Modify priors on eta_sd and inf_feedback (#236)

CDCgov · Nov 12, 2024 · bb1478d · bb1478d
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diff --git a/NEWS.md b/NEWS.md
@@ -8,7 +8,8 @@ hospital admissions to output of function and package data. ([#184](https://gith
 - `get_plot_subpop_rt()` now uses a shared y-axis to facilitate comparison of R(t) estimates) ([#245](https://github.com/CDCgov/ww-inference-model/issues/245))
 
 ## Internal changes
-- Updated the workflow for posting the pages artifact to PRs (issue [#229](https://github.com/CDCgov/ww-inference-model/issues/229)).
+- Modified the priors on the infection feedback term and the step size of the weekly random walk in the effective reproductive number (issue [#227](https://github.com/CDCgov/ww-inference-model/issues/227)), based on benchmarking results from the evaluation pipeline described in the [PR](https://github.com/CDCgov/ww-inference-model/pull/236) corresponding to this change.
+- Updated the workflow for posting the pages artifact to PRs (issue [#229](https://github.com/CDCgov/ww-inference-model/issues/229)(https://github.com/CDCgov/ww-inference-model/issues/229)).
 - Modify `plot_forecasted_counts()` so that it does not require an evaluation dataset ([#218](https://github.com/CDCgov/ww-inference-model/pull/218))
 
 # wwinference 0.1.0

diff --git a/R/get_stan_data.R b/R/get_stan_data.R
@@ -620,6 +620,7 @@ get_stan_data <- function(input_count_data,
     sd_log_sigma_ww_site_prior_sd =
       params$sd_log_sigma_ww_site_prior_sd,
     eta_sd_sd = params$eta_sd_sd,
+    eta_sd_mean = params$eta_sd_mean,
     sigma_i_first_obs_prior_mode = params$sigma_i_first_obs_prior_mode,
     sigma_i_first_obs_prior_sd = params$sigma_i_first_obs_prior_sd,
     p_hosp_prior_mean = params$p_hosp_mean,

diff --git a/inst/extdata/example_params.toml b/inst/extdata/example_params.toml
@@ -41,9 +41,11 @@ offset_ref_initial_exp_growth_rate_prior_sd = 0.025
 
 autoreg_p_hosp_a = 1 # shape1 parameter of autoreg term on IHR(t) trend
 autoreg_p_hosp_b = 100 # shape2 parameter of autoreg term on IHR(t) trend
+eta_sd_mean = 0.0278 # from posterior of fit to long time series
 eta_sd_sd = 0.01
-infection_feedback_prior_logmean = 6.37408 # log(mode) + q^2 mode = 500, q = 0.4
-infection_feedback_prior_logsd = 0.4
+infection_feedback_prior_logmean = 4.498 # log(~90) from posterior of fit to long
+# time series
+infection_feedback_prior_logsd = 0.636 # log(~1.9)
 
 [hospital_admission_observation_process]
 # Hospitalization parameters (informative priors)

diff --git a/inst/stan/wwinference.stan b/inst/stan/wwinference.stan
@@ -85,6 +85,7 @@ data {
   real sd_log_sigma_ww_site_prior_mode;
   real<lower=0> sd_log_sigma_ww_site_prior_sd;
   real<lower=0> eta_sd_sd;
+  real<lower=0> eta_sd_mean;
   real p_hosp_prior_mean;
   real<lower=0> p_hosp_sd_logit;
   real<lower=0> p_hosp_w_sd_sd;
@@ -325,7 +326,7 @@ model {
                                         offset_ref_logit_i_first_obs_prior_sd);
   offset_ref_initial_exp_growth_rate ~ normal(offset_ref_initial_exp_growth_rate_prior_mean,
                                               offset_ref_initial_exp_growth_rate_prior_sd);
-  eta_sd ~ normal(0, eta_sd_sd);
+  eta_sd ~ normal(eta_sd_mean, eta_sd_sd);
   autoreg_rt_subpop ~ beta(autoreg_rt_subpop_a, autoreg_rt_subpop_b);
 
   autoreg_rt ~ beta(autoreg_rt_a, autoreg_rt_b);

diff --git a/tests/testthat/test_preprocess_ww_data.R b/tests/testthat/test_preprocess_ww_data.R
@@ -382,8 +382,7 @@ test_that("Function handles LOD values equal to concentration values", {
 
 test_that("Constant population per site", {
   wrong_pop <- ww_data
-
-  wrong_pop$site_pop <- 1e6 + seq_len(nrow(ww_data))
+  wrong_pop$site_pop[1] <- ww_data$site_pop[1] + 1000
 
   expect_error(
     preprocess_ww_data(