Analyzing and Modeling Coronavirus Data

Analyzing and Modeling Coronavirus Data

In this course you will learn about both epidemiological models and statistical models used to forecast Covid-19 pandemic data.

$589 | Enroll Now
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Overview

The Covid-19 pandemic caused by the Coronavirus has produced a wealth of data to a degree not seen in any previous pandemic, and doubtless will fuel an equivalent volume of research.  Statistical researchers outside the field of epidemiology have become involved, and will need to learn more about epidemiological models.

Learning Outcomes

In this course, you will learn the basic epidemiologic models and statistical models that are used to forecast the Covid-19 pandemic

  • Explain the workings of a basic SIR model
  • Specify Markov Chain Monte Carlo simulation for SIR
  • Factor in the SIR model parameters
  • Explain the IHME curve-fitting statistical model
  • Explain the difference between the SIR model and the IHME model
  • Quickly read and digest analyses of the Coronavirus pandemic

Who Should Take This Course

This course is for statistically literate health science professionals, and statistical research professionals who need to understand how the Covid-19 pandemic is being modeled.  

Instructors

dr-james-hardin

Dr. James Hardin

Dr. James Hardin is an Associate Dean of Faculty Affairs and Curriculum Professor at the University of South Carolina. Co-author (with Joseph Hilbe) of Generalized Estimating Equations, Dr. Hardin is on the editorial board of The Stata Journal and is the developer of the Stata GEE command, and with Dr. Hilbe is the developer of the GLM command.
See Instructor Bio
Wayne-Folta

Mr. Wayne Folta

Wayne Folta is a Lead Data Scientist at Elder Research, Inc. where he develops and deploys models for clients. His current work involves the design and implementation of text mining and deep learning models at the U.S. Dept. of Health and Human Services; he has also been active within Elder Research in exploring and assessing epidemiological models in R. Previous work has included fraud analytics and customer complaint modeling. Before joining Elder, Wayne worked as a software developer in the US government and in communications.
See Instructor Bio

Course Syllabus

Week 1

Exploring the data

  • States
    • Susceptible
    • Infected
      • Symptomatic
      • Asymptomatic
      • Contagious
    • Removed
      • Recovery
      • Death
  • Clustering
  • Age and health 
  • Sources and reliability
  • Heterogeneity among geographic units

Week 2

Epidemiological Models

  • Movement between 3 health states
    • Susceptible
    • Infected
    • Removed (recovered or dead)
  • Markov Chain simulation
  • Model parameters
    • R - reproduction rate
    • more…

Week 3

Statistical Models

  • IHME model
  • Curve fitting
    • Data used as base
    • First Wuhan, then Italy, Spain, ...
  • Mixed models
  • SIR and statistical models compared

Week 4

Implications

  • Future resurgence
  • Data-based decision-making
    • Public policy
    • Companies and Organizations
    • Individuals

 

 

Class Dates

2020

Jun 12, 2020 to Jul 10, 2020

2021

No classes scheduled at this time.

2022

No classes scheduled at this time.

Send me reminder for next class

Prerequisites

This is a discussion-based seminar style course.  It is intended for statistically-literate researchers, but you will gain something from the course even if you are not an expert in statistical models.

What Our Students Say​

I just completed another of your courses and yours is without question the best online educational resource available.

LaVera Crawley
empirical bioethicist and Asst. Professor at the Stanford University School of Medicine

Frequently Asked Questions

Do you provide custom training services?

We provide custom training services that can include, but is not limited to: 

  • Custom curriculum 
  • Custom courses and materials
  • Live training on-site
  • Live training via webinar
  • Special tuition pricing for multiple-student volume

Contact us to see how we can help you meet your training needs.

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

How do I enroll in a course?

In most courses, you are able to register for any course until the course start date.

Once you decide which course you want to take, click the ‘Enroll Now’ button and follow the purchasing process. Once you have purchased the course, you are enrolled in the class date you have selected.

You will receive a personal email message confirming your registration in the course. A second email is sent to you three days before the course start date with instructions to access the course in our Learning Management System (LMS).

Please see our knowledge center for more information.

Are courses eligible for CEU?

Many of the courses at The Institute for Statistics Education have been recommended for C.E.U.’s, based on the length of the course (typically 5.0 CEUs for 4-week courses).

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

Epidemiologic Statistics

This course will teach you the underlying concepts and methods of epidemiologic statistics: study designs, and measures of disease frequency and treatment effect.
Topic: Statistics, Biostatistics | Skill: Introductory | Credit Options: CEU
Class Start Dates: Nov 6, 2020, Nov 5, 2021

Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

About 10 hours per week, at times of your choosing.

Homework

Homework in this course consists of discussion questions, plus mostly optional assignments to test knowledge of modeling.  Records of completion will be issued, based primarily on participation in discussion.

Course Text

All materials and links to materials will be provided.

Software

Modeling illustrations will be provided in R

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

Supplemental Information

Register for This Course​

Analyzing and Modeling Coronavirus Data
$589 | Enroll Now
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