Summary
I work for a data science team at a health system, we have limited knowledge/prior experience running docker containers etc so we downloaded (via urllib.request) the files in the src/pnn_chime folder to run locally and output csvs for patient census in each one of our regions our health system covers. code is in attached notebook. fyi, was having problems getting the relative imports to run so I regexed them out so the file could be run by exec().
The output from doing this direct file download and running is different than the output from the CHIME web app even though the same files should be running in both examples
Additional details
ex row of region data:
Pop | current_hosp | date first hosp | doubling_time | initial_infections | hosp_rate | icu_rate | vent_rate | hosp_los | icu_los | vent_los | market_share
-- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | --
604227 | 14 | 3-18-2020 | 7 | 61 | 0.025 | 0.01 | 0.0075 | 7 | 9 | 10 | 0.233
output for that region
2020-04-05_projected_census.xlsx
python notebook file as text file:
automated_notebook_to_text.txt
Suggested fix
unknown
Summary
I work for a data science team at a health system, we have limited knowledge/prior experience running docker containers etc so we downloaded (via urllib.request) the files in the src/pnn_chime folder to run locally and output csvs for patient census in each one of our regions our health system covers. code is in attached notebook. fyi, was having problems getting the relative imports to run so I regexed them out so the file could be run by exec().
The output from doing this direct file download and running is different than the output from the CHIME web app even though the same files should be running in both examples
Additional details
ex row of region data:
Pop | current_hosp | date first hosp | doubling_time | initial_infections | hosp_rate | icu_rate | vent_rate | hosp_los | icu_los | vent_los | market_share
-- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | -- | --
604227 | 14 | 3-18-2020 | 7 | 61 | 0.025 | 0.01 | 0.0075 | 7 | 9 | 10 | 0.233
output for that region
2020-04-05_projected_census.xlsx
python notebook file as text file:
automated_notebook_to_text.txt
Suggested fix
unknown