{"id":13379,"date":"2020-05-05T15:35:15","date_gmt":"2020-05-05T19:35:15","guid":{"rendered":"http:\/\/stateofthenation.co\/?p=13379"},"modified":"2020-05-05T15:35:15","modified_gmt":"2020-05-05T19:35:15","slug":"why-did-the-imperial-college-of-london-use-totally-fake-models-to-predict-over-2-2-million-american-deaths","status":"publish","type":"post","link":"http:\/\/stateofthenation.co\/?p=13379","title":{"rendered":"Why did the Imperial College of London use totally fake models to predict over 2.2 million American deaths?!"},"content":{"rendered":"<header class=\"blog-post-header mb-4\">\n<h1 class=\"mb-2 h2 heading\">How One Model Simulated 2.2 Million U.S. Deaths from COVID-19<\/h1>\n<p><!--more-->By Alan Reynolds<br \/>\nCATO Institute<\/p>\n<p>When it came to dealing with an unexpected surge in infections and deaths from SARS\u2010\u200bCoV\u2010\u200b2 (the virus causing COVID-19 symptoms), federal and state policymakers understandably sought guidance from competing epidemiological computer models. On March 16, a 20\u2010\u200bpage report from Neil Ferguson\u2019s team at Imperial College London quickly gathered enormous attention by producing enormous death estimates. Dr. Ferguson had previously publicized almost equally\u00a0<a href=\"https:\/\/www.spectator.co.uk\/article\/six-questions-that-neil-ferguson-should-be-asked\/amp\">sensational death estimates<\/a>\u00a0from mad cow disease, bird flu and swine flu.<\/p>\n<\/header>\n<div>\n<div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">\n<div class=\"align-center embedded-entity\" data-embed-button=\"promo_block\" data-entity-embed-display=\"view_mode:block_content.full\" data-entity-embed-display-settings=\"internal:\/research\/covid-19\" data-entity-type=\"block_content\" data-entity-uuid=\"3100ed49-a16e-4270-8d9b-8c9aa44dea27\" data-langcode=\"en\">\n<div class=\"promo-block clearfix spacer--standout block--standout bg--standout block p-standard\">\n<div class=\"block--inner\">\n<h3 class=\"mb-md-4 heading\"><a href=\"https:\/\/www.cato.org\/research\/covid-19\">Frequently Asked Questions about COVID-19<\/a><\/h3>\n<ul>\n<li><strong>How should the government approach this pandemic?<\/strong>\n<ul>\n<li><a href=\"https:\/\/www.cato.org\/publications\/commentary\/covid-19-response-critical-guidelines-policymakers\">COVID-19 Response: Critical Guidelines for Policymakers<\/a><\/li>\n<\/ul>\n<\/li>\n<li><strong>Does immigration affect COVID-19 rates?<\/strong>\n<ul>\n<li><a href=\"https:\/\/www.cato.org\/blog\/no-mr-president-immigration-not-correlated-covid-19-united-states\">\u201cNo, Mr. President, Immigration Is Not Correlated with COVID-19\u00a0in the United States<\/a>,\u201d by Alex Nowrasteh and Andrew C. Forrester<\/li>\n<\/ul>\n<\/li>\n<li><strong>How do we keep our liberty during this crisis?<\/strong>\n<ul>\n<li>\u201c<a href=\"https:\/\/www.cato.org\/publications\/commentary\/preventing-liberty-becoming-coronavirus-fatality\">Preventing Liberty from Becoming a\u00a0Coronavirus Fatality,\u201d<\/a>\u00a0by Ted Galen Carpenter<\/li>\n<\/ul>\n<\/li>\n<li><strong>Need help with homeschooling?<\/strong>\n<ul>\n<li><a href=\"https:\/\/www.cato.org\/publications\/commentary\/i-homeschool-kids-here-are-6-ideas-parents-while-schools-are-closed\">\u201cI Homeschool My Kids. Here Are 6\u00a0Ideas for Parents While Schools Are Closed,\u201d<\/a>\u00a0by Kerry McDonald<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<div class=\"mt-md-4 mt-standard field field-name-field-call-to-action\"><span id=\"hs-cta-wrapper-d3308680-4313-468d-b361-e7a6da28ca98\" class=\"hs-cta-wrapper\"><span id=\"hs-cta-d3308680-4313-468d-b361-e7a6da28ca98\" class=\"hs-cta-node hs-cta-d3308680-4313-468d-b361-e7a6da28ca98\" data-hs-drop=\"true\"><a id=\"cta_button_4957480_fd55fce6-ffb6-496c-97a1-de14e0eddc36\" class=\"cta_button btn btn-primary\" title=\"Learn more\" href=\"https:\/\/events.cato.org\/cs\/c\/?cta_guid=fd55fce6-ffb6-496c-97a1-de14e0eddc36&amp;placement_guid=d3308680-4313-468d-b361-e7a6da28ca98&amp;portal_id=4957480&amp;canon=https%3A%2F%2Fwww.cato.org%2Fblog%2Fhow-one-model-simulated-22-million-us-deaths-covid-19&amp;redirect_url=APefjpFMhTfzpb3QDdnuXHo9g_vONY7wqaQP8eUb65eLuN1JQGFSccM9s1IUFvB2LbMbyuifMxlFN4latHxsUvYod_X6kfh2yMlVlJLUOkUt1DZvclOBJujHc4lFLzkNh_Ww-DwsR2ugJU9brGy0PXPxL-oRYQ9fu-y6Qil80nHxbR_PmWHjQllLhIchAN3pkLhND9xN2_Ff_dmaagyhbxU4jHDQMRNObP-p34F-7NKPPDs4CRL2ri3SEDL1d8M8p5y5_GWJnJ5Nxl93vWCy1VzBXqSLtUQmfw&amp;click=4cc05b5d-8766-46e6-9636-21e9e1271c2f&amp;hsutk=2412c602ae50be6b37dea41fd80c4a2b&amp;signature=AAH58kEYzSldnhhGnC3XCwR0FaBTB0yiCg&amp;utm_referrer=https%3A%2F%2Fwww.google.com%2F&amp;__hstc=38939644.2412c602ae50be6b37dea41fd80c4a2b.1588706352214.1588706352214.1588706352214.1&amp;__hssc=38939644.1.1588706352215&amp;__hsfp=688129454\" target=\"_blank\" rel=\"noopener noreferrer\">LEARN MORE<\/a><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><a href=\"https:\/\/www.nytimes.com\/2020\/03\/17\/world\/europe\/coronavirus-imperial-college-johnson.html\">The New York Times<\/a>\u00a0quickly ran the hot news about this new COVID-19 estimate:<\/p>\n<blockquote><p>The report, which warned that an uncontrolled spread of the disease could cause as many as 510,000 deaths in Britain, triggered a\u00a0sudden shift in the government\u2019s comparatively relaxed response to the virus. American officials said the report, which projected up to 2.2 million deaths in the United States from such a\u00a0spread, also influenced the White House to strengthen its measures to isolate members of the public.<\/p><\/blockquote>\n<p>A month later that 2.2 million estimate was still being used (without revealing the source) by President Trump and Doctors Fauci and Birx to imply that up to\u00a0<a href=\"https:\/\/www.cato.org\/blog\/did-mitigation-save-two-million-lives\">two million lives had been saved<\/a>\u00a0by state lockdowns and business closings and\/\u200bor by federal travel bans.<\/p>\n<p>The following summary of the Ferguson\/\u200bImperial College report provides clues about how the model came to generate such dramatic conclusions:<\/p>\n<blockquote><p>In the (unlikely) absence of any control measures or spontaneous changes in individual behavior, we would expect a\u00a0peak in mortality (daily deaths) to occur after approximately 3\u00a0months. In such scenarios, given an estimated R0 of 2.4, we predict 81% of the G.B. and U.S. populations would be infected over the course of the epidemic\u2026 In total, in an unmitigated epidemic, we would predict approximately 510,000 deaths in G.B. and 2.2 million in the U.S., not accounting for the potential negative effects of health systems being overwhelmed on mortality.<\/p><\/blockquote>\n<p>This worst\u2010\u200bcase simulation came up with 2.2 million deaths by simply assuming that\u00a0<a href=\"https:\/\/www.hpnonline.com\/infection-prevention\/screening-surveillance\/article\/21130206\/covid19-predicted-to-infect-81-of-us-population-cause-22-million-deaths-in-us\">81% of the population<\/a>\u00a0gets infected \u00ad\u2013268 million people\u2013 and that 0.9% of them die. It did\u00a0<em>not\u00a0<\/em>assume health systems would have to be overwhelmed to result in so many deaths, though it did make that prediction.<\/p>\n<p>Neither the high infection rate nor the high fatality rate holds up under scrutiny.<\/p>\n<p>To project that nearly everyone becomes infected the report had to assume that each person infects 2.4 others and those people, in turn, infect 2.4 others and so on, with the result that the number infected doubles roughly every four days. This 2.4 \u201creproduction number\u201d (R0) was \u201cbased on \u2026 the early growth\u2010\u200brate of the epidemic in Wuhan.\u201d But the reproduction number always appears highest during the early phase of an epidemic (partly due to increased testing) and has now fallen to nearly zero in China.<\/p>\n<p>The reproduction number is not a\u00a0constant, but a\u00a0variable that depends on many other things, from humidity and sunlight to human behavior.<\/p>\n<p>Suppose an infected man walks into a\u00a0small elevator with three other people and begins coughing. The other three get infected from droplets in the air or from virus on objects (such as elevator buttons) they touch before touching their faces. In this case, we observe an R0 of 3.0. But if the coughing man is wearing a\u00a0mask then perhaps one person does not become infected by inhaling the virus, so the R0 falls to 2.0. If the other two quickly use an alcohol\u2010\u200bbased hand sanitizer before touching their face, or wash their hands, then nobody becomes infected and the R0 falls to zero.<\/p>\n<p>The worst\u2010\u200bcase Imperial College estimate of 2.2 million deaths if everyone does \u201cnothing\u201d did\u00a0<em>not<\/em>\u00a0simply mean no government lockdowns, as a\u00a0March 31 White House graph with two curves implied. It meant nobody avoids crowded elevators, or wears face masks, washes their hands more often, or buys gloves or hand sanitizer. Everyone does literally nothing to avoid danger.The Ferguson team knew that was unrealistic, yet their phantasmal 2.2 million estimate depended on it. As they reticently acknowledged, \u201cit is highly likely that there would be significant spontaneous change in population behavior even in the absence of government\u2010\u200bmandated interventions.\u201d An earlier\u00a0<a href=\"https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/873723\/03-potential-effect-of-non-pharmaceutical-interventions-npis-on-a-Covid-19-epidemic-in-the-UK.pdf\">February 20<\/a>\u00a0brief said, \u201cSome social distancing is to be expected, even in the absence of formal control measures.\u201d<\/p>\n<p>The obvious reality of voluntary self\u2010\u200bprotective actions makes it incorrect to allude to the extreme Ferguson death estimate, consciously or not, as evidence that heavy\u2010\u200bhanded government interventions prevented\u00a0<a href=\"https:\/\/www.wsj.com\/articles\/americans-need-forbearance-not-more-stimulus-11587422691\">\u201chundreds of thousands\u201d<\/a>\u00a0of deaths. In fact, the Imperial College team\u00a0<a href=\"https:\/\/www.forbes.com\/sites\/bjornlomborg\/2020\/04\/09\/save-lives-and-avoid-a-catastrophic-recession\/#5a57037c6f92\">did\u00a0<em>not\u00a0<\/em>recommend \u201ca complete lockdown<\/a>\u00a0which \u2026 prevents people going to work.\u201d<\/p>\n<p>The key premise of 81% of the population being infected should have raised more alarms than it did. Even the deadly \u201c<a href=\"https:\/\/www.livescience.com\/worst-epidemics-and-pandemics-in-history.html\">Spanish Flu<\/a>\u201d (H1N1) pandemic of 1918\u201319 infected no more than\u00a0<a href=\"https:\/\/web.archive.org\/web\/20160923152823\/http:\/www.flu.gov\/pandemic\/history\/1918\/\">28% of the U.S. population<\/a>. The next H1N1 \u201cSwine Flu\u201d pandemic in 2009-10, infected 20-<a href=\"https:\/\/www.cidrap.umn.edu\/news-perspective\/2013\/01\/study-puts-global-2009-pandemic-h1n1-infection-rate-24\">24%<\/a>\u00a0of Americans.<\/p>\n<p>To push the percentage infected up from 20\u201328% to an unprecedented 81% for COVID-19 required assuming the number of cases and\/\u200bor deaths keeps doubling every three or four days for months (deaths were predicted\u00a0to peak July 20). And that means assuming the estimated reproduction number (R0) of 2.4 remains high, and people keep mingling with different groups,\u00a0until nearly everyone gets infected. Long before 8\u00a0out of 10 people became infected, however, a\u00a0larger and larger percentage of the population would have recovered from the disease and become immune, so a\u00a0smaller and smaller share would still remain susceptible.<\/p>\n<p>Little more than a\u00a0month after the outbreak exploded in March, COVID-19 curves are already flattening conclusively in many different countries with quite different government mitigation policies. By April 16, it was taking\u00a0<a href=\"https:\/\/ourworldindata.org\/coronavirus\">60\u00a0days for the number of deaths to double in China<\/a>\u00a0\u2013 not 4\u00a0days. The worldwide average was up to 11\u00a0days, including 17\u00a0days in Italy, 18\u00a0days in Taiwan, and 24\u00a0in South Korea.<\/p>\n<p>In short, the Imperial College projection that 81% of the U.S. population could be infected if everyone just did literally nothing to protect themselves or others is inconsistent with rational risk avoidance, history and recent experience. Even with a\u00a0much smaller percentage infected, however, deaths could still end up extremely high if nearly 1% of those infected died, as the Ferguson team assumed.<\/p>\n<p>The assumed 0.9% death rate (within a\u00a0range of 0.4% to 1.4%) was tweaked from a\u00a0smaller estimate in a\u00a0study of deaths in China by\u00a0<a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2020.03.09.20033357v1\">Robert Verrity<\/a>\u00a0and others, which found a \u201c<em>case<\/em>\u00a0fatality rate\u201d (CFR) of 1.38% among known and tested cases. By assuming that such confirmed cases underestimated actual infections by only about half, they inferred an \u201c<em>infection\u00a0<\/em>fatality rate\u201d (IFR) of 0.66%.<\/p>\n<p>Epidemiologists have since found growing\u00a0<a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2020.03.24.20042291v1\">evidence<\/a>\u00a0that the number of\u00a0<a href=\"https:\/\/www.statnews.com\/2020\/03\/17\/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data\/\">undetected cases with few symptoms or none<\/a>\u00a0is much larger than merely doubling the\u00a0<a href=\"https:\/\/reason.com\/wp-content\/uploads\/2020\/04\/Bommer-Vollmer-2020-COVID-19-detection-April-2nd.pdf\">small number<\/a>\u00a0of known and tested cases. A\u00a0review of such research by the Oxford University\u00a0<a href=\"https:\/\/www.cebm.net\/covid-19\/global-covid-19-case-fatality-rates\/\">Centre for Evidence\u2010\u200bBased Medicine<\/a>\u00a0finds \u201ca presumed estimate for the COVID-19 IFR somewhere between 0.1% and 0.36%.\u201d A\u00a0middling estimate of 0.22% would by itself reduce the infamous 2.2 million death estimate to half a\u00a0million even if 81% were somehow infected.<\/p>\n<p><a href=\"https:\/\/www.wsj.com\/articles\/is-the-coronavirus-as-deadly-as-they-say-11585088464\">Eran Bendavid and Jay Bhattacharya<\/a>\u00a0of the Stanford School of Medicine, with 15 others, conducted serological tests for COVID-19 antibodies from a\u00a0representative sample of 3,300 people from Santa Clara County, CA. The high percentage showing proof of having been cured of undetected asymptomatic cases indicates that between 48,000 to 81,000 people in Santa Clara county had already been infected and cured by the time they were tested on April 3\u20134. Those numbers are 50 to 85 times larger than the number of known, confirmed cases. They correspond to \u201can infection fatality rate of 0.12\u20130.2%\u201d \u2013 similar to the flu (which nonetheless killed a\u00a0CDC\u2010\u200bestimated 61,000\u00a0in the 2017\/18 season by infecting millions).<\/p>\n<p>The Santa Clara antibody testing strongly suggests there must be sizable islands or clusters of people elsewhere in the U.S. who now have some immunity, which would substantially reduce the future risk of community spread. This is one reason any \u201crebound\u201d in the fourth quarter would likely be more easily contained, even aside from the fact that we\u2019re all much better educated, equipped and prepared if hot spots flare up in the fall. Because a\u00a0newer and better\u00a0<a href=\"https:\/\/covid19.healthdata.org\/united-states-of-america\">Washington University IHME model<\/a>\u00a0ends with August 4, its low estimate of COVID-19 deaths (under 61,000 as of April 15) misses five months of 2020 and is therefore surely too optimistic for the whole year. Yet the IHME estimates will nonetheless prove enormously closer to reality than the archaic overstuffed Imperial College prediction of 2.2 million deaths.<\/p>\n<p>The trouble with being too easily led by models is we can too easily be misled by models. Epidemic models may seem entirely different from economic models or climate models, but they all make terrible forecasts if filled with wrong assumptions and parameters.<\/p>\n<p>___<br \/>\n<a href=\"https:\/\/www.cato.org\/blog\/how-one-model-simulated-22-million-us-deaths-covid-19\">https:\/\/www.cato.org\/blog\/how-one-model-simulated-22-million-us-deaths-covid-19<\/a><\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>How One Model Simulated 2.2 Million U.S. Deaths from COVID-19<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-13379","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"http:\/\/stateofthenation.co\/index.php?rest_route=\/wp\/v2\/posts\/13379","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/stateofthenation.co\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/stateofthenation.co\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/stateofthenation.co\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/stateofthenation.co\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=13379"}],"version-history":[{"count":0,"href":"http:\/\/stateofthenation.co\/index.php?rest_route=\/wp\/v2\/posts\/13379\/revisions"}],"wp:attachment":[{"href":"http:\/\/stateofthenation.co\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13379"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/stateofthenation.co\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13379"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/stateofthenation.co\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13379"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}