{"id":6480,"date":"2020-06-12T21:47:00","date_gmt":"2020-06-13T02:47:00","guid":{"rendered":"https:\/\/arch.tamu.edu.staging2.juiceboxint.com\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/"},"modified":"2022-06-27T14:38:54","modified_gmt":"2022-06-27T19:38:54","slug":"cosc-prof-refines-covid-19-statistical-model","status":"publish","type":"post","link":"https:\/\/www.arch.tamu.edu\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/","title":{"rendered":"Construction science prof refines COVID-19 statistical model"},"content":{"rendered":"

A model developed by Chinese researchers that health experts commonly use to predict coronavirus fatality rates has a narrower gap between predicted coronavirus cases and actual cases after it\u2019s modified with tweaks created by John Nichols, associate professor of construction science<\/a>, who has decades of experience as a statistical analyst.<\/p>\n

The predictions that public health experts make about infectious outbreaks such as coronavirus are based on what\u2019s called a SEIR model. The acronym stands for susceptible, exposed, infectious, and recovered, and is a statistical approach to predicting the number of people at each step of an infectious disease outbreak.<\/p>\n

In the Chinese model, which includes a fatality component, Nichols saw a notable difference between the model\u2019s predicted COVID-19 cases and fatalities and actual cases and fatalities. \u201c\u201cI looked at one of the published datasets and it didn\u2019t look sound from a statistical standpoint,\u201d said Nichols.<\/p>\n

He consulted with a colleague, Nino Kordzakhia, a statistics expert and faculty member at Macquarie University in Sydney, Australia, about the SEIR formula. She thought Nichols\u2019 idea to tweak the formula so that it its predictions would more accurately conform to actual daily fatality numbers was worth exploring.<\/p>\n

To develop the tweaks and improve the model, Nichols applied two standard statistical methods. He did his work in Fortran, a general-purpose programming language mainly intended for mathematical computations, to make his approach broadly accessible.<\/p>\n

\u201cUsing Fortran doesn\u2019t require a knowledge of difficult statistical software or a statistical background,\u201d said Nichols. \u201cYou just need a computer and you can run it anywhere in the world.\u201d<\/p>\n

Nichols published his initial tweaks to the SEIR model in Fortran forums online, and with forum users\u2019 feedback, has been gradually refining the tweaks and closing the gap between SEIR predicted coronavirus cases and actual numbers, as well as the model\u2019s predicted fatalities and the actual numbers.<\/p>\n

The program is now in the public domain, and Nichols has submitted a paper detailing the project to the Journal of Statistical Software, which is published by the Foundation for Open Access Statistics. The journal is dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research.<\/p>\n

For many years, Nichols has created and refined statistical models for earthquake fatalities and bridge strength and durability, and used his experience to work with COVID-19 figures.<\/p>\n

\u201cData is data,\u201d said Nichols. \u201cWhen you\u2019re tweaking a model, data doesn\u2019t care whether it\u2019s coming from a bridge or the coronavirus,\u201d he said.<\/p>\n

Something as abstract as statistics can be a great aid in battling the coronavirus, said Nichols.<\/p>\n

\u201cThe virus is the meanest beast we\u2019ve ever fought, without a doubt,\u201d he said. \u201cIt\u2019s sitting there in a reservoir in the community waiting for us to make a mistake. It doesn\u2019t care about time. It\u2019s just sitting there waiting for you to make a mistake until you beat it, and the only way you can beat it is by quarantine or by developing a vaccine.\u201d<\/p>\n

Nichols\u2019 research and various tweaks of the SEIR model is supported by the College of Architecture.<\/p>\n

For more information, contact rnira@arch.tamu.edu<\/a> or doswald@tamu.edu<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

John Nichols’ tweaks to a model used to predict coronavirus fatality rates led to a narrower gap between predicted and actual coronavirus cases.<\/p>\n","protected":false},"author":32,"featured_media":6481,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[61,87,63],"tags":[],"acf":[],"yoast_head":"\nConstruction science prof refines COVID-19 statistical model - Texas A&M<\/title>\n<meta name=\"description\" content=\"John Nichols' tweaks to a model that predicted coronavirus fatality rates led to a narrower gap between predicted and actual cases.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.arch.tamu.edu\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Construction science prof refines COVID-19 statistical model\" \/>\n<meta property=\"og:description\" content=\"John Nichols' tweaks to a model that predicted coronavirus fatality rates led to a narrower gap between predicted and actual cases.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.arch.tamu.edu\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/\" \/>\n<meta property=\"og:site_name\" content=\"Texas A&M University College of Architecture\" \/>\n<meta property=\"article:published_time\" content=\"2020-06-13T02:47:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-06-27T19:38:54+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.arch.tamu.edu\/app\/uploads\/2020\/06\/Nichols-COVID.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"449\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Richard Nira\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Richard Nira\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.arch.tamu.edu\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/\",\"url\":\"https:\/\/www.arch.tamu.edu\/news\/2020\/06\/12\/cosc-prof-refines-covid-19-statistical-model\/\",\"name\":\"Construction science prof refines COVID-19 statistical model - 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