- A
great intro to many of the most important question: "When a new
virus emerges, no one is immune. A highly transmissible virus, like the
coronavirus behind the current pandemic, can spread like wildfire,
quickly burning through the dry kindling of a totally naive
population. But once enough people are immune, the virus runs into
walls of immunity, and the pandemic peters out instead of raging
ahead. Scientists call that the herd immunity threshold."
- How
epidemics like covid-19 end (and how to end them faster): A
coronavirus causing a disease called covid-19 has infected more than
70,000 people since it was first reported in late 2019. To predict how
big the epidemic could get, researchers are working to determine how
contagious the virus is.
- The SIR Model for Spread of Disease - Introduction (from the MAA).
In particular, we will implement The SIR Model for Spread of Disease - The Differential Equation Model in InsightMaker.
- Mathematics
of the Corona outbreak, with Professor Tim Britton
(An excellent introduction to SIR models, from both the
infectious disease and mathematical sides)
Questions:
- Where is the "calculus moment" in this video?
- How does Britton suggest breaking $R_0$ down into
"actionable" pieces?
- An on-line
model developed by Ashleigh Tuite and David Fisman, Dalla Lana
School of Public Health, University of Toronto
- This one incorporates space into the model. These models are called "agent-based models".
- Could
Coronavirus Cause as Many Deaths as Cancer in the U.S.? Putting
Estimates in Context
This on-line estimator (i.e., a model!) allows one to estimate
deaths, as well as death by age-category.
- A nice R-based introduction to infectious diseases and nonlinear differential equations.
- Use of a log-scale (which they take pains to explain) to illustrate deaths by country, updated daily. There is even a separate page at the New York Times to explain log plots: "A Different Way to Chart the Spread of Coronavirus: Those skyrocketing curves tell an alarming story. But logarithmic graphs can help reveal when the pandemic begins to slow."