Rob Emanuele

This PR sets up the CHIME python package for reuse: https://github.com/CodeForPhilly/chime/pull/249 I think getting county level parameters into here https://github.com/CodeForPhilly/chime/blob/develop/src/penn_chime/parameters.py and running the model here https://github.com/CodeForPhilly/chime/blob/develop/src/penn_chime/models.py will get us what...

If you want to combine the those two papers to create an estimate of what's needed, I think one way to do that is: - https://github.com/covidcaremap/covid19-healthsystemcapacity/blob/master/notebooks/processing/Generate_CCM_CareModel_Facility_Data.ipynb is a start to...

@williamratcliff > What is the status of data sources for the project? I'm unsure what you are asking, can you clarify? Do you mean this project or the projects listed...

Looked over #68 - seems like a great start. So if we take the county level confirmed cases mentioned above, could this be turned onto PPE estimates per county? That...

Being done as part of #37

The notebook currently aggregates to these statistics: ``` Total Beds 742,562.0 ICU Total Beds 74,688.0 ``` This page: https://www.aha.org/statistics/fast-facts-us-hospitals Gives these figures: ``` Total Staffed Beds in All U.S. Hospitals:...

From https://github.com/daveluo/covid19-healthsystemcapacity/blob/71a455849190b5487230a1d59258e43482d5429b/nbs/usa_beds_capacity_analysis_20200313_v2.ipynb: ## Check bed stats against: https://www.kff.org/other/state-indicator/beds-by-ownership/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D - 2.4 staffed beds per 1,000 pop across USA https://www.sccm.org/Communications/Critical-Care-Statistics AHA data: According to the AHA 2015 annual survey, the United States...

https://github.com/datasets/covid-19

Already used in this project: US County dataset: https://eric.clst.org/assets/wiki/uploads/Stuff/gz_2010_us_050_00_20m.json Census data by county: https://www2.census.gov/programs-surveys/popest/datasets/2010-2018/counties/asrh/cc-est2018-alldata.csv

Data that contribute to generating these numbers (taken from the Flu Surge 2.0 Model) are high priority: