TODOs from 04/07 meeting

[michaelchughes]

• @michaelchughes Recruit new teammembers to help with viz dashboard deployment and other features

• @deastman

• [x] Update aesthetics (pretty-print strings, update dimensions of plots, layout)

• [x] Add checkboxes to Dash app to show/hide plots based on name

• [x] Add series for actual data to compare with predictions/forecast

• [x] Add column for actual date information rather than generic time step

• [x] Allow for ability to update visualization based upon parameter change (proof of concept: recovery probability)

• [x] Figure out how to deploy Plotly Dash app

• @panlybero Try out a pipeline that uses CHIME to provide input numbers, in a probabilistic way (specify distributions over CHIME inputs, run using samples from these distributions)

• @gvisani Read up on the IHME model and come up with prelim strategies for a "curve fitting" approach Paper: https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v1.full.pdf Current MA forecasts: https://covid19.healthdata.org/united-states-of-america/massachusetts

[michaelchughes]

All, if you think of new things to ask the TMC team about, please let me know!

[michaelchughes]

Update from TMC team: They will give us "incoming" patient counts for two types of patient, "new" and "referral" (see #12 ) These will be based on scenarios they are interested in using both CHIME and IHME, which they have the capability of generating inhouse

So I think we can still put some energy into the "run CHIME" and "run IHME" scenarios.

But for next few days, focus will be on:

• adapting to admit types (see #12)
• updating visualization

[michaelchughes]

Updated resources from meeting with TMC folks:

• Concrete numbers about tests and hospitalizations for each day https://tufts.box.com/s/fevrlky6mxqs6farxpudvbbtpzbjvygx @panlybero @gvisani could use these to help do side-by-side with CHIME predictions

• Slides summarizing daily counts of testings for various hospitals in region to-date https://tufts.box.com/s/8a3xnuynw0dh60wkxu6x5cbe59z2f4ak

• LitReview from Jinny Park (an RA at TMC) helps us get age-specific risk distributions https://tufts.box.com/s/8c6yumhft680sw9lcjzdoxe6wkzl1dtr

@rathp these lit review numbers could be a jumping off point for the age-specific progression probas

[michaelchughes]

Mostly Resolved (still working on sidebyside plots of forecasts and data....)