><a href="#fn37" rel="footnote">37</a></sup> The summer-winter difference in New York City is 26°C (47°F),<sup id="fnref38"><a href="#fn38" rel="footnote">38</a></sup> so summer will make R drop by ~31%.</p>
|
||||
|
||||
<div class="sim">
|
||||
<iframe src="sim?stage=int-6b&format=calc" width="285" height="220"></iframe>
|
||||
|
@ -475,7 +475,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p>We hope these plans give you hope. </p>
|
||||
|
||||
<p><strong>Even under a pessimistic scenario, it <em>is</em> possible to beat COVID-19, while protecting our mental and financial health.</strong> Use the lockdown as a "reset button", keep R < 1 with case isolation + privacy-protecting contract tracing + at <em>least</em> cloth masks for all... and life can get back to a normal-ish!</p>
|
||||
<p><strong>Even under a pessimistic scenario, it <em>is</em> possible to beat COVID-19, while protecting our mental and financial health.</strong> Use the lockdown as a "reset button", keep R < 1 with case isolation + privacy-protecting contact tracing + at <em>least</em> cloth masks for all... and life can get back to a normal-ish!</p>
|
||||
|
||||
<p>Sure, you may have dried-out hands. But you'll get to invite a date out to a comics bookstore! You'll get to go out with friends to watch the latest Hollywood cash-grab. You'll get to people-watch at a library, taking joy in people going about the simple business of <em>being alive.</em></p>
|
||||
|
||||
|
@ -495,10 +495,10 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
<p>...<em>for how long?</em></p>
|
||||
|
||||
<ul>
|
||||
<li>COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.<sup id="fnref38"><a href="#fn38" rel="footnote">38</a></sup></li>
|
||||
<li>The coronaviruses that cause "the" common cold give you 8 months of immunity.<sup id="fnref39"><a href="#fn39" rel="footnote">39</a></sup></li>
|
||||
<li>There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.<sup id="fnref40"><a href="#fn40" rel="footnote">40</a></sup></li>
|
||||
<li>One <em>not-yet-peer-reviewed</em> study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.<sup id="fnref41"><a href="#fn41" rel="footnote">41</a></sup></li>
|
||||
<li>COVID-19 is most closely related to SARS, which gave its survivors 2 years of immunity.<sup id="fnref39"><a href="#fn39" rel="footnote">39</a></sup></li>
|
||||
<li>The coronaviruses that cause "the" common cold give you 8 months of immunity.<sup id="fnref40"><a href="#fn40" rel="footnote">40</a></sup></li>
|
||||
<li>There's reports of folks recovering from COVID-19, then testing positive again, but it's unclear if these are false positives.<sup id="fnref41"><a href="#fn41" rel="footnote">41</a></sup></li>
|
||||
<li>One <em>not-yet-peer-reviewed</em> study on monkeys showed immunity to the COVID-19 coronavirus for at least 28 days.<sup id="fnref42"><a href="#fn42" rel="footnote">42</a></sup></li>
|
||||
</ul>
|
||||
|
||||
<p>But for COVID-19 <em>in humans</em>, as of May 1st 2020, "how long" is the big unknown.</p>
|
||||
|
@ -550,7 +550,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
|
||||
<p><strong>To be clear: this is unlikely.</strong> 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. </p>
|
||||
|
||||
<p>Still, infectious disease researchers have expressed worries: What if we can't make enough?<sup id="fnref42"><a href="#fn42" rel="footnote">42</a></sup> What if we rush it, and it's not safe?<sup id="fnref43"><a href="#fn43" rel="footnote">43</a></sup></p>
|
||||
<p>Still, infectious disease researchers have expressed worries: What if we can't make enough?<sup id="fnref43"><a href="#fn43" rel="footnote">43</a></sup> What if we rush it, and it's not safe?<sup id="fnref44"><a href="#fn44" rel="footnote">44</a></sup></p>
|
||||
|
||||
<p>Even in the nightmare "no-vaccine" scenario, we still have 3 ways out. From most to least terrible:</p>
|
||||
|
||||
|
@ -589,7 +589,7 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
</div>
|
||||
</div>
|
||||
|
||||
<p>Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.<sup id="fnref44"><a href="#fn44" rel="footnote">44</a></sup></p>
|
||||
<p>Plane's sunk. We've scrambled onto the life rafts. It's time to find dry land.<sup id="fnref45"><a href="#fn45" rel="footnote">45</a></sup></p>
|
||||
|
||||
<p>Teams of epidemiologists and policymakers (<a href="https://www.americanprogress.org/issues/healthcare/news/2020/04/03/482613/national-state-plan-end-coronavirus-crisis/">left</a>, <a href="https://www.aei.org/research-products/report/national-coronavirus-response-a-road-map-to-reopening/">right</a>, and <a href="https://ethics.harvard.edu/covid-roadmap">multi-partisan</a>) have come to a consensus on how to beat COVID-19, while protecting our lives <em>and</em> liberties.</p>
|
||||
|
||||
|
@ -617,6 +617,8 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
<p>These footnotes will have sources, links, or bonus commentary. Like this commentary! <a href="#fnref1" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>This guide was published on May 1st, 2020.</strong> Many details will become outdated, but we're confident this guide will cover 95% of possible futures, and that Epidemiology 101 will remain forever useful.</p>
|
||||
|
||||
<p>(Update May 15: Added citations for "1 in 20 of infected are hospitalized" and "0.5% of infected die")</p>
|
||||
</li>
|
||||
|
||||
<li id="fn2">
|
||||
|
@ -678,7 +680,15 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
</li>
|
||||
|
||||
<li id="fn13">
|
||||
<p><a href="https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/">"Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"</a>. Between 4.9% to 11.5% of <em>all</em> COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations. <a href="#fnref13" rev="footnote">↩</a></p>
|
||||
<p><strong>[UPDATED MAY 15]</strong> Many of you rightly pointed out that our previous citation for "<strong>1 in 20</strong> need hospitalization" was based off old USA data on <em>confirmed</em> cases – which was way lower than the <em>real</em> number of cases, due to lack of tests. <a href="#fnref13" rev="footnote">↩</a></p>
|
||||
|
||||
<p>So, let's look at the country with the <em>most</em> tests per capita: Iceland. As of May 15th, 2020, they had 115 hospitalized among 1802 confirmed cases ≈ 6.4% hospitalization rate, or <strong>1 in 16</strong>.</p>
|
||||
|
||||
<p><a href="https://science.sciencemag.org/content/early/2020/05/12/science.abc3517">A more recent study of COVID-19 in France</a> – using not just official confirmed cases but also antibody test data – found that “3.6% of infected individuals are hospitalized”. Or, <strong>1 in 28.</strong></p>
|
||||
|
||||
<p>Overall, there's a lot of uncertainty, but "1 in 20" is roughly close. Besides, for the rest of these simulations, we <em>triple</em> hospital capacity – so, even if "1 in 20" is three times too high, the point still stands.</p>
|
||||
|
||||
<p>Old citation: <del><a href="https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/">"Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"</a>. Between 4.9% to 11.5% of <em>all</em> COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations.</del></p>
|
||||
</li>
|
||||
|
||||
<li id="fn14">
|
||||
|
@ -686,77 +696,81 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
</li>
|
||||
|
||||
<li id="fn15">
|
||||
<p>“He says that the actual goal is the same as that of other countries: flatten the curve by staggering the onset of infections. As a consequence, the nation may achieve herd immunity; it’s a side effect, not an aim. [...] The government’s actual coronavirus action plan, available online, doesn’t mention herd immunity at all.” <a href="#fnref15" rev="footnote">↩</a></p>
|
||||
<p><strong>[UPDATED MAY 15]</strong> <a href="https://news.iu.edu/stories/2020/05/iupui/releases/13-preliminary-findings-impact-covid-19-indiana-coronavirus.html">Researchers in Indiana, USA</a> did a random-sample test of the population, and found an infection-fatality rate (IFR) of 0.58%. <a href="#fnref15" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn16">
|
||||
<p>“He says that the actual goal is the same as that of other countries: flatten the curve by staggering the onset of infections. As a consequence, the nation may achieve herd immunity; it’s a side effect, not an aim. [...] The government’s actual coronavirus action plan, available online, doesn’t mention herd immunity at all.” <a href="#fnref16" rev="footnote">↩</a></p>
|
||||
|
||||
<p>From a <a href="https://www.theatlantic.com/health/archive/2020/03/coronavirus-pandemic-herd-immunity-uk-boris-johnson/608065/">The Atlantic article by Ed Yong</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn16">
|
||||
<p>“All eight eligible studies reported that handwashing lowered risks of respiratory infection, with risk reductions ranging from 6% to 44% [pooled value 24% (95% CI 6–40%)].” We rounded up the pooled value to 25% in these simulations for simplicity. <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-3156.2006.01568.x">Rabie, T. and Curtis, V.</a> Note: as this meta-analysis points out, the quality of studies for handwashing (at least in high-income countries) are awful. <a href="#fnref16" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn17">
|
||||
<p>“We found a 73% reduction in the average daily number of contacts observed per participant. This would be sufficient to reduce R0 from a value from 2.6 before the lockdown to 0.62 (0.37 - 0.89) during the lockdown”. We rounded it down to 70% in these simulations for simplicity. <a href="https://cmmid.github.io/topics/covid19/comix-impact-of-physical-distance-measures-on-transmission-in-the-UK.html">Jarvis and Zandvoort et al</a> <a href="#fnref17" rev="footnote">↩</a></p>
|
||||
<p>“All eight eligible studies reported that handwashing lowered risks of respiratory infection, with risk reductions ranging from 6% to 44% [pooled value 24% (95% CI 6–40%)].” We rounded up the pooled value to 25% in these simulations for simplicity. <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-3156.2006.01568.x">Rabie, T. and Curtis, V.</a> Note: as this meta-analysis points out, the quality of studies for handwashing (at least in high-income countries) are awful. <a href="#fnref17" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn18">
|
||||
<p>This distortion would go away if we plotted R on a logarithmic scale... but then we'd have to explain <em>logarithmic scales.</em> <a href="#fnref18" rev="footnote">↩</a></p>
|
||||
<p>“We found a 73% reduction in the average daily number of contacts observed per participant. This would be sufficient to reduce R0 from a value from 2.6 before the lockdown to 0.62 (0.37 - 0.89) during the lockdown”. We rounded it down to 70% in these simulations for simplicity. <a href="https://cmmid.github.io/topics/covid19/comix-impact-of-physical-distance-measures-on-transmission-in-the-UK.html">Jarvis and Zandvoort et al</a> <a href="#fnref18" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn19">
|
||||
<p>“Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022.” <a href="https://science.sciencemag.org/content/early/2020/04/14/science.abb5793">Kissler and Tedijanto et al</a> <a href="#fnref19" rev="footnote">↩</a></p>
|
||||
<p>This distortion would go away if we plotted R on a logarithmic scale... but then we'd have to explain <em>logarithmic scales.</em> <a href="#fnref19" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn20">
|
||||
<p>See <a href="https://journals.sagepub.com/doi/abs/10.1177/1745691614568352">Figure 6 from Holt-Lunstad & Smith 2010</a>. Of course, big disclaimer that they found a <em>correlation</em>. But unless you want to try randomly assigning people to be lonely for life, observational evidence is all you're gonna get. <a href="#fnref20" rev="footnote">↩</a></p>
|
||||
<p>“Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022.” <a href="https://science.sciencemag.org/content/early/2020/04/14/science.abb5793">Kissler and Tedijanto et al</a> <a href="#fnref20" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn21">
|
||||
<p><strong>3 days on average to infectiousness:</strong> “Assuming an incubation period distribution of mean 5.2 days from a separate study of early COVID-19 cases, we inferred that infectiousness started from 2.3 days (95% CI, 0.8–3.0 days) before symptom onset” (translation: Assuming symptoms start at 5 days, infectiousness starts 2 days before = Infectiousness starts at 3 days) <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al.</a> <a href="#fnref21" rev="footnote">↩</a></p>
|
||||
<p>See <a href="https://journals.sagepub.com/doi/abs/10.1177/1745691614568352">Figure 6 from Holt-Lunstad & Smith 2010</a>. Of course, big disclaimer that they found a <em>correlation</em>. But unless you want to try randomly assigning people to be lonely for life, observational evidence is all you're gonna get. <a href="#fnref21" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn22">
|
||||
<p><strong>3 days on average to infectiousness:</strong> “Assuming an incubation period distribution of mean 5.2 days from a separate study of early COVID-19 cases, we inferred that infectiousness started from 2.3 days (95% CI, 0.8–3.0 days) before symptom onset” (translation: Assuming symptoms start at 5 days, infectiousness starts 2 days before = Infectiousness starts at 3 days) <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al.</a> <a href="#fnref22" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>4 days on average to infecting someone else:</strong> “The mean [serial] interval was 3.96 days (95% CI 3.53–4.39 days)” <a href="https://wwwnc.cdc.gov/eid/article/26/6/20-0357_article">Du Z, Xu X, Wu Y, Wang L, Cowling BJ, Ancel Meyers L</a></p>
|
||||
|
||||
<p><strong>5 days on average to feeling symptoms:</strong> “The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days)” <a href="https://annals.org/AIM/FULLARTICLE/2762808/INCUBATION-PERIOD-CORONAVIRUS-DISEASE-2019-COVID-19-FROM-PUBLICLY-REPORTED">Lauer SA, Grantz KH, Bi Q, et al</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn22">
|
||||
<p>“We estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage” <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al</a> <a href="#fnref22" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn23">
|
||||
<p>“Contact tracing was a critical intervention in Liberia and represented one of the largest contact tracing efforts during an epidemic in history.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152989/">Swanson KC, Altare C, Wesseh CS, et al.</a> <a href="#fnref23" rev="footnote">↩</a></p>
|
||||
<p>“We estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage” <a href="https://www.nature.com/articles/s41591-020-0869-5">He, X., Lau, E.H.Y., Wu, P. et al</a> <a href="#fnref23" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn24">
|
||||
<p>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. <a href="#fnref24" rev="footnote">↩</a></p>
|
||||
<p>“Contact tracing was a critical intervention in Liberia and represented one of the largest contact tracing efforts during an epidemic in history.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152989/">Swanson KC, Altare C, Wesseh CS, et al.</a> <a href="#fnref24" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn25">
|
||||
<p>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. <a href="#fnref25" rev="footnote">↩</a></p>
|
||||
|
||||
<p>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 <em>does</em> think Bob's been exposed, it can refer Bob to a <em>manual</em> contact tracer, for an in-depth follow-up interview.</p>
|
||||
|
||||
<p>For other issues like data bandwidth, source integrity, and other security issues, check out <a href="https://github.com/DP-3T/documents#decentralized-privacy-preserving-proximity-tracing">the open-source DP-3T whitepapers!</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn25">
|
||||
<p><a href="https://github.com/TCNCoalition/TCN#tcn-protocol">Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol</a> <a href="#fnref25" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn26">
|
||||
<p><a href="https://pact.mit.edu/">PACT: Private Automated Contact Tracing</a> <a href="#fnref26" rev="footnote">↩</a></p>
|
||||
<p><a href="https://github.com/TCNCoalition/TCN#tcn-protocol">Temporary Contact Numbers, a decentralized, privacy-first contact tracing protocol</a> <a href="#fnref26" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn27">
|
||||
<p><a href="https://www.apple.com/ca/newsroom/2020/04/apple-and-google-partner-on-covid-19-contact-tracing-technology/">Apple and Google partner on COVID-19 contact tracing technology </a>. Note they're not making the apps <em>themselves</em>, just creating the systems that will <em>support</em> those apps. <a href="#fnref27" rev="footnote">↩</a></p>
|
||||
<p><a href="https://pact.mit.edu/">PACT: Private Automated Contact Tracing</a> <a href="#fnref27" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn28">
|
||||
<p>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 <em>ever</em>" (true asymptomatic). The only way you could tell the difference is by following up with cases later. <a href="#fnref28" rev="footnote">↩</a></p>
|
||||
<p><a href="https://www.apple.com/ca/newsroom/2020/04/apple-and-google-partner-on-covid-19-contact-tracing-technology/">Apple and Google partner on COVID-19 contact tracing technology </a>. Note they're not making the apps <em>themselves</em>, just creating the systems that will <em>support</em> those apps. <a href="#fnref28" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn29">
|
||||
<p>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 <em>ever</em>" (true asymptomatic). The only way you could tell the difference is by following up with cases later. <a href="#fnref29" rev="footnote">↩</a></p>
|
||||
|
||||
<p>Which is what <a href="https://wwwnc.cdc.gov/eid/article/26/8/20-1274_article">this study</a> 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."</p>
|
||||
|
||||
<p>So that means "true asymptomatics" are rare, and catching the disease from a true asymptomatic may be even rarer!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn29">
|
||||
<p>From the same Oxford study that first recommended apps to fight COVID-19: <a href="https://science.sciencemag.org/content/early/2020/04/09/science.abb6936/tab-figures-data">Luca Ferretti & Chris Wymant et al</a> See Figure 2. Assuming R<sub>0</sub> = 2.0, they found that: <a href="#fnref29" rev="footnote">↩</a></p>
|
||||
<li id="fn30">
|
||||
<p>From the same Oxford study that first recommended apps to fight COVID-19: <a href="https://science.sciencemag.org/content/early/2020/04/09/science.abb6936/tab-figures-data">Luca Ferretti & Chris Wymant et al</a> See Figure 2. Assuming R<sub>0</sub> = 2.0, they found that: <a href="#fnref30" rev="footnote">↩</a></p>
|
||||
|
||||
<ul>
|
||||
<li>Symptomatics contribute R = 0.8 (40%)</li>
|
||||
|
@ -768,68 +782,68 @@ the <em>second</em>-most important idea in Epidemiology 101:</p>
|
|||
<p>And add up the pre- & a-symptomatic contacts (45% + 5%) and you get 50% of R!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn30">
|
||||
<p>“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” <a href="https://www.sciencedirect.com/science/article/pii/S0196655307007742">Tara Oberg & Lisa M. Brosseau</a> <a href="#fnref30" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn31">
|
||||
<p>“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.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591312/">Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ</a> <a href="#fnref31" rev="footnote">↩</a></p>
|
||||
<p>“None of these surgical masks exhibited adequate filter performance and facial fit characteristics to be considered respiratory protection devices.” <a href="https://www.sciencedirect.com/science/article/pii/S0196655307007742">Tara Oberg & Lisa M. Brosseau</a> <a href="#fnref31" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn32">
|
||||
<p>Any actual scientist who read that last sentence is probably laugh-crying right now. See: <a href="https://en.wikipedia.org/wiki/Data_dredging">p-hacking</a>, <a href="https://en.wikipedia.org/wiki/Replication_crisis">the replication crisis</a>) <a href="#fnref32" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591312/">Milton DK, Fabian MP, Cowling BJ, Grantham ML, McDevitt JJ</a> <a href="#fnref32" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn33">
|
||||
<p>“It is time to apply the precautionary principle” <a href="https://www.bmj.com/content/bmj/369/bmj.m1435.full.pdf">Trisha Greenhalgh et al [PDF]</a> <a href="#fnref33" rev="footnote">↩</a></p>
|
||||
<p>Any actual scientist who read that last sentence is probably laugh-crying right now. See: <a href="https://en.wikipedia.org/wiki/Data_dredging">p-hacking</a>, <a href="https://en.wikipedia.org/wiki/Replication_crisis">the replication crisis</a>) <a href="#fnref33" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn34">
|
||||
<p><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/testing-the-efficacy-of-homemade-masks-would-they-protect-in-an-influenza-pandemic/0921A05A69A9419C862FA2F35F819D55">Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A</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. <a href="#fnref34" rev="footnote">↩</a></p>
|
||||
<p>“It is time to apply the precautionary principle” <a href="https://www.bmj.com/content/bmj/369/bmj.m1435.full.pdf">Trisha Greenhalgh et al [PDF]</a> <a href="#fnref34" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn35">
|
||||
<p><strong>"We need to save supplies for hospitals."</strong> <em>Absolutely agreed.</em> But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. <a href="#fnref35" rev="footnote">↩</a></p>
|
||||
<p><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/testing-the-efficacy-of-homemade-masks-would-they-protect-in-an-influenza-pandemic/0921A05A69A9419C862FA2F35F819D55">Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A</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. <a href="#fnref35" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn36">
|
||||
<p><strong>"We need to save supplies for hospitals."</strong> <em>Absolutely agreed.</em> But that's more of an argument for increasing mask production, not rationing. In the meantime, we can make cloth masks. <a href="#fnref36" rev="footnote">↩</a></p>
|
||||
|
||||
<p><strong>"They're hard to wear correctly."</strong> 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.</p>
|
||||
|
||||
<p><strong>"It'll make people more reckless with handwashing & social distancing."</strong> 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 <em>constant physical reminder</em> to be careful – and in East Asia, masks are also a symbol of solidarity!</p>
|
||||
</li>
|
||||
|
||||
<li id="fn36">
|
||||
<p>“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%. <a href="https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3551767">Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng</a> <a href="#fnref36" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn37">
|
||||
<p>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. <a href="https://www.weather.gov/media/okx/Climate/CentralPark/monthlyannualtemp.pdf">PDF from Weather.gov</a> <a href="#fnref37" rev="footnote">↩</a></p>
|
||||
<p>“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%. <a href="https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3551767">Wang, Jingyuan and Tang, Ke and Feng, Kai and Lv, Weifeng</a> <a href="#fnref37" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn38">
|
||||
<p>“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851497/">Wu LP, Wang NC, Chang YH, et al.</a> "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. <a href="#fnref38" rev="footnote">↩</a></p>
|
||||
<p>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. <a href="https://www.weather.gov/media/okx/Climate/CentralPark/monthlyannualtemp.pdf">PDF from Weather.gov</a> <a href="#fnref38" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn39">
|
||||
<p>“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.” <a href="http://www.columbia.edu/%7Ejls106/galanti_shaman_ms_supp.pdf">Marta Galanti & Jeffrey Shaman (PDF)</a> <a href="#fnref39" rev="footnote">↩</a></p>
|
||||
<p>“SARS-specific antibodies were maintained for an average of 2 years [...] Thus, SARS patients might be susceptible to reinfection ≥3 years after initial exposure.” <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851497/">Wu LP, Wang NC, Chang YH, et al.</a> "Sadly" we'll never know how long SARS immunity would have really lasted, since we eradicated it so quickly. <a href="#fnref39" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn40">
|
||||
<p>“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.” <a href="https://www.statnews.com/2020/04/20/everything-we-know-about-coronavirus-immunity-and-antibodies-and-plenty-we-still-dont/">from STAT News by Andrew Joseph</a> <a href="#fnref40" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="http://www.columbia.edu/%7Ejls106/galanti_shaman_ms_supp.pdf">Marta Galanti & Jeffrey Shaman (PDF)</a> <a href="#fnref40" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn41">
|
||||
<p>From <a href="https://www.biorxiv.org/content/10.1101/2020.03.13.990226v1.abstract">Bao et al.</a> <em>Disclaimer: This article is a preprint and has not been certified by peer review (yet).</em> Also, to emphasize: they only tested re-infection 28 days later. <a href="#fnref41" rev="footnote">↩</a></p>
|
||||
<p>“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.” <a href="https://www.statnews.com/2020/04/20/everything-we-know-about-coronavirus-immunity-and-antibodies-and-plenty-we-still-dont/">from STAT News by Andrew Joseph</a> <a href="#fnref41" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn42">
|
||||
<p>“If a coronavirus vaccine arrives, can the world make enough?” <a href="https://www.nature.com/articles/d41586-020-01063-8">by Roxanne Khamsi, on Nature</a> <a href="#fnref42" rev="footnote">↩</a></p>
|
||||
<p>From <a href="https://www.biorxiv.org/content/10.1101/2020.03.13.990226v1.abstract">Bao et al.</a> <em>Disclaimer: This article is a preprint and has not been certified by peer review (yet).</em> Also, to emphasize: they only tested re-infection 28 days later. <a href="#fnref42" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn43">
|
||||
<p>“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” <a href="https://www.nature.com/articles/d41586-020-00751-9">by Shibo Jiang, on Nature</a> <a href="#fnref43" rev="footnote">↩</a></p>
|
||||
<p>“If a coronavirus vaccine arrives, can the world make enough?” <a href="https://www.nature.com/articles/d41586-020-01063-8">by Roxanne Khamsi, on Nature</a> <a href="#fnref43" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn44">
|
||||
<p>Dry land metaphor <a href="https://www.statnews.com/2020/04/01/navigating-covid-19-pandemic/">from Marc Lipsitch & Yonatan Grad, on STAT News</a> <a href="#fnref44" rev="footnote">↩</a></p>
|
||||
<p>“Don’t rush to deploy COVID-19 vaccines and drugs without sufficient safety guarantees” <a href="https://www.nature.com/articles/d41586-020-00751-9">by Shibo Jiang, on Nature</a> <a href="#fnref44" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
<li id="fn45">
|
||||
<p>Dry land metaphor <a href="https://www.statnews.com/2020/04/01/navigating-covid-19-pandemic/">from Marc Lipsitch & Yonatan Grad, on STAT News</a> <a href="#fnref45" rev="footnote">↩</a></p>
|
||||
</li>
|
||||
|
||||
</ol>
|
||||
|
|
|
@ -37,6 +37,8 @@ This guide (published May 1st, 2020. click this footnote!→[^timestamp]) is mea
|
|||
[^timestamp]: These footnotes will have sources, links, or bonus commentary. Like this commentary!
|
||||
|
||||
**This guide was published on May 1st, 2020.** Many details will become outdated, but we're confident this guide will cover 95% of possible futures, and that Epidemiology 101 will remain forever useful.
|
||||
|
||||
(Update May 15: Added citations for "1 in 20 of infected are hospitalized" and "0.5% of infected die")
|
||||
|
||||
So, buckle in: we're about to experience some turbulence.
|
||||
|
||||
|
@ -121,7 +123,7 @@ starts at just 0.001% <span class="nowrap"><icon i></icon>:</span>
|
|||
|
||||
And *that's* where that famous curve comes from! It's not a bell curve, it's not even a "log-normal" curve. It has no name. But you've seen it a zillion times, and beseeched to flatten.
|
||||
|
||||
This is the the **SIR Model**,[^sir]
|
||||
This is the **SIR Model**,[^sir]
|
||||
(<icon s></icon>**S**usceptible <icon i></icon>**I**nfectious <icon r></icon>**R**ecovered)
|
||||
the *second*-most important idea in Epidemiology 101:
|
||||
|
||||
|
@ -247,9 +249,17 @@ Brace yourselves for an emergency landing...
|
|||
|
||||
###Scenario 0: Do Absolutely Nothing
|
||||
|
||||
Around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).[^icu_covid] In a rich country like the USA, there's 1 ICU bed per 3400 people.[^icu_us] Therefore, the USA can handle 20 out of 3400 people being *simultaneously* infected – or, 0.6% of the population.
|
||||
*Roughly* around 1 in 20 people infected with COVID-19 need to go to an ICU (Intensive Care Unit).[^icu_covid] In a rich country like the USA, there's 1 ICU bed per 3400 people.[^icu_us] Therefore, the USA can handle 20 out of 3400 people being *simultaneously* infected – or, 0.6% of the population.
|
||||
|
||||
[^icu_covid]: ["Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"](https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/). Between 4.9% to 11.5% of *all* COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations.
|
||||
[^icu_covid]: **[UPDATED MAY 15]** Many of you rightly pointed out that our previous citation for "**1 in 20** need hospitalization" was based off old USA data on *confirmed* cases – which was way lower than the *real* number of cases, due to lack of tests.
|
||||
|
||||
So, let's look at the country with the *most* tests per capita: Iceland. As of May 15th, 2020, they had 115 hospitalized among 1802 confirmed cases ≈ 6.4% hospitalization rate, or **1 in 16**.
|
||||
|
||||
[A more recent study of COVID-19 in France](https://science.sciencemag.org/content/early/2020/05/12/science.abc3517) – using not just official confirmed cases but also antibody test data – found that “3.6% of infected individuals are hospitalized”. Or, **1 in 28.**
|
||||
|
||||
Overall, there's a lot of uncertainty, but "1 in 20" is roughly close. Besides, for the rest of these simulations, we *triple* hospital capacity – so, even if "1 in 20" is three times too high, the point still stands.
|
||||
|
||||
Old citation: ~~["Percentage of COVID-19 cases in the United States from February 12 to March 16, 2020 that required intensive care unit (ICU) admission, by age group"](https://www.statista.com/statistics/1105420/covid-icu-admission-rates-us-by-age-group/). Between 4.9% to 11.5% of *all* COVID-19 cases required ICU. Generously picking the lower range, that's 5% or 1 in 20. Note that this total is specific to the US's age structure, and will be higher in countries with older populations, lower in countries with younger populations.~~
|
||||
|
||||
[^icu_us]: “Number of ICU beds = 96,596”. From [the Society of Critical Care Medicine](https://sccm.org/Blog/March-2020/United-States-Resource-Availability-for-COVID-19) USA Population was 328,200,000 in 2019. 96,596 out of 328,200,000 = roughly 1 in 3400.
|
||||
|
||||
|
@ -264,7 +274,9 @@ Not good.
|
|||
That's what [the March 16 Imperial College report](http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/) found: do nothing, and we run out of ICUs, with more than 80% of the population getting infected.
|
||||
(remember: total cases *overshoots* herd immunity)
|
||||
|
||||
Even if only 0.5% of infected die – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... *IF we did nothing.*
|
||||
Even if only 0.5% of infected die[^ifr] – a generous assumption when there's no more ICUs – in a large country like the US, with 300 million people, 0.5% of 80% of 300 million = still 1.2 million dead... *IF we did nothing.*
|
||||
|
||||
[^ifr]: **[UPDATED MAY 15]** [Researchers in Indiana, USA](https://news.iu.edu/stories/2020/05/iupui/releases/13-preliminary-findings-impact-covid-19-indiana-coronavirus.html) did a random-sample test of the population, and found an infection-fatality rate (IFR) of 0.58%.
|
||||
|
||||
(Lots of news & social media reported "80% will be infected" *without* "IF WE DO NOTHING". Fear was channelled into clicks, not understanding. *Sigh.*)
|
||||
|
||||