def columns(self):
self.config['mother_ids'] = tuple(DeliveryMothersIds(config=self.config).data.keys()) + ('',)
columns = [
DatabaseColumn("Total children with with birthweight known",
CountUniqueColumn('doc_id', alias="total_birthweight_known",
filters=self.filters + [NOTEQ('weight_birth', 'empty')])),
DatabaseColumn("Total births",
CountUniqueColumn('doc_id',
filters=[AND([IN('mother_id', get_INFilter_bindparams('mother_ids', self.config['mother_ids'])),
OR([EQ('gender', 'female'), EQ('gender', 'male')])])],
alias='total_births'))]
columns.extend([
DatabaseColumn("Birthweight < 2.5 kg",
CountUniqueColumn('doc_id',
alias="total_birthweight_lt_25",
filters=self.filters + [AND([LT('weight_birth', 'weight_birth_25'), NOTEQ('weight_birth', 'empty')])]
)
),
DatabaseColumn("Birthweight >= 2.5 kg",
CountUniqueColumn('doc_id',
alias="total_birthweight_gte_25",
filters=self.filters + [AND([GTE('weight_birth', 'weight_birth_25'), NOTEQ('weight_birth', 'empty')])]
)
)
])
return columns
def columns(self):
columns = [
DatabaseColumn(
"Total children with with birthweight known",
CountUniqueColumn('doc_id',
alias="total_birthweight_known",
filters=self.filters +
[NOTEQ('weight_birth', 'empty')])),
]
columns.extend([
DatabaseColumn(
"Birthweight < 2.5 kg",
CountUniqueColumn(
'doc_id',
alias="total_birthweight_lt_25",
filters=self.filters + [
AND([
LT('weight_birth', 'weight_birth_25'),
NOTEQ('weight_birth', 'empty')
])
])),
DatabaseColumn(
"Birthweight >= 2.5 kg",
CountUniqueColumn(
'doc_id',
alias="total_birthweight_gte_25",
filters=self.filters + [
AND([
GTE('weight_birth', 'weight_birth_25'),
NOTEQ('weight_birth', 'empty')
])
]))
])
return columns
def columns(self):
return [
DatabaseColumn("Early initiation of breastfeeding",
CountUniqueColumn('doc_id', alias="colostrum_feeding",
filters=self.filters + [EQ('breastfeed_1_hour', 'yes')])),
DatabaseColumn("Early initiation of breastfeeding Total Eligible",
CountUniqueColumn('doc_id', alias="colostrum_feeding_total_eligible",
filters=self.filters + [NOTEQ('breastfeed_1_hour', 'empty')])),
DatabaseColumn("Exclusive breastfeeding",
CountUniqueColumn('doc_id', alias="exclusive_breastfeeding",
filters=self.filters + [AND([EQ('exclusive_breastfeeding', "yes"),
GTE('dob', "today_minus_183")])])),
DatabaseColumn("Exclusive Breastfeeding (EBF) Total Eligible",
CountUniqueColumn('doc_id', alias="exclusive_breastfeeding_total_eligible",
filters=self.filters + [GTE('dob', 'today_minus_183')])),
DatabaseColumn("Supplementary feeding",
CountUniqueColumn('doc_id', alias="supplementary_feeding",
filters=self.filters + [AND([EQ('supplementary_feeding_baby', 'yes'),
GTE('dob', 'today_minus_182')])])),
DatabaseColumn("Supplementary feeding Total Eligible",
CountUniqueColumn('doc_id', alias="supplementary_feeding_total_eligible",
filters=self.filters + [GTE('dob', 'today_minus_182')])),
DatabaseColumn("Complementary feeding",
CountUniqueColumn('doc_id', alias="complementary_feeding",
filters=self.filters + [AND([EQ('comp_breastfeeding', 'yes'),
LTE('dob', 'today_minus_183'),
GTE('dob', 'today_minus_730')])])),
DatabaseColumn("Complementary feeding Total Eligible",
CountUniqueColumn('doc_id', alias="complementary_feeding_total_eligible",
filters=self.filters + [AND([LTE('dob', 'today_minus_183'),
GTE('dob', 'today_minus_730')])]))
]
def columns(self):
self.config['mother_ids'] = tuple(
DeliveryMothersIds(config=self.config).data.keys()) + ('', )
return [
DatabaseColumn(
"Total births",
CountUniqueColumn(
'doc_id',
filters=[
AND([
IN(
'mother_id',
get_INFilter_bindparams(
'mother_ids', self.config['mother_ids'])),
OR([EQ('gender', 'female'),
EQ('gender', 'male')])
])
],
alias='total_births')),
DatabaseColumn(
"Newborn deaths (< 1 m)",
CountUniqueColumn(
'doc_id',
filters=self.filters + [
AND([
EQ('reason_for_child_closure', 'death'),
EQ('type_of_child_death', 'newborn_death')
])
],
alias='newborn_death')),
DatabaseColumn(
"Infant deaths (< 1 y)",
CountUniqueColumn(
'doc_id',
filters=self.filters + [
AND([
EQ('reason_for_child_closure', 'death'),
EQ('type_of_child_death', 'infant_death')
])
],
alias='infant_death')),
DatabaseColumn(
"Child deaths (2-5y)",
CountUniqueColumn(
'doc_id',
filters=self.filters + [
AND([
EQ('reason_for_child_closure', 'death'),
EQ('type_of_child_death', 'child_death')
])
],
alias='child_death')),
DatabaseColumn(
"Total deaths",
CountUniqueColumn('doc_id',
filters=self.filters +
[EQ('reason_for_child_closure', 'death')],
alias='total_deaths'))
]
def columns(self):
columns = [
DatabaseColumn("Total child registered ever", CountUniqueColumn('doc_id', alias="total"))
]
if 'startdate' not in self.config and 'enddate' not in self.config or 'startdate' not in self.config \
and 'enddate' in self.config:
columns.extend([
DatabaseColumn(
"Total open children cases", CountUniqueColumn(
'doc_id', alias="no_date_opened",
filters=self.filters + [EQ('closed_on', 'empty')]
)
),
DatabaseColumn(
"Total closed children cases", CountUniqueColumn(
'doc_id', alias="no_date_closed",
filters=self.filters + [NOTEQ('closed_on', 'empty')]
)
),
DatabaseColumn(
"New registrations during last 30 days", CountUniqueColumn(
'doc_id', alias="no_date_new_registrations",
filters=self.filters + [AND([GTE('opened_on', "last_month"), LTE('opened_on', "today")])]
)
)
])
else:
columns.extend([
DatabaseColumn(
"Children cases open at end period", CountUniqueColumn(
'doc_id', alias="opened",
filters=self.filters + [AND([LTE('opened_on', "stred"), OR([EQ('closed_on', 'empty'),
GT('closed_on', "stred")])])]
)
),
DatabaseColumn(
"Children cases closed during period", CountUniqueColumn(
'doc_id', alias="closed",
filters=self.filters + [AND([GTE('closed_on', "strsd"), LTE('closed_on', "stred")])]
)
),
DatabaseColumn(
"Total children followed during period", CountUniqueColumn(
'doc_id', alias="followed",
filters=self.filters + [AND([LTE('opened_on', "stred"), OR([EQ('closed_on', 'empty'),
GTE('closed_on', "strsd")])])]
)
),
DatabaseColumn(
"New registrations during period", CountUniqueColumn(
'doc_id', alias="new_registrations",
filters=self.filters + [AND([LTE('opened_on', "stred"), GTE('opened_on', "strsd")])]
)
)
])
return columns
def __init__(self, table_name, filters, group_by, key):
self.key = key
super(IntraHealthQueryMeta, self).__init__(table_name, filters,
group_by, [])
assert len(filters) > 0
self.filter = AND(
self.filters) if len(self.filters) > 1 else self.filters[0]
def filters(self):
filters = None
if 'enddate' not in self.config:
self.config['enddate'] = self.config['today']
self.config['stred'] = self.config['today']
if 'startdate' in self.config:
filters = [
AND([
LTE("date", "enddate"),
OR([
GTE('closed_on', "startdate"),
EQ('closed_on', 'empty')
])
])
]
else:
self.config['strsd'] = '0001-01-01'
filters = [LTE("date", "enddate")]
for k, v in six.iteritems(LOCATION_HIERARCHY):
if v['prop'] in self.config and self.config[v['prop']]:
filters.append(
IN(k, get_INFilter_bindparams(k, self.config[v['prop']])))
return filters
def columns(self):
return [
DatabaseColumn(
"Trimester 1",
CountUniqueColumn('doc_id',
alias="trimester_1",
filters=self.filters +
[GT('edd', "today_plus_196")])),
DatabaseColumn(
"Trimester 2",
CountUniqueColumn('doc_id',
alias="trimester_2",
filters=self.filters + [
AND([
LTE('edd', "today_plus_196"),
GT('edd', "today_plus_84")
])
])),
DatabaseColumn(
"Trimester 3",
CountUniqueColumn('doc_id',
alias="trimester_3",
filters=self.filters +
[LTE('edd', 'today_plus_84')]))
]
def filters(self):
filters = [
EQ("domain", "domain"),
EQ("ppt_year", "ppt_year"),
AND([
NOTEQ("case_status", "duplicate"),
NOTEQ("case_status", "test")
])
]
for k, v in self.geography_config.items():
if k in self.config and self.config[k]:
filters.append(
IN(k, get_INFilter_bindparams(k, self.config[k])))
if 'value_chain' in self.config and self.config['value_chain']:
filters.append(EQ("value_chain", "value_chain"))
if 'group_leadership' in self.config and self.config[
'group_leadership']:
filters.append(EQ('group_leadership', 'group_leadership'))
if 'cbt_name' in self.config and self.config['cbt_name']:
filters.append(
IN(
'owner_id',
get_INFilter_bindparams('cbt_name',
self.config['cbt_name'])))
if 'real_or_test' in self.config and self.config['real_or_test']:
filters.append(IEQ('real_or_test', 'real_or_test'))
for column_name in ['domains', 'practices', 'schedule']:
if column_name in self.config and self.config[
column_name] and self.config[column_name] != ('0', ):
filters.append(
IN(
column_name,
get_INFilter_bindparams(column_name,
self.config[column_name])))
return filters
def _get_age_range_filter(self):
filters = [
AND([
GTE(age_range.column, age_range.lower_param),
LT(age_range.column, age_range.upper_param)
]) for age_range in self._age_ranges
]
return filters[0] if len(filters) == 1 else OR(filters)
def filters(self):
#We have to filter data by real_date_repeat not date(first position in filters list).
#Filtering is done directly in columns method(CountUniqueColumn).
filters = super(ConventureData, self).filters
filters.append(AND([GTE('real_date_repeat', "strsd"), LTE('real_date_repeat', "stred")]))
if 'archived_locations' in self.config:
filters.append(_locations_filter(self.config['archived_locations']))
return filters[1:]
def filters(self):
filters = super(PPSAvecDonnees, self).filters
filters.append(
AND([
GTE('real_date_repeat', "strsd"),
LTE('real_date_repeat', "stred")
]))
return filters[1:]
def filters(self):
filters = super(NumberOfPNCVisits, self).filters[1:]
filters.append(
AND([
NOTEQ('delivery_date', 'empty'),
LTE('delivery_date', 'today_minus_42')
]))
return filters
def filters(self):
filter = []
if 'start_date' in self.config:
filter.extend([
AND([
GTE('date_of_death', 'startdate'),
LTE('date_of_death', 'enddate')
])
])
return filter
def get_age_filters(beta):
if beta:
return [NOT(EQ('age_tranche', 'age_72'))]
return [
AND([
NOT(EQ('age_tranche', 'age_0')),
NOT(EQ('age_tranche', 'age_6')),
NOT(EQ('age_tranche', 'age_72'))
])
]
def filters(self):
filters = super(PPSAvecDonnees, self).filters
filters.append(
AND([
GTE('real_date_repeat', "strsd"),
LTE('real_date_repeat', "stred")
]))
if 'archived_locations' in self.config:
filters.append(NOT(IN('location_id', 'archived_locations')))
return filters[1:]
def columns(self):
return [
DatabaseColumn("EBF stopped between 0-1 month",
CountUniqueColumn('doc_id', alias="stopped_0_1",
filters=self.filters + [LTE('ebf_stop_age_month', '1')])
),
DatabaseColumn("EBF stopped between 1-3 month",
CountUniqueColumn('doc_id', alias="stopped_1_3",
filters=self.filters + [AND([GT('ebf_stop_age_month', '1'), LTE('ebf_stop_age_month', '3')])])
),
DatabaseColumn("EBF stopped between 3-5 month",
CountUniqueColumn('doc_id', alias="stopped_3_5",
filters=self.filters + [AND([GT('ebf_stop_age_month', '3'), LTE('ebf_stop_age_month', '5')])])
),
DatabaseColumn("EBF stopped between 5-6 month",
CountUniqueColumn('doc_id', alias="stopped_5_6",
filters=self.filters + [AND([GT('ebf_stop_age_month', '5'), LTE('ebf_stop_age_month', '6')])])
)
]
def filters(self):
filter = []
if 'start_date' in self.config:
filter.extend([
AND([
GTE('date_of_death', 'startdate'),
LTE('date_of_death', 'enddate')
])
])
filter.extend([EQ('reason_for_child_closure', 'death')])
return filter
def columns(self):
return [
DatabaseColumn(
"ARI (Pneumonia) cases",
CountUniqueColumn('doc_id',
alias="ari_cases",
filters=self.filters +
[EQ('pneumonia_since_last_visit', 'yes')])),
DatabaseColumn(
"Diarrhea cases",
CountUniqueColumn(
'doc_id',
alias="diarrhea_cases",
filters=self.filters +
[EQ('has_diarrhea_since_last_visit', 'yes')])),
DatabaseColumn(
"ORS given during diarrhea",
CountUniqueColumn(
'doc_id',
alias="ors",
filters=self.filters + [
AND([
EQ('dairrhea_treated_with_ors', 'yes'),
EQ('has_diarrhea_since_last_visit', 'yes')
])
])),
DatabaseColumn(
"Zinc given during diarrhea",
CountUniqueColumn(
'doc_id',
alias="zinc",
filters=self.filters + [
AND([
EQ('dairrhea_treated_with_zinc', 'yes'),
EQ('has_diarrhea_since_last_visit', 'yes')
])
]))
]
def columns(self):
return [
DatabaseColumn(
"Trimester 1",
CountUniqueColumn(
'doc_id',
alias="trimester_1",
filters=self.filters + [
AND([
LTE('lmp', "today"),
GT('lmp', "first_trimester_start_date"),
NOTEQ('lmp', 'empty')
])
])),
DatabaseColumn(
"Trimester 2",
CountUniqueColumn(
'doc_id',
alias="trimester_2",
filters=self.filters + [
AND([
LTE('lmp', "second_trimester_start_date"),
GT('lmp', "second_trimester_end_date"),
NOTEQ('lmp', 'empty')
])
])),
DatabaseColumn(
"Trimester 3",
CountUniqueColumn(
'doc_id',
alias="trimester_3",
filters=self.filters + [
AND([
LTE('lmp', 'third_trimester_start_date'),
NOTEQ('lmp', 'empty')
])
]))
]
def columns(self):
registered_column = "registered_total_for_region"
if 'district_id' in self.config:
registered_column = 'registered_total_for_district'
return [
DatabaseColumn(
"No de PPS (number of PPS registered in that region)",
MaxColumn(registered_column, alias='registered')),
DatabaseColumn("No de PPS planifie (number of PPS planned)",
MaxColumn('planned_total')),
DatabaseColumn(
"No de PPS avec livrasion cet mois (number of PPS visited this month)",
CountUniqueColumn('location_id',
alias="visited",
filters=self.filters + [
AND([
GTE('real_date_repeat', "strsd"),
LTE('real_date_repeat', "stred")
])
])),
AggregateColumn(
"Taux de couverture (coverage ratio)", self.percent_fn,
[AliasColumn('registered'),
AliasColumn("visited")]),
DatabaseColumn(
"No de PPS avec donnees soumises (number of PPS which submitted data)",
CountUniqueColumn('location_id',
alias="submitted",
filters=self.filters + [
AND([
GTE('real_date_repeat', "strsd"),
LTE('real_date_repeat', "stred")
])
])),
AggregateColumn("Exhaustivite des donnees", self.percent_fn,
[AliasColumn('visited'),
AliasColumn('submitted')]),
]
def test_filters_multiple(self):
def test(filters):
filter_values = {
"startdate": date(2013, 02, 20),
"enddate": date(2013, 03, 05)
}
data = self._get_user_data(filter_values, filters)
self.assertNotIn('user1', data)
self.assertEqual(data['user2']['indicator_a'], 2)
self.assertEqual(data['user2']['indicator_b'], 1)
test([GTE('date', 'startdate'), LT('date', 'enddate')])
test([AND([GTE('date', 'startdate'), LT('date', 'enddate')])])
def filters(self):
filters = [
AND([GTE('opened_on', 'start_date'),
LT('opened_on', 'end_date')]),
]
locations_id = filter(lambda x: bool(x), self.config.locations_id)
if locations_id:
filters.append(
IN('person_owner_id',
get_INFilter_bindparams('locations_id', locations_id)))
return filters
def columns(self):
return [
DatabaseColumn(
"PNC in 48 hours",
CountUniqueColumn('doc_id', alias="pnc_1", filters=self.filters + [EQ('pp_1_done', 'yes')]),
),
DatabaseColumn(
"PNC in 2-4 days",
CountUniqueColumn('doc_id', alias="pnc_2", filters=self.filters + [EQ('pp_2_done', 'yes')]),
),
DatabaseColumn(
"PNC in 5-7",
CountUniqueColumn('doc_id', alias="pnc_3", filters=self.filters + [EQ('pp_3_done', 'yes')]),
),
DatabaseColumn(
"PNC in 21-42 days",
CountUniqueColumn('doc_id', alias="pnc_4", filters=self.filters + [EQ('pp_4_done', 'yes')]),
),
DatabaseColumn(
"PNC 1 visits Total Eligible",
CountUniqueColumn('doc_id', alias="pnc_1_eligible",
filters=self.filters + [AND([NOTEQ('delivery_date', 'empty'),
LTE('delivery_date', 'today')])]),
),
DatabaseColumn("PNC 2 visits Total Eligible",
CountUniqueColumn('doc_id', alias="pnc_2_eligible",
filters=self.filters + [AND([NOTEQ('delivery_date', 'empty'), LTE('delivery_date', 'today_minus_2')])]),
),
DatabaseColumn("PNC 3 visits Total Eligible",
CountUniqueColumn('doc_id', alias="pnc_3_eligible",
filters=self.filters + [AND([NOTEQ('delivery_date', 'empty'), LTE('delivery_date', 'today_minus_25')])]),
),
DatabaseColumn("PNC 4 visits Total Eligible",
CountUniqueColumn('doc_id', alias="pnc_4_eligible",
filters=self.filters + [AND([NOTEQ('delivery_date', 'empty'), LTE('delivery_date', 'today_minus_21')])]),
)
]
def filters(self):
filters = [
AND([GTE(self.date_property, 'start_date'), LT(self.date_property, 'end_date')])
]
locations_id = filter(lambda x: bool(x), self.config.locations_id)
if locations_id:
filters.append(
IN(self.location_property, get_INFilter_bindparams('locations_id', locations_id))
)
is_migrated = self.config.is_migrated
if is_migrated is not None:
filters.append(EQ('case_created_by_migration', 'is_migrated'))
return filters
def columns(self):
return [
DatabaseColumn("Total pregnant",
CountUniqueColumn('doc_id',
alias="total_pregnant")),
DatabaseColumn(
"No ANC",
CountUniqueColumn('doc_id',
alias="no_anc",
filters=self.filters +
[NOTEQ('anc_1', 'yes')])),
DatabaseColumn(
"ANC1",
CountUniqueColumn('doc_id',
alias="anc_1",
filters=self.filters +
[EQ('anc_1', 'yes')])),
DatabaseColumn(
"ANC2",
CountUniqueColumn('doc_id',
alias="anc_2",
filters=self.filters +
[EQ('anc_2', 'yes')])),
DatabaseColumn(
"ANC3",
CountUniqueColumn('doc_id',
alias="anc_3",
filters=self.filters +
[EQ('anc_3', 'yes')])),
DatabaseColumn(
"ANC4",
CountUniqueColumn('doc_id',
alias="anc_4",
filters=self.filters +
[EQ('anc_4', 'yes')])),
DatabaseColumn(
"TT1",
CountUniqueColumn('doc_id',
alias="tt_1",
filters=self.filters + [EQ('tt_1', 'yes')])),
DatabaseColumn(
"TT2",
CountUniqueColumn('doc_id',
alias="tt_2",
filters=self.filters + [EQ('tt_2', 'yes')])),
DatabaseColumn(
"TT Booster",
CountUniqueColumn('doc_id',
alias="tt_booster",
filters=self.filters +
[EQ('tt_booster', 'yes')])),
DatabaseColumn(
"TT Complete",
CountUniqueColumn(
'doc_id',
alias="tt_completed",
filters=self.filters +
[OR([EQ('tt_2', 'yes'),
EQ('tt_booster', 'yes')])])),
DatabaseColumn(
"IFA received",
CountUniqueColumn('doc_id',
alias="ifa_tablets",
filters=self.filters +
[EQ('iron_folic', 'yes')])),
DatabaseColumn(
"100 IFA consumed",
CountUniqueColumn('doc_id',
alias="100_tablets",
filters=self.filters[1:-1] + [
AND([
EQ('completed_100_ifa', 'yes'),
GTE('delivery_date', 'strsd'),
LTE('delivery_date', 'stred')
])
])),
DatabaseColumn(
"Clinically anemic mothers",
CountUniqueColumn('doc_id',
alias="clinically_anemic",
filters=self.filters +
[EQ('anemia_signs', 'yes')])),
DatabaseColumn(
"Number of pregnant mother referrals due to danger signs",
CountUniqueColumn('doc_id',
alias="danger_signs",
filters=self.filters +
[EQ('currently_referred', 'yes')])),
DatabaseColumn(
"Knows closest health facility",
CountUniqueColumn('doc_id',
alias="knows_closest_facility",
filters=self.filters +
[EQ('knows_closest_facility', 'yes')])),
DatabaseColumn(
"No ANC Total Eligible",
CountUniqueColumn('doc_id',
alias="no_anc_eligible",
filters=self.filters +
[LTE('edd', 'today_plus_196')])),
DatabaseColumn(
"ANC1 Total Eligible",
CountUniqueColumn('doc_id',
alias="anc_1_eligible",
filters=self.filters +
[LTE('edd', 'today_plus_196')])),
DatabaseColumn(
"ANC2 Total Eligible",
CountUniqueColumn(
'doc_id',
alias="anc_2_eligible",
filters=self.filters +
[AND([EQ('anc_1', 'yes'),
LTE('edd', 'today_plus_112')])])),
DatabaseColumn(
"ANC3 Total Eligible",
CountUniqueColumn(
'doc_id',
alias="anc_3_eligible",
filters=self.filters +
[AND([EQ('anc_2', 'yes'),
LTE('edd', 'today_plus_56')])])),
DatabaseColumn(
"ANC4 Total Eligible",
CountUniqueColumn(
'doc_id',
alias="anc_4_eligible",
filters=self.filters +
[AND([EQ('anc_3', 'yes'),
LTE('edd', 'today_plus_35')])])),
DatabaseColumn(
"TT1 Total Eligible",
CountUniqueColumn('doc_id',
alias="tt_1_eligible",
filters=self.filters +
[NOTEQ('previous_tetanus', 'yes')])),
DatabaseColumn(
"TT2 Total Eligible",
CountUniqueColumn('doc_id',
alias="tt_2_eligible",
filters=self.filters + [EQ('tt_1', 'yes')])),
DatabaseColumn(
"TT Booster Total Eligible",
CountUniqueColumn('doc_id',
alias="tt_booster_eligible",
filters=self.filters +
[EQ('previous_tetanus', 'yes')])),
DatabaseColumn(
"TT Completed (TT2 or Booster) Total Eligible",
CountUniqueColumn(
'doc_id',
alias="tt_completed_eligible",
filters=self.filters +
[OR([EQ('tt_1', 'yes'),
EQ('previous_tetanus', 'yes')])])),
DatabaseColumn(
"Taking IFA tablets Total Eligible",
CountUniqueColumn('doc_id', alias="ifa_tablets_eligible")),
DatabaseColumn(
"Completed 100 IFA tablets Total Eligible",
CountUniqueColumn('doc_id',
alias="100_tablets_eligible",
filters=self.filters[1:-1] + [
AND([
GTE('delivery_date', 'strsd'),
LTE('delivery_date', 'stred')
])
])),
DatabaseColumn(
"Clinically anemic mothers Total Eligible",
CountUniqueColumn('doc_id',
alias="clinically_anemic_eligible")),
DatabaseColumn(
"Number of mother referrals due to danger signs Total Eligible",
CountUniqueColumn('doc_id', alias="danger_signs_eligible")),
DatabaseColumn(
"Know closest health facility Total Eligible",
CountUniqueColumn('doc_id',
alias="knows_closest_facility_eligible"))
]
def columns(self):
test_type_filter = [RawFilter("bacteriological_examination = 1")]
filters_without_episode_type = self.filters[:-1]
bacteriological_test_date_reported = [
AND([
GTE('bacteriological_test_date_reported', 'start_date'),
LT('bacteriological_test_date_reported', 'end_date')
])
]
filters_with_bacteriological_date = bacteriological_test_date_reported + self.filters[
1:]
return (
generate_for_all_patient_types(
'pulmonary_microbiologically', self.filters +
diagnosis_filter('microbiological', 'pulmonary')) +
generate_for_all_patient_types(
'pulmonary_clinical',
self.filters + diagnosis_filter('clinical', 'pulmonary')) +
generate_for_all_patient_types(
'extra_pulmonary', self.filters + [
RawFilter('patient_type IS NOT NULL'),
RawFilter("disease_classification = 'extra_pulmonary'")
]) + generate_for_all_patient_types(
'total',
self.filters + [RawFilter("patient_type IS NOT NULL")]) +
generate_for_all_ranges(
'male', self.filters + [RawFilter("sex = 'male'")]) +
generate_for_all_ranges(
'female', self.filters + [RawFilter("sex = 'female'")]) +
generate_for_all_ranges(
'transgender',
self.filters + [RawFilter("sex = 'transgender'")]) +
generate_for_all_ranges('all', self.filters) + [
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=filters_without_episode_type +
test_type_filter + [
RawFilter(
"bacteriological_test_episode_type = 'presumptive_tb'"
)
],
alias='patients_with_presumptive_tb')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=
(filters_without_episode_type + test_type_filter + [
RawFilter(
"result_of_bacteriological_test = 'tb_detected'"
),
RawFilter(
"bacteriological_test_episode_type = 'presumptive_tb'"
)
]),
alias='patients_with_positive_tb')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=self.filters + [
RawFilter(
"hiv_status IN ('reactive', 'non_reactive')")
],
alias='all_hiv_tested')),
DatabaseColumn(
'',
CountColumn('doc_id',
filters=self.filters +
[RawFilter("hiv_status = 'reactive'")],
alias='hiv_reactive')),
DatabaseColumn(
'',
CountColumn('doc_id',
filters=self.filters + [
RawFilter("hiv_status = 'reactive'"),
RawFilter("cpt_initiated = 'yes'")
],
alias='hiv_reactive_cpt')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(self.filters +
[RawFilter("hiv_status = 'reactive'")] +
[RawFilter("initiated_on_art = 'yes'")]),
alias='hiv_reactive_art')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(filters_with_bacteriological_date +
convert_to_raw_filters_list(
"patient_type = 'new'",
"disease_classification = 'pulmonary'",
"diagnostic_result = 'tb_detected'")),
alias='new_positive_tb_pulmonary')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(filters_with_bacteriological_date +
convert_to_raw_filters_list(
"patient_type = 'new'",
"disease_classification = 'pulmonary'",
"diagnostic_result = 'tb_not_detected'")),
alias='new_negative_tb_pulmonary')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(
filters_with_bacteriological_date +
convert_to_raw_filters_list(
"patient_type = 'new'",
"disease_classification = 'extrapulmonary'",
"diagnostic_result = 'tb_detected'")),
alias='new_positive_tb_extrapulmonary')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(self.filters + convert_to_raw_filters_list(
"patient_type = 'recurrent'",
"diagnostic_result = 'tb_detected'")),
alias='recurrent_positive_tb')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(self.filters + convert_to_raw_filters_list(
"patient_type = 'treatment_after_failure'",
"diagnostic_result = 'tb_detected'")),
alias='failure_positive_tb')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(self.filters + convert_to_raw_filters_list(
"patient_type = 'treatment_after_lfu'",
"diagnostic_result = 'tb_detected'")),
alias='lfu_positive_tb')),
DatabaseColumn(
'',
CountColumn(
'doc_id',
filters=(self.filters + convert_to_raw_filters_list(
"patient_type = 'other_previously_treated'",
"diagnostic_result = 'tb_detected'")),
alias='other_positive_tb'))
])
def columns(self):
return [
DatabaseColumn(
"BCG",
CountUniqueColumn('doc_id',
alias="bcg",
filters=self.filters + [EQ('bcg', 'yes')])),
DatabaseColumn(
"OPV3",
CountUniqueColumn('doc_id',
alias="opv3",
filters=self.filters + [EQ('opv3', 'yes')])),
DatabaseColumn(
"HEP3",
CountUniqueColumn('doc_id',
alias="hep3",
filters=self.filters +
[EQ('hepb3', 'yes')])),
DatabaseColumn(
"DPT3",
CountUniqueColumn('doc_id',
alias="dpt3",
filters=self.filters + [EQ('dpt3', 'yes')])),
DatabaseColumn(
"Measles",
CountUniqueColumn('doc_id',
alias="measles",
filters=self.filters +
[EQ('measles', 'yes')])),
DatabaseColumn(
"Fully Immunized in 1st year",
CountUniqueColumn('doc_id',
alias="fully_immunized",
filters=self.filters + [
AND([
EQ('bcg', 'yes'),
EQ('opv0', 'yes'),
EQ('hepb0', 'yes'),
EQ('opv1', 'yes'),
EQ('hepb1', 'yes'),
EQ('dpt1', 'yes'),
EQ('opv2', 'yes'),
EQ('hepb2', 'yes'),
EQ('dpt2', 'yes'),
EQ('opv3', 'yes'),
EQ('hepb3', 'yes'),
EQ('dpt3', 'yes'),
EQ('measles', 'yes')
])
])),
DatabaseColumn(
"DPT-OPT Booster",
CountUniqueColumn('doc_id',
alias="dpt_opv_booster",
filters=self.filters +
[EQ('dpt_opv_booster', 'yes')])),
DatabaseColumn(
"VitA3",
CountUniqueColumn('doc_id',
alias="vita3",
filters=self.filters +
[EQ('vita3', 'yes')])),
DatabaseColumn(
"BCG Total Eligible",
CountUniqueColumn('doc_id', alias="bcg_eligible"),
),
DatabaseColumn(
"OPV3 Total Eligible",
CountUniqueColumn('doc_id',
alias="opv3_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_106')])),
DatabaseColumn(
"HEP3 Total Eligible",
CountUniqueColumn('doc_id',
alias="hep3_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_106')])),
DatabaseColumn(
"DPT3 Total Eligible",
CountUniqueColumn('doc_id',
alias="dpt3_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_106')])),
DatabaseColumn(
"Measles Total Eligible",
CountUniqueColumn('doc_id',
alias="measles_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_273')])),
DatabaseColumn(
"Fully Immunized Total Eligible",
CountUniqueColumn('doc_id',
alias="fully_immunized_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_273')])),
DatabaseColumn(
"DPT-OPT Booster Total Eligible",
CountUniqueColumn('doc_id',
alias="dpt_opv_booster_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_548')])),
DatabaseColumn(
"VitA3 Total Eligible",
CountUniqueColumn('doc_id',
alias="vita3_eligible",
filters=self.filters +
[LTE('dob', 'today_minus_700')]))
]
def columns(self):
return [
DatabaseColumn("Total pregnant",
CountUniqueColumn('doc_id',
alias="total_pregnant")),
DatabaseColumn(
"ANC3",
CountUniqueColumn('doc_id',
alias="anc_3",
filters=self.filters +
[EQ('anc_3', 'yes')])),
DatabaseColumn(
"TT Completed (TT2 or Booster)",
CountUniqueColumn(
'doc_id',
alias="tt_completed",
filters=self.filters +
[OR([EQ('tt_2', 'yes'),
EQ('tt_booster', 'yes')])])),
DatabaseColumn(
"Taking IFA tablets",
CountUniqueColumn('doc_id',
alias="ifa_tablets",
filters=self.filters +
[EQ('iron_folic', 'yes')])),
DatabaseColumn(
"Completed 100 IFA tablets",
CountUniqueColumn('doc_id',
alias="100_tablets",
filters=self.filters[1:-1] + [
AND([
EQ('completed_100_ifa', 'yes'),
GTE('delivery_date', 'strsd'),
LTE('delivery_date', 'stred')
])
])),
DatabaseColumn(
"ANC3 Total Eligible",
CountUniqueColumn(
'doc_id',
alias="anc_3_eligible",
filters=self.filters +
[AND([EQ('anc_2', 'yes'),
LTE('edd', 'today_plus_56')])])),
DatabaseColumn(
"TT Completed (TT2 or Booster) Total Eligible",
CountUniqueColumn(
'doc_id',
alias="tt_completed_eligible",
filters=self.filters +
[OR([EQ('tt_1', 'yes'),
EQ('previous_tetanus', 'yes')])])),
DatabaseColumn(
"Taking IFA tablets Total Eligible",
CountUniqueColumn('doc_id', alias="ifa_tablets_eligible")),
DatabaseColumn(
"Completed 100 IFA tablets Total Eligible",
CountUniqueColumn('doc_id',
alias="100_tablets_eligible",
filters=self.filters[1:-1] + [
AND([
GTE('delivery_date', 'strsd'),
LTE('delivery_date', 'stred')
])
])),
]
def columns(self):
return [
DatabaseColumn(
"Total pregnant",
CountUniqueColumn('doc_id', alias="total_pregnant"),
),
DatabaseColumn(
"ANC3",
CountUniqueColumn('doc_id',
alias="anc_3",
filters=self.filters + [EQ('anc_3', 'yes')]),
),
DatabaseColumn(
"TT Completed (TT2 or Booster)",
CountUniqueColumn(
'doc_id',
alias="tt_completed",
filters=self.filters +
[OR([EQ('tt_2', 'yes'),
EQ('tt_booster', 'yes')])]),
),
DatabaseColumn(
"Taking IFA tablets",
CountUniqueColumn('doc_id',
alias="ifa_tablets",
filters=self.filters +
[EQ('iron_folic', 'yes')]),
),
DatabaseColumn(
"Completed 100 IFA tablets",
CountUniqueColumn('doc_id',
alias="100_tablets",
filters=self.filters +
[EQ('completed_100_ifa', 'yes')]),
),
DatabaseColumn(
"ANC3 Total Eligible",
CountUniqueColumn(
'doc_id',
alias="anc_3_eligible",
filters=self.filters +
[AND([EQ('anc_2', 'yes'),
LTE('lmp', 'days_224')])]),
),
DatabaseColumn(
"TT Completed (TT2 or Booster) Total Eligible",
CountUniqueColumn(
'doc_id',
alias="tt_completed_eligible",
filters=self.filters +
[OR([EQ('tt_1', 'yes'),
EQ('previous_tetanus', 'yes')])]),
),
DatabaseColumn(
"Taking IFA tablets Total Eligible",
CountUniqueColumn('doc_id', alias="ifa_tablets_eligible"),
),
DatabaseColumn(
"Completed 100 IFA tablets Total Eligible",
CountUniqueColumn('doc_id',
alias="100_tablets_eligible",
filters=self.filters +
[LTE('lmp', 'days_195')]),
)
]
