Estimate sub-national LASV infections and LF incidence rates in West Africa
# lassa-model
Estimate sub-national LASV infections and LF incidence rates in West Africa
This repository contains the code to recreate the modeling analysis in the article "Estimation of Lassa fever incidence rates in West Africa: development of a modeling framework to inform vaccine trial design". This article is currently available as a preprint at:
doi.org
The analysis involves running the following R scripts from the 'code' directory:
*Note: to successfully complete this analysis for the 2nd administrative level, the zip file containing population data, adm_2_pop_upd.z, will first need to be unzipped.
0. prior_iceberg.R
Description: Estimate priors for proportion of infections that are asymptomatic/mild/unreported, a reported case, a reported death
Input: data/iceberg_data.csv
Output: results/prior_iceberg.RData
2. step1_analyze_sero_lassa.R
Description: Estimate the FOI for each administrative unit with serology data using a catalytic model.
Input: data/case_reports_Lassa_IGG.csv
Output: results/foi_from_sero_adm_X_revrateXX.RData
Command variables:
1. admin: 1 or 2
2. reversion rate: 0,3,6 (%)
3. step2_estimate_proportion_by_type_country_effects.R
Description: Estimate case and death reporting fractions for each country based on FOI estimates from step 1 and case/death data.
Input: data/case_reports_Lassa_CASES.csv
results/foi_from_sero_admX_revrateXX.RData
Output: results/proportion_by_type_admX_revrateXX_country_upd.RData
Command variables:
1. admin: 1 or 2
2. reversion rate: 0,3,6 (%)
4. step3_project_infections_by_country.R
Description: Estimate number of spillover infections for administrative units based on reporting fractions from step2.
Input: data/case_reports_Lassa_CASES.csv
results/proportion_by_type_admX_revrateXX_country_upd.RData
Output: results/projected_infections_admX_revrateXX_country_upd.RData
Command variables:
1. admin: 1 or 2
2. reversion rate: 0,3,6 (%)
5. step4_project_foi_by_country.R
Descripti …