Absolute figures

Relative increments

Increments compared to Tests

Number of tests used is the linearly decreasing weighted average over previous 7 days

Latest estimates of the number of confirmed cases by date of infection, the expected change in daily confirmed cases, the effective reproduction number, tthe doubling time (when negative this corresponds to the halving time), and the adjusted R-squared of the exponential fit. The mean an 90% credible interval is shown for any numeric estimate

The estimates of the coefficient of reproduction shown here have been done by a team based at London School of Hygiene and Tropical Medicine who is specialised on real-time modelling and forecasting of infectious disease outbreaks.

All rights are reserved to them, who have shared codes, data and result with MIT license at this Github repository. Additional methodological info and the estimates for other countries are available at this webpage

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today's case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection

Confirmed cases and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected changein daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Confirmed cases by date of report (bars) and their estimated date of infection

Time-varying estimate of the effective reproduction number. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Theseshould be considered indicative only