compute average OR and sd for each RUCC bin

scripts/OR_urbanmetro_v6-14-13.py
- compute average OR for all zip3s across all
seasons for each RUCC bin (urban metro, small
metro, rural)
- found that average values were not as
disparate as originally thought
minor changes

changes unknown
changed directory names

zip3_RUCC_v6-9-13.R
zip_code_database.R
export ILI data for offices only, znorm OR

Znorm_OR.py
- first commit: z-normalize all ILI data and plot

OR_allweeks.sql
- add export of child, adult, and other age group incidence
of just offices/OP service place visits

OR_allweeks.py
- minor changes
z-norm labels, change set weeks for normalization

Znorm_OR.py
- number of weeks over which OR will be normalized is a parameter
set at beginning of script
- considered normalizing over first 10, 12, 25, and 33 weeks of
flu season
- do not plot season 1
change scatters in prep for GID seminar

- calculate Pearson correlation coefficients
- increase label size
- change label and legend text
first commit ORincid charts

ORincid_allweeks.py
- plots OR and child/adult incidence on same plot for
each season in SDI data
- script first written in 9/2013
first commit Znorm OR summer normalization SDI

Znorm_OR_summer.py
- Z-normalize OR by summer months data (wks 21
to 39) for all ILI and office/OP ILI only in
SDI dataset
- plot Z-normalized OR for each and compare to
OR that was Z-normalized using first 12 weeks of
data in season
redraw ZnormOR with 10 normwks and label updates

Znorm_OR.py
- normalize season by 10 initial flu season wks
- plot labels show number of norm wks in normalization
WIPS talk figures update

attackrates_wk.py
- increase axis label size
- change legend to include full years
update figure label to reflect US datasource

attackrates_wk.py
- added "U.S." to y-axis
plot formatting

OR_allweeks.py
ORincid_allweeks.py
Znorm_OR.py
- plotting changes in preparation for WIPS 2014
presentation and talk with Cecile
first commit weekly OR by HHS region (spatial)

OR_zip3_week.sql
- export child and adult incidence data for OR
calculation by zip3 by week (OR_zip3_week.csv)
- export popstat data for OR calculation by zip3
by week (popstat_zip3_season.csv)
- files exported to SQL_export folder

clean_OR_hhsreg_week.R
- clean OR_zip3_week.csv and popstat_zip3_season.csv
to remove zip3s that do not have data for all 10
seaons or zip3s where not all child and adult age
increments have popstat data
- aggregated zip3-level ILI data and popstat data
 by HHS region
- files exported to R_export folder as OR_zip3_week_cl.csv
and popstat_zip3_season_cl.csv

OR_allweeks_hhsreg.py
- imported OR_zip3_week_cl.csv and popstat_zip3_season_cl.csv
- plot OR and z-normalized OR (10 week normalization)
by week for each season and each HHS region
updated docstring OR_allweeks_hhsreg.py

OR_allweeks_hhsreg.py
- improved description in docstrings for incid_reg_wk
and reg_season functions
alter plot formats for Cecile slides (2/11/14)

OR_allweeks_hhsreg.py
Znorm_OR.py
- changed axes and plot formatting for slides
- then, changed formats back to original code
charts for 2/16 version of severity ms

OR_fluweeks.py - Fig 2
OR_allweeks_hhsreg.py - Fig 5
Znorm_OR.py - Fig 3
attackrates_wk.sql - Fig 3
createF1.sql - Fig 1

Other figure scripts for manuscript are in
Manuscripts/Age_Severity/create_fluseverity_figs
process and plot avg sev retro rank vs region num

OR_allweeks_hhsreg.py

Rank each region for every season and report avg
rank for each region across all seasons, and
mild (S3, S6, S7, S9), moderate (S2, S5), and
severe (S4, S8, S10) seasons.
boxplot instead of barplot for zOR by region

OR_allweeks_hhsreg.py
- added plots for average z-OR vs. region in addition
to average z-OR rank vs. region
- boxplot for average z-OR vs region across all seasons
- boxplot for average z-OR vs region across
different season types is not complete because x-axis
values need to be manually implemented
since there will be multiple boxplots per region
relative zOR classif periods, moving window zOR

Znorm_OR.py
- add code to write zOR averages to file

Znorm_OR_window.py
- calculate moving window zOR across all weeks to
determine if there are trends during flu and non-flu seasons
- difficulty in understanding the dynamics and not sure
if this will help with pandemic outbreak detection

Znorm_OR_relative.py
- calculate average zORs during classification periods
where early warning period depends on week of Thanksgiving
and retrospective period depends on growth period of seasonal
epidemic
- early warning period is two weeks beginning on the week
after Thanksgiving, based on My's data file 'Thanksgiving
WeekData_Revised.csv'
- retrospective period may be calculated as the two week
period that begins after the cumulative flu season incidence
surpasses a certain proportion of the flu season cases or
as the two week period that begins two weeks prior to the
epidemic peak week

ORgenerator.py
- added functions for Znorm_OR_relative script
- import_relative_early_period returns a dictionary of
the date of the Sunday before Thanksgiving for each
season key; this helps define the early warning period
- import_relative_retro_period returns a list of the
weeks in the retrospective period with options to
identify those weeks based on proportion of cumulative
incidence or number of weeks prior to peak epidemic
week
minor changes

Znorm_OR_summer.py
- not sure