Modularize model in preparation for fitting real NHSN data

pipelines/build_pyrenew_model.py

@@ -4,7 +4,13 @@
 import jax.numpy as jnp
 from pyrenew.deterministic import DeterministicVariable
 
-from pyrenew_hew.pyrenew_hew_model import pyrenew_hew_model
+from pyrenew_hew.pyrenew_hew_model import (
+    EDVisitObservationProcess,
+    HospAdmitObservationProcess,
+    LatentInfectionProcess,
+    PyrenewHEWModel,
+    WastewaterObservationProcess,
+)
 
 
 def build_model_from_dir(model_dir):
@@ -21,6 +27,11 @@
         "inf_to_ed", jnp.array(model_data["inf_to_ed_pmf"])
     )  # check if off by 1 or reversed
 
+    # use same as inf to ed, per NNH guidelines
+    inf_to_hosp_admit_rv = DeterministicVariable(
+        "inf_to_hosp_admit", jnp.array(model_data["inf_to_ed_pmf"])
+    )  # check if off by 1 or reversed
+
     generation_interval_pmf_rv = DeterministicVariable(
         "generation_interval_pmf",
         jnp.array(model_data["generation_interval_pmf"]),
@@ -37,9 +48,9 @@
     data_observed_disease_hospital_admissions = jnp.array(
         model_data["data_observed_disease_hospital_admissions"]
     )
-    state_pop = jnp.array(model_data["state_pop"])
+    population_size = jnp.array(model_data["state_pop"])
 
-    right_truncation_pmf_rv = DeterministicVariable(
+    ed_right_truncation_pmf_rv = DeterministicVariable(
         "right_truncation_pmf", jnp.array(model_data["right_truncation_pmf"])
     )
 
@@ -55,8 +66,7 @@
 
     right_truncation_offset = model_data["right_truncation_offset"]
 
-    my_model = pyrenew_hew_model(
-        state_pop=state_pop,
+    my_latent_infection_model = LatentInfectionProcess(
         i0_first_obs_n_rv=priors["i0_first_obs_n_rv"],
         initialization_rate_rv=priors["initialization_rate_rv"],
         log_r_mu_intercept_rv=priors["log_r_mu_intercept_rv"],
@@ -65,14 +75,34 @@
         generation_interval_pmf_rv=generation_interval_pmf_rv,
         infection_feedback_strength_rv=priors["inf_feedback_strength_rv"],
         infection_feedback_pmf_rv=infection_feedback_pmf_rv,
+        n_initialization_points=uot,
+    )
+
+    my_ed_visit_obs_model = EDVisitObservationProcess(
         p_ed_mean_rv=priors["p_ed_visit_mean_rv"],
         p_ed_w_sd_rv=priors["p_ed_visit_w_sd_rv"],
         autoreg_p_ed_rv=priors["autoreg_p_ed_visit_rv"],
         ed_wday_effect_rv=priors["ed_visit_wday_effect_rv"],
         inf_to_ed_rv=inf_to_ed_rv,
-        phi_rv=priors["phi_rv"],
-        right_truncation_pmf_rv=right_truncation_pmf_rv,
-        n_initialization_points=uot,
+        ed_neg_bin_concentration_rv=(priors["ed_neg_bin_concentration_rv"]),
+        ed_right_truncation_pmf_rv=ed_right_truncation_pmf_rv,
+    )
+
+    my_hosp_admit_obs_model = HospAdmitObservationProcess(
+        inf_to_hosp_admit_rv=inf_to_hosp_admit_rv,
+        hosp_admit_neg_bin_concentration_rv=(
+            priors["hosp_admit_neg_bin_concentration_rv"]
+        ),
+    )
+
+    my_wastewater_obs_model = WastewaterObservationProcess()
+
+    my_model = PyrenewHEWModel(
+        population_size=population_size,
+        latent_infection_process_rv=my_latent_infection_model,
+        ed_visit_obs_process_rv=my_ed_visit_obs_model,
+        hosp_admit_obs_process_rv=my_hosp_admit_obs_model,
+        wastewater_obs_process_rv=my_wastewater_obs_model,
     )
 
     return (

pipelines/priors/prod_priors.py

@@ -65,4 +65,11 @@
 )
 
 # Based on looking at some historical posteriors.
-phi_rv = DistributionalVariable("phi", dist.LogNormal(4, 1))
+ed_neg_bin_concentration_rv = DistributionalVariable(
+    "ed_visit_neg_bin_concentration", dist.LogNormal(4, 1)
+)
+
+# more diffuse than ED visit, same mean
+hosp_admit_neg_bin_concentration_rv = DistributionalVariable(
+    "hosp_admit_neg_bin_concentration", dist.LogNormal(4, 2)
+)