{"id":6534,"date":"2020-04-27T19:13:17","date_gmt":"2020-04-27T19:13:17","guid":{"rendered":"https:\/\/firsteval.com\/?p=6534"},"modified":"2020-07-07T21:47:37","modified_gmt":"2020-07-07T21:47:37","slug":"covid-19-curve-flattening-models-and-garbage-data","status":"publish","type":"post","link":"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/","title":{"rendered":"COVID-19: Curve-Flattening, Models, and Garbage Data"},"content":{"rendered":"

We\u2019ve been surrounded lately with an abundance of news that has forced the field of epidemiology (statistics related to diseases and applied to public health) into our thoughts. Epidemiologists are experts specifically in the prevalence and spread of diseases, like COVID-19, among populations. And, while epidemiologists are statisticians, not all statisticians are trained in epi stats or public health.<\/p>\n

I am not an epidemiologist. Yet, like all statisticians, I\u2019ve been trained to sniff out sound statistical measurement, good data, and most of all, find other experts who know what they are talking about much more than I do.<\/p>\n

I\u2019ll share with you what I\u2019ve been reading, who I\u2019m paying attention to, and what perks my ears from the news.<\/p>\n

The Ubiquitous Curve<\/u><\/p>\n

If nothing else recently, the typical consumer of news has absorbed fantastic data visualization lessons \u2013 both in \u201cflattening the curve\u201d and in guessing the alphabet letter shape chart our economic recovery will take.<\/p>\n

What is the curve? The curve we are eager to flatten represents the pace of deaths or disease from COVID-19. If the pace is too forceful, and the curve shoots up high very quickly, we overwhelm our healthcare system. To disperse demand for COVID-19-related healthcare, we\u2019ve tried to flatten, or spread out the curve. To be clear, flattening the curve doesn\u2019t lessen the raw number of disease cases, it merely spreads the cases out, slowing the spread and pace of cases. In theory, even if we \u201cflatten the curve,\u201d we may have the same number of COVID-19 cases.<\/p>\n

Cathy O\u2019Neil (mathematician worth reading #1) warns us here<\/a> that this \u201ccurve\u201d we\u2019ve been seeing depicted as an actual curve in news visualizations may not actually be curve-shaped. To date, the second half of the curve is a guess, as it is still in the future. It may be asymmetrical. It may level off after it peaks. It may peak again. Importantly, we can\u2019t expect diseases to lessen at the same rate that they increased. Hence, we can\u2019t predict how long the COVID-19 crisis will last.<\/p>\n

Models and Garbage Data<\/u><\/p>\n

Another term news-consumers are being bombarded with: models. Statistical modeling is not the same as just an algorithm or a formula itself, it\u2019s the application of an algorithm or formula to a set of data to predict what may happen. There are two pieces here. Modeling requires both a valid algorithm and valid data. Both must be correct for the model to produce a usable prediction.<\/p>\n

\"\"
No, not that kind of models.<\/figcaption><\/figure>\n

Hence our challenge. Not only do we not have a known formula for the model (new virus \u2013 what shape will its path take?), we also don\u2019t have valid data (disease case prevalence, death rates, etc.). In fact, we have the opposite \u2013 we have garbage data. Many models are dogs that won\u2019t hunt. While we can know (to some validity) raw counts of hospitalizations and deaths, we can\u2019t know number of people infected because of a lack of tests (at least in the U.S.). And, we need both of those numbers to calculate the illness rate and death rate. In one sense, the lack of tests for COVID-19\u2019s prevalence stairsteps us down to numerous other incorrect and incalculable statistics.<\/p>\n

Who Should We Listen To?<\/u><\/p>\n

Here\u2019s my personal decision rule: listen to those that caveat themselves. Accurate models for COVID-19 don\u2019t exist, but some models are better than others. If an expert or a model does not include caveats or a description of likely errors, ignore it. Johns Hopkins University\u2019s map<\/a> is clear what it is measuring \u2013 number tested, and number of deaths reported. Nigel Marriott has a fantastic compilation<\/a> of credible COVID-19 data sources. Finally, the UK\u2019s Royal Statistical Society spells out all of this clearly in their Statistician\u2019s Guide to Coronavirus Numbers<\/a>. Consume COVID-19 data numbers with an abundance of skepticism.<\/p>\n

 <\/p>\n

(I can\u2019t help all of the dog analogies. I\u2019ve just adopted a snuggly St. Bernard to be a sibling to my older lab.)<\/p>\n

\"\"
Phoebe, the St. Bernard quarantine rescue, likes to lay on feet.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"

We\u2019ve been surrounded lately with an abundance of news that has forced the field of epidemiology (statistics related to diseases and applied to public health) into our thoughts. Epidemiologists are experts specifically in the prevalence and spread of diseases, like COVID-19, among populations. And, while epidemiologists are statisticians, not all statisticians are trained in epi …<\/p>\n

COVID-19: Curve-Flattening, Models, and Garbage Data<\/span> Read More »<\/a><\/p>\n","protected":false},"author":3,"featured_media":6780,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50],"tags":[120,77,121,89],"yoast_head":"\nCOVID-19: Curve-Flattening, Models, and Garbage Data - Melissa Kovacs, FirstEval<\/title>\n<meta name=\"description\" content=\"What I\u2019ve been reading, who I\u2019m paying attention to, and COVID-19 data models.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"COVID-19: Curve-Flattening, Models, and Garbage Data - Melissa Kovacs, FirstEval\" \/>\n<meta property=\"og:description\" content=\"What I\u2019ve been reading, who I\u2019m paying attention to, and COVID-19 data models.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\" \/>\n<meta property=\"og:site_name\" content=\"FirstEval-Melissa Kovacs\" \/>\n<meta property=\"article:published_time\" content=\"2020-04-27T19:13:17+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-07-07T21:47:37+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/firsteval.com\/wp-content\/uploads\/2020\/07\/PAT_196050-2-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1707\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Melissa Kovacs\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@https:\/\/twitter.com\/firsteval\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Melissa Kovacs\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\"},\"author\":{\"name\":\"Melissa Kovacs\",\"@id\":\"https:\/\/firsteval.com\/#\/schema\/person\/42834112e101666b9941ee9531959d4b\"},\"headline\":\"COVID-19: Curve-Flattening, Models, and Garbage Data\",\"datePublished\":\"2020-04-27T19:13:17+00:00\",\"dateModified\":\"2020-07-07T21:47:37+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\"},\"wordCount\":715,\"publisher\":{\"@id\":\"https:\/\/firsteval.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/firsteval.com\/wp-content\/uploads\/2020\/07\/PAT_196050-2-scaled.jpg\",\"keywords\":[\"COVID-19\",\"data\",\"statistical models\",\"statistics\"],\"articleSection\":[\"News from FirstEval\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\",\"url\":\"https:\/\/firsteval.com\/covid-19-curve-flattening-models-and-garbage-data\/\",\"name\":\"COVID-19: Curve-Flattening, Models, and Garbage Data - 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