+Currently, this estimation can be done in the web application via four
+different methods: White and Panago (WP), sequential Bayes (seqB),
+incidence decay (ID), and incidence decay and exponential adjustment
+(IDEA).
+
+Datasets can be uploaded as a .csv file, or can be entered manually into
+the application. The data is visualized in the application through plots
+that show the case counts (either weekly or daily). If multiple datasets
+are uploaded/manually entered, the trends corresponding to these
+datasets are populated in the same plot and can be compared. This plot
+can be exported as a .png file. Further, the dataset entered can be
+exported into a .csv file. Two sample datasets are included: weekly
+Canadian COVID-19 case count data from March 3rd, 2020 to March 31st,
+2020, and weekly Ontario COVID-19 case count data from March 3rd, 2020
+to March 31st, 2020.
+
+To estimate the basic reproductive number, the user can choose their
+preferred estimator, and if applicable, must enter the known serial
+interval prior to estimation. If multiple estimates of the basic
+reproductive number are calculated, they are all included in a table
+where each row represents an estimate. If multiple datasets are being
+considered, the basic reproductive number is estimated for all datasets
+and the columns of the table correspond to the different datasets
+uploaded into the application. The table also consists of a column
+corresponding to the value of the [serial interval
+(SI)](https://en.wikipedia.org/wiki/Serial_interval). This table can be
+exported as a .csv file.
+
+In progress…
git.nmode.ca / Rnaught / blobdiff
