Teaching Quantitative Biology Online

This collection of resources on the PDB 101 site focuses on COVID 19 from a molecular viewpoint.  There are 11 modules, ranging from hand washing to a deep dive into key molecular structures of the virus. (Image by David Goodsell)

How to Spot COVID-19 Conspiracy Theories, authored by Stephan Lewandowsky, John Cook, Ullrich Ecker, and Sander van der Linden, looks at possible examples of COVID-19 conspiracy theories, and identifies how they illustrate the seven traits of conspiratorial thinking,

An Infographic datapack of visualizations on COVID 19

Also check out Myths and Misconceptions: https://informationisbeautiful.net/visualizations/coronavirus-myths-mythconceptions/

"The Academic Data Science Alliance is working with partners to pull together data and data science resources related to the COVID-19 pandemic. This is a living list of resources and we welcome additions, suggestions, and collaborations. Please send additions, corrections, comments, and suggestions to us using this feedback form.

Please keep suggestions limited to research and data resources, avoiding opinion pieces and teaching resources. 

Note that the resources listed here are provided as-is. Use your professional judgement and best practices to vet these resources before you use them for research and scientific communications."

A PBS Newshour: Student Reporting Labs Interview 

"West Ranch High School student reporter Madi Marks interviews University of Pittsburgh professor and epidemiologist Dr. Wilbert Van Panhuis on how he's collecting data on the coronavirus and how to combat it for our #SRLAsks series."

Quick intro to epidemiology and modeling and a peek into career pathways in this area.

NCCSTS requires a $25 annual subscription for individuals.  Materials are peer reviewed, and include student handouts and teacher materials.  We are sharing information about recent cases published on COVID19 from this organization:

"COVID-19: Where Did You Come From, Where Did You Go?” by authors from North Carolina State University: Stefanie H. Chen, Carlos C. Goller, and Melissa C. Srougi

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1125&id=1125

"Put to the Test: RT-PCR and Antibody Detection Diagnostic Tools for COVID-19 ” by a team of authors from Brandeis University:  Melissa S. Kosinski-Collins, Lindsay Mehrmanesh, Jessie Cuomo and Kene N. Piasta.

Fatally Flawed? Early Genetic Testing for the COVID-19 Virus” by Amy C. Groth, Department of Biology, Eastern Connecticut State University

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1123&id=1123

“Social Distancing in the Midst of COVID-19” is by Jason C. Cochrane, Science Department, Mountain Vista High School, Highlands Ranch, CO. 

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1113&id=1113

 “Pandemic Pandemonium: Why Can’t We Just Treat COVID-19?” by a team of authors from Brandeis University:  Melissa S. Kosinski-Collins, Lindsay Mehrmanesh, Jessie Cuomo and Kene N. Piasta.

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1114&id=1114 

"Coronavirus Quandaries for Patients with Cardiovascular Disease” by Janine Bartholomew, Department of Biology, Carlow University, Pittsburgh, PA

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1121&id=1121

“Where’s the Evidence? Confronting Public Panic About COVID-19” by Laura Pickell, Department of Biology, Cégep Heritage College, Gatineau, QC, Canada

https://sciencecases.lib.buffalo.edu/collection/detail.html?case_id=1120&id=1120

Fred Hutchinson Cancer Research Center's list of science papers you should be reading about the coronavirus: Amid the thousands of research publications on COVID-19, here are the ones they are reading

This is a python package for exploring SEIR models on social networks. The first link is to a Twitter thread where the use and some significant results are explained.

Dr. Harry Kestler at LCCC keeps us informed about the coronavirus and how we can all work together to slow the spread of COVID-19 in this series of daily videos about various aspects of the pandemic: https://www.lorainccc.edu/security/dr-kestlers-coronavirus-video-series/

Prior to his position at LCCC, Kestler held faculty positions at the Lerner Medical College of the Cleveland Clinic and the department of Microbiology and Molecular Genetics at Harvard Medical School.

By Dr  Kamuela Yong

Helps readers interpret various models and statistics around COVID-19. Written at the introductory level, could be used for high school or introductory undergraduate.

Several graphics around COVID19 and the pandemic, with readings at the bottom of the page and access to underlying data.

There is an R Shiny contest going on right now.  Many of the most recent submissions are data dashboards for tracking the COVID-19 pandemic.  Take a look!

This phylogeny shows evolutionary relationships of hCoV-19 (or SARS-CoV-2) viruses from the ongoing novel coronavirus COVID-19 pandemic. This phylogeny shows an initial emergence in Wuhan, China, in Nov-Dec 2019 followed by sustained human-to-human transmission leading to sampled infections. Although the genetic relationships among sampled viruses are quite clear, there is considerable uncertainty surrounding estimates of transmission dates and in reconstruction of geographic spread. Please be aware that specific inferred transmission patterns are only a hypothesis.

This ESTEEM worksheet implements an SIR (Susceptible/ Infected/ Resistant) model of epidemiology for vector-borne diseases. Up to three microbial strains with different virulence and transmission parameters can be modeled and the results graphed. Originally designed to explore coevolution of myxoma and rabbits, the model is easily generalized to other systems.

The SIR Build It REVISED 2018 file attached here represents a basic SIR model and demonstrates Farr's law as well as the corresponding S/I phase plot. Additional sheets demonstrate some modifications of the basic model, including the effects of stochasticity.

From Tony Weisstein, Truman State

More Excel based simulations from the BioQUEST ESTEEM collection are available here:https://qubeshub.org/community/groups/esteem/esteem_modules_and_descriptions

For use in a calculus class!

Estimating actual COVID 19 cases (novel corona virus infections) in an area based on deaths. Based on work by Tomas Pueyo at: https://medium.com/@tomaspueyo/coronavirus-act-today-or-people-will-die-f4d3d9cd99ca

From 3Blue1Brown animated math collection: https://www.3blue1brown.com/

Doesn't require any simulator tools/R code. Just have your students play and look for insights!

Click on the intervention tab to see the #flattenthecurve app.