Amidst the continuing spread of the COVID-19 pandemic, timely, data-driven
metrics remain critical to track the pandemic's impact and inform policy making.
It is critical to use multiple metrics concurrently as they provide
complementary insight into relative impact, as in the effective reproduction
number (Rt), and absolute impact, as in the number of new cases and deaths in a
given population. This tool provides a visualization for these three metrics
which are calculated based on [Poisson log-linear
models](https://www.medrxiv.org/content/10.1101/2021.03.12.21253496v1). Please
see the About tab for more information about the usage of the site and please
see [our paper](https://www.medrxiv.org/content/10.1101/2021.03.12.21253496v1)
for more details about the method.

+ The **effective reproduction number (Rt)** characterizes the COVID-19 spread
  rate, defined as the average number of secondary infectious cases produced by
  a primary infectious case. It's used to define the potential for spread at a
  specific time. If Rt > 1, the virus will spread out and the disease will
  become an epidemic; if Rt = 1, the virus will spread locally and the disease
  is endemic; if Rt < 1, the virus will stop spreading and the disease will
  disappear eventually.

+ The **daily new cases per million** and **daily new deaths per million**
  quantify the daily new COVID-19 cases and deaths, scaled by the population of
  a given area.

Change the date, metric, and resolution below. Click on an area in the map to
see its metrics over time.
