Cervical cancer #1287
Cervical cancer #1287
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Thanks @andrew-phillips-1 for this first draft. I think it looks good. I will be adding some few comments/suggestions for your consideration. |
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Thanks @mnjowe |
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| # ----- SCHEDULE LOGGING EVENTS ----- | ||
| # Schedule logging event to happen immediately | ||
| sim.schedule_event(CervicalCancerLoggingEvent(self), sim.date + DateOffset(months=0)) |
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Why schedule logging event immediately yet polling event is starting a month after? Are we interested in logging defaults also?
| sim.schedule_event(CervicalCancerLoggingEvent(self), sim.date + DateOffset(months=0)) | ||
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| # ----- SCHEDULE MAIN POLLING EVENTS ----- | ||
| # Schedule main polling event to happen immediately |
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| # Schedule main polling event to happen immediately | |
| # Schedule main polling event to happen after a month |
| Types.REAL, | ||
| "probabilty per month of oncogenic hpv infection", |
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| Types.REAL, | |
| "probabilty per month of oncogenic hpv infection", | |
| Types.REAL, | |
| "probability per month of oncogenic hpv infection", |
| Types.REAL, | ||
| "probabilty per month of incident cin1 amongst people with hpv", |
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| Types.REAL, | |
| "probabilty per month of incident cin1 amongst people with hpv", | |
| Types.REAL, | |
| "probability per month of incident cin1 amongst people with hpv", |
| Types.REAL, | ||
| "probabilty per month of incident cin2 amongst people with cin1", |
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| Types.REAL, | |
| "probabilty per month of incident cin2 amongst people with cin1", | |
| Types.REAL, | |
| "probability per month of incident cin2 amongst people with cin1", |
| Types.REAL, | ||
| "probabilty per month of incident cin3 amongst people with cin2", |
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| Types.REAL, | |
| "probabilty per month of incident cin3 amongst people with cin2", | |
| Types.REAL, | |
| "probability per month of incident cin3 amongst people with cin2", |
| Types.REAL, | ||
| "probabilty per month of incident stage1 cervical cancer amongst people with cin3", |
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typo. change probabilty to probability for Ln 105, 109, 113, 117 and 121.
| def on_hsi_alert(self, person_id, treatment_id): | ||
| pass |
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are you planning on doing something here in the next draft? if not I think we can remove the function.
| # this was not assigned here at outset because baseline value of hv_inf was not accessible - it is assigned | ||
| # st start of main polling event below |
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why is baseline value for hv_inf not accessible yet HIV module is included in the dependencies section and hv_inf has been initialised here in Hiv module? what was the error?
| # this was done here and not at outset because baseline value of hv_inf was not accessible | ||
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| given_date = pd.to_datetime('2010-02-03') | ||
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| if self.sim.date < given_date: | ||
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| women_over_15_nhiv_idx = df.index[(df["age_years"] > 15) & (df["sex"] == 'F') & ~df["hv_inf"]] | ||
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| df.loc[women_over_15_nhiv_idx, 'ce_hpv_cc_status'] = rng.choice( | ||
| ['none', 'hpv', 'cin1', 'cin2', 'cin3', 'stage1', 'stage2a', 'stage2b', 'stage3', 'stage4'], | ||
| size=len(women_over_15_nhiv_idx), p=p['init_prev_cin_hpv_cc_stage_nhiv'] | ||
| ) | ||
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| women_over_15_hiv_idx = df.index[(df["age_years"] > 15) & (df["sex"] == 'F') & df["hv_inf"]] | ||
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| df.loc[women_over_15_hiv_idx, 'ce_hpv_cc_status'] = rng.choice( | ||
| ['none', 'hpv', 'cin1', 'cin2', 'cin3', 'stage1', 'stage2a', 'stage2b', 'stage3', 'stage4'], | ||
| size=len(women_over_15_hiv_idx), p=p['init_prev_cin_hpv_cc_stage_hiv'] | ||
| ) |
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I think we can do this in initialise population? I'm interested to know why the value for hv_inf is not accessible at initialise population yet we have included Hiv in the list of dependencies
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| df.ce_selected_for_via_this_month = False | ||
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| eligible_population = df.is_alive & (df.sex == 'F') & (df.age_years > 30) & (df.age_years < 50) & \ |
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| eligible_population = df.is_alive & (df.sex == 'F') & (df.age_years > 30) & (df.age_years < 50) & \ | |
| eligible_population = df.is_alive & (df.sex == 'F') & (df.age_years.between(30, 50, inclusive="neither") & \ |
| | df.ce_ever_treated) | ||
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| # -------------------------------- SCREENING FOR CERVICAL CANCER USING XPERT HPV TESTING AND VIA--------------- | ||
| # A subset of women aged 30-50 will receive a screening test |
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should the boundaries be included(30yrs and 50yrs) selection on Ln 720 is excluding them
| self.sim.schedule_event( | ||
| InstantaneousDeath(self.module, person_id, "CervicalCancer"), self.sim.date | ||
| ) | ||
| df.loc[selected_to_die, 'ce_date_death'] = self.sim.date |
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is date of death not recorded already in demography?
| # Ignore this event if the person is no longer alive: | ||
| if not df.at[person_id, 'is_alive']: | ||
| return hs.get_blank_appt_footprint() |
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@tbhallett is this not being handled already by the Healthsystem? If yes then I think we will save some computational time by removing it here and in all other HSI's.
| if random_value <= p['prob_cure_stage1'] and df.at[person_id, "ce_date_treatment"] == self.sim.date: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'none' | ||
| df.at[person_id, 'ce_current_cc_diagnosed'] = False | ||
| else: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'stage1' | ||
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| if random_value <= p['prob_cure_stage2a'] and df.at[person_id, "ce_date_treatment"] == self.sim.date: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'none' | ||
| df.at[person_id, 'ce_current_cc_diagnosed'] = False | ||
| else: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'stage2a' | ||
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| if random_value <= p['prob_cure_stage2b'] and df.at[person_id, "ce_date_treatment"] == self.sim.date: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'none' | ||
| df.at[person_id, 'ce_current_cc_diagnosed'] = False | ||
| else: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'stage2b' | ||
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| if random_value <= p['prob_cure_stage3'] and df.at[person_id, "ce_date_treatment"] == self.sim.date: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'none' | ||
| df.at[person_id, 'ce_current_cc_diagnosed'] = False | ||
| else: | ||
| df.at[person_id, "ce_hpv_cc_status"] = 'stage3' |
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Are we assuming that patients do recover from cervical cancer same day they receive treatment?
| # Schedule another instance of the event for one month | ||
| hs.schedule_hsi_event( | ||
| hsi_event=HSI_CervicalCancer_PalliativeCare( | ||
| module=self.module, | ||
| person_id=person_id | ||
| ), | ||
| topen=self.sim.date + DateOffset(months=1), | ||
| tclose=None, | ||
| priority=0 | ||
| ) |
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@tbhallett don't we have frequency argument in HSI events? could be useful here
| self.repeat = 30 | ||
| super().__init__(module, frequency=DateOffset(days=self.repeat)) |
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how about changing days to months i.e.
| self.repeat = 30 | |
| super().__init__(module, frequency=DateOffset(days=self.repeat)) | |
| self.repeat = 1 | |
| super().__init__(module, frequency=DateOffset(months=self.repeat)) |
| self.repeat = 30 | ||
| super().__init__(module, frequency=DateOffset(days=self.repeat)) | ||
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| def apply(self, population): |
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I think the use of groupby can be more efficient in computing the statistics below?
| # warnings.warn(UserWarning(f"Couldn't find priority ranking for TREATMENT_ID \n" | ||
| # f"{hsi_event.TREATMENT_ID}")) |
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I think this should be uncommented
| @@ -40,7 +40,7 @@ | |||
| from tlo.util import create_age_range_lookup | |||
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| logger = logging.getLogger(__name__) | |||
| logger.setLevel(logging.INFO) | |||
| logger.setLevel(logging.CRITICAL ) | |||
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Any reason you are setting this to critical? I think if we don't want .INFO logs from Hiv module, we can configure cervical cancer analyses to only allow logging.INFO from cervical cancer module
| @@ -20,7 +20,7 @@ | |||
| from tlo.util import random_date | |||
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| logger = logging.getLogger(__name__) | |||
| logger.setLevel(logging.INFO) | |||
| logger.setLevel(logging.CRITICAL) | |||
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same here, we can configure this in cervical cancer analyses. This should be as it was
| logger.setLevel(logging.CRITICAL) | |
| logger.setLevel(logging.INFO) |
| @@ -16,7 +16,7 @@ | |||
| from tlo.progressbar import ProgressBar | |||
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| logger = logging.getLogger(__name__) | |||
| logger.setLevel(logging.INFO) | |||
| logger.setLevel(logging.CRITICAL) | |||
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same here.
| logger.setLevel(logging.CRITICAL) | |
| logger.setLevel(logging.INFO) |
| @@ -82,7 +82,7 @@ def __init__(self, *, start_date: Date, seed: int = None, log_config: dict = Non | |||
| self.rng = np.random.RandomState(np.random.MT19937(self._seed_seq)) | |||
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| def configure_logging(self, filename: str = None, directory: Union[Path, str] = "./outputs", | |||
| custom_levels: Dict[str, int] = None, suppress_stdout: bool = False): | |||
| custom_levels: Dict[str, int] = None, suppress_stdout: bool = True): | |||
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I think we can also do this in analyses file
| custom_levels: Dict[str, int] = None, suppress_stdout: bool = True): | |
| custom_levels: Dict[str, int] = None, suppress_stdout: bool = False): |
| # print(stats_dict) | ||
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| # print(stats_dict) |
| # todo: not sure what is wrong with this assert as I am fairly certain the intended assert is true | ||
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| # assert set(sim.modules['SymptomManager'].who_has('vaginal_bleeding')).issubset( | ||
| # df.index[df.ce_cc_ever]) |
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This test is just okay. It is failing because of how test test_check_progression_through_stages_is_blocked_by_treatment has been configured.
| sim.population.props.loc[population_of_interest, "ce_hpv_cc_status"] = 'stage1' | ||
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| # force that they are all symptomatic | ||
| sim.modules['SymptomManager'].change_symptom( | ||
| person_id=population_of_interest.index[population_of_interest].tolist(), | ||
| symptom_string='vaginal_bleeding', | ||
| add_or_remove='+', | ||
| disease_module=sim.modules['CervicalCancer'] | ||
| ) |
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This will make all >15 yrs females be on stage 1 and have cancer symptoms yes BUT it will not automatically make everyone deemed as ever had cervical cancer in the code Hence check
assert set(sim.modules['SymptomManager'].who_has('vaginal_bleeding')).issubset( df.index[df.ce_cc_ever]) is likely to fail
Here's a first draft of this module. I need to do another search to try to find additional data for calibration.
I couldn't upload the draft write as it was asking me to use the command line and Git LFS.