Cost Effectiveness Meta Regression of Rotavirus Vaccination

This repository contains the code that performs the cost effectiveness meta-regression analysis of Rotavirus vaccination programs. This analysis has been accepted for publication in Vaccine under the title, "Cost-effectiveness of Rotavirus vaccination in children under five years of age in 195 Countries: A Metaregression Analysis".

Purpose

The purpose for this repository is to make the analytic code for this project available as part of Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) compliance.

Organization

All input, intermediate, and output files are defined in the file paths.py, and are replaced with "FILEPATH".

Scripts should be run in the following order:

1. create_prediction_df_public.py

   Constructs a data set consisting of pairs of ratios from the same article and location that differ only in that they use different values of one covariate.

2. crosswalks_public.ipynb

   Analyses of differences between ICERs for sensitivity-reference pairs of ratios. Uses functions defined in crosswalk_functions.py.

3. rotavirus_mr_public.ipynb

   Most of the analytic code as well as some code to generate plots, including those in Figure 2 of the publication. Uses functions defined in mr_functions.py and plotting_functions.py.

4. create_prediction_df_public.py

   Generates predictions and uncertainty intervals using model objects fitted in hpv_analysis.py.

5. The logistics regression code file is unavailable. It is possible to reference the logistic_regression.R from https://github.com/ihmeuw/cost_effectiveness_hpv_vax_metareg for a comparable analysis.

6. Code to map the ICERs is currently unavailable. It is possible to reference the map_icers.R from https://github.com/ihmeuw/cost_effectiveness_hpv_vax_metareg for a comparable analysis.

Inputs

Inputs required for the code to run are:

1. Valid paths to directories must be specified as ROOT_DIR, PLOT_DIR, and MODEL_RESULTS_DIR in paths.py.

2. A data file whose path is specified in paths.py as CLEANED_REG_DF.

3. A file specifying the values of all covariates for each prediction. Its path is specified in paths.py as CLEANED_PREDS_DF.

4. A shapefile in rds format that defines the boundaries of countries. This is used only in map_icers.R and is saved in a location specified as SHAPEFILE in paths.py.

size for children under 5 years for each year$ rota_vaccine_sev Mean SEV for “lack of rotavirus vaccine” risk. cost_per_case Mean inpatient and outpatient costs for each diarrhea case. vaccine_cost_per_course Mean per person cost for each course of vaccine administered

Calculations are outlined in accompanying word document

Diarrhea viz

tool: Rotavirus vaccine cost calculations

Note: This dataset only includes 188 locations, rather than 195, as we only have healthcare cost data for 188 countries.

Variable Description

year_id year location_id GBD location IDs mi_ratio Mean deaths per rotavirus case for children under 5 years for each year-location combination. population Mean population size for children under 5 years for each year-location combination. rota_vaccine_sev Mean SEV for “lack of rotavirus vaccine” risk. This should match the values already being used in the viz tool (from Abie). cost_per_case Mean inpatient and outpatient costs for each diarrhea case. vaccine_cost_per_course Mean per person cost for each course of vaccine administered; includes vaccine unit costs, supply chain, and service delivery costs.