Model Output plots
+26 November, 2024
+ +Here is a snapshot 📸 of your model outputs for run ID +20241126_125533EST, from config config_sample_2pop_inference.yml, stored +in model_output.
+1 Infection timeseries:
+SEIR model output
+These are the outputs for the compartmental epidemic model, stored in
+the seir directory, which track the prevalence and
+incidence of individuals in each model compartment over time.
Incidence values are per day.
+## [1] "Assuming inference run with files in/global/final"
+## [1] "Importing seir files (n = 10):"## [1] "Assuming inference run with files in/global/final"
+## [1] "Importing llik files (n = 10):"1.1 All +infections
+Total number of individuals in each infection state over time
+(compartments defined by infection_stage), aggregated
+across other strata. Plotted for slot 4 which has the highest total
+likelihood over all subpopulations (if inferrence was run) or was
+randomly chosen (if no inference).
1.1.1 +Total
+1.1.1.1 Prevalence
+
1.1.1.2 Cumulative +incidence
+
1.1.2 Per +capita
+1.1.2.1 Prevalence
+
1.1.2.2 Cumulative +incidence
+
2 Outcome timeseries:
+HOSP model output
+These are the outputs for the observational (“outcomes”) model,
+stored in the hosp directory, which tracks the incidence
+and prevalence of individuals with defined observed disease outcomes
+over time.
2.1 +Aggregate outcomes - by slot
+Total number of individuals with each outcome over time, aggregated +across other strata (only outcomes without an “_” specifying a +stratification are plotted). If more than one simulation (slot) was run, +results are plotted for slot 4 which has the highest total likelihood +over all subpopulations (if inference was run) or was randomly chosen +(if no inference). Incidence values are per day.
+If inference was run, only some of these outcomes may have been used +in inference, and the outcomes may have been aggregated to a longer time +period (e.g., weeks, months). Inference-specific outcomes, along with +the data they were compared to, are shown in later plots.
+[1] “Assuming inference run with files in/global/final” [1] +“Importing hosp files (n = 10):”
+2.1.1 +incidCase
+2.1.1.1 Total
+
2.1.2 +incidHosp
+2.1.2.1 Total
+
2.1.3 +currHosp
+2.1.3.1 Total
+
2.1.4 +incidDeath
+2.1.4.1 Total
+
2.2 +Inference-specific outcomes - by slot
+The inference method specified that the model be fit to sum_hosp, +with aggregation over period: 1 weeks. Plotted for slot 4 which has the +highest total likelihood over all subpopulations (if inference was run) +or was randomly chosen (if no inference).
+[1] “Assuming inference run with files in/global/final” [1] +“Importing hosp files (n = 10):”
+2.2.1 +sum_hosp
+
2.3 +Inference-specific outcomes - quantiles
+The inference method specified that the model be fit to sum_hosp, +with aggregation over period: 1 weeks. In total 10 slots ran +successfully.
+2.3.1 +sum_hosp
+
+## Inference-specific outcomes - by likelihood{.tabset}
The inference method specified that the model be fit to sum_hosp, +with aggregation over period: 1 weeks. In total 10 slots ran +successfully.
+This section plots the top 5 and bottom 5 log likelihoods for each +subpopulation.
+2.3.2 +sum_hosp
+
3 Infection model
+parameters: SNPI model output
+These are the parameters that define time-dependent modifications to
+the infection model parameters, and are stored in the snpi
+directory.
3.1 Values by slot
+If inference is run, parameters are the final values at the end of
+all MCMC iterations, colored by their likelihoods in a given
+subpopulation.
+
3.2 MCMC evolution
+The accepted value of the parameter for each iteration of the MCMC +algorithm, colored by their likelihood in a given subpopulation. If more +than 5 slots were run, we will plot only the top 5 and bottom 5 log +likelihoods for each subpopulation.
+
3.3 MCMC evolution - +chimeric vs global
+The accepted value of the parameter for each iteration of the MCMC +algorithm, for both the chimeric and global chain, in a given +subpopulation. Plotted for slot 4 which has the highest total likelihood +over all subpopulations (if inference was run) or was randomly chosen +(if no inference).
+
4 Outcome model
+parameters: HNPI model output
+This shows the parameters associated with your outcomes model, for +all subpopulations.
+4.1 Values by slot
+If inference is run, parameters are the final values at the end of +all MCMC iterations, coloured by their likelihoods in a given +subpopulation.
+
4.2 MCMC evolution
+The accepted value of the parameter for each iteration of the MCMC +algorithm, colored by their likelihood in a given subpopulation. If more +than 5 slots were run, we will plot only the top 5 and bottom 5 log +likelihoods for each subpopulation.
+
4.3 MCMC evolution - +chimeric vs global
+The accepted value of the parameter for each iteration of the MCMC +algorithm, for both the chimeric and global chain, in a given +subpopulation. Plotted for slot 4 which has the highest total likelihood +over all subpopulations (if inference was run) or was randomly chosen +(if no inference).
+
5 Likelihood:
+LLIK model output
+5.1 Acceptance and +likelihood trajectories - All slots and subpopulations
+This plot shows the binary acceptance decision for each MCMC
+iteration (accept), the probability of acceptance for that
+acceptance decision (accept_prob), the running average
+acceptance probability (accept_avg), and the likelihood.
+Chimeric values are subpopulation specific - there are
+likely more acceptances as well as acceptances that can increase
+subpop-specific likelihood while not changing the total likelihood.
+Global acceptances occur for all subpopulations together,
+and will always result in the total likelihood increasing, but could
+result in decreases in the subpop-specific likelihood.
## [1] "Assuming inference run with files in/global/intermediate"
+## [1] "Importing llik files (n = 120):"## [1] "Assuming inference run with files in/chimeric/intermediate"
+## [1] "Importing llik files (n = 120):"
5.2 Acceptance and +likelihood trajectories - Single slot
+