We used this page for UW collaboration and assistance to the state involving COVID-19 models and data. This page is publicly accessible. To gain access to editing and discussion functions, please log in (request an account from Alex Buerkle via email to buerkle@uwyo.edu).

Collaboration with State of Wyoming

Our collaboration with the State of Wyoming is on a private page for data science working group members.

Visualizations of national and Wyoming data

In communicating about the consequences of the pandemic, visualizations play a key role. Let’s collect some of these visualizations we find in research papers and on the web (with links and attributions to the originals), and ones we create ourselves.

Higher education SARS-CoV-2 policy documents and publications

• Financial implications and planning (Johns Hopkins University)

• Purdue University president’s outlook (21 April 2020)

• University of Texas president’s outlook (22 April 2020)

• College Campuses Must Reopen in the Fall. Here’s How We Do It – Opinion article in NYTimes by Brown University president, Christina Paxson

  • This is an argument based almost entirely on revenue to the institution, from the perspective of institutions that are highly tuition dependent. The University of Wyoming is an outlier with respect to how little we rely on tuition, so the economics in Wyoming will be different than this perspective. It does not give consideration to trade-offs or a clear accounting of costs and benefits. In particular, it lacks a clear articulation of what (other than revenue) is lost by delaying reopening.

  • It makes clear that extraordinary resources will need to be used (money spent) to open. Testing and effectively isolating students in quarantine will require resources.

• Twitter thread with links to many news stories and official documents regarding the breadth of plans for the fall, and the widely varying timelines that colleges and university will follow.

Some resources and things to consider

Publications (news, scientific journals/preprints, and blogs)

• Projecting the transmission dynamics of SARS-CoV-2 through the post-pandemic period

• Impact of non-pharmaceutical interventions (NPIs) to reduce COVID- 19 mortality and healthcare demand

• Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

• Set of COVID-19 Epidemiology links at the Center for Infectious Disease Research and Policy

• Quantifying dynamics of SARS-CoV-2 transmission suggests that epidemic control and avoidance is feasible through instantaneous digital contact tracing

• A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data (read the comments)

• Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)

• Serial Interval of Novel Coronavirus (COVID-19) Infections

• Coronavirus cases have dropped sharply in South Korea. What’s the secret to its success?

• Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

• Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China

• Coronavirus: The Hammer and the Dance

• Academic Data Science Alliance is working with partners to pull together data and data science resources related to the COVID-19 pandemic

• RAPID ASSISTANCE IN MODELLING THE PANDEMIC: RAMP. A call for assistance, addressed to the scientific modelling community. Coordinated by the Royal Society

• Effective visualizations of SIR simulations by 3Brown1Blue.

• Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2) (Science 16 Mar 2020: eabb3221 DOI: 10.1126/science.abb3221)

• Observational Health Data Sciences and Informatics (OHDSI) international community hosted a COVID-19 virtual study-a-thon March 26-29

• Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection (preprint)

• The second derivative of the time trend on the log scale – Commentary on the IMHE pre-print and projections

• Estimating the number of infections and the impact of non- pharmaceutical interventions on COVID-19 in 11 European countries (30 March 20 pre-print from Imperial College COVID-19 Response Team). Repo with code for analysis.

• Don’t Believe the COVID-19 Models – That’s not what they’re for. Zeynep Tufekci in The Atlantic (2 April 2020).

• National coronavirus response: A road map to reopening (American Enterprise Institute)

• Can we emulate Iceland and try to test nearly everyone? Iceland’s ‘Test Everyone’ Goal Has Skeptics, but It May Be Working

• The Small World Network of College Classes: Implications for Epidemic Spread on a University Campus (11 April 2020, preprint)

• Our Pandemic Summer – The fight against the coronavirus won’t be over when the U.S. reopens. Here’s how the nation must prepare itself. The Atlantic, 14 April 2020.

• What 5 Coronavirus Models Say the Next Month Will Look Like (22 April 2020, New York Times)

• What Happens Next? COVID-19 Futures, explained with playable simulations (1 May 2020). This is a useful primer on SIR models and different measures contribute to driving R to below 1. It includes this useful figure and simulations that make clear that we need a robust test, trace, and isolate strategy.

• The effect of human mobility and control measures on the COVID-19 epidemic in China (Science, 1 May 2020)

• Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions (Science 10 July 2020)

Data

• CSSEGISandData time series data from Johns Hopkins GitHub (update daily). Overall 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE repository.