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numalariamodeling/hbhi-nigeria-publication-2021

Domain:

healthcare

Record type:

software
Creator:
num
Host:
Code and data for modeling analysis and shiny app associated with the manuscript titled 'Application of mathematical modeling to inform national malaria intervention planning in Nigeria' Application of Mathematical Modeling to Inform National Malaria Intervention Planning in Nigeria Table of Contents About The Project Summary Of The Modeling Framework Built With Getting Started With The Simulation Modeling Framework Prerequisites Seasonality Calibration Baseline Calibration Historical Simulations Future Projections Post processing IPTi IPTp Analyzers Contact Acknowledgements ## About the Project The Nigerian Malaria Elimination Program (NMEP) together with the World Health Organization developed a targeted response to intervention deployment at the local government-level to inform the development of the 2021-2025 National Malaria Strategic Plan, as part of the High Burden to High Impact response. The Northwestern University Malaria Modeling Team were recruited to create a mathematical modeling framework for predicting the impact of four NMEP proposed strategies on malaria morbidity and mortality in each of Nigeria's 774 local government areas (LGA). This repository contains scripts and data for replicating the LGA-level models described in the associated manuscript entitled "Application of mathematical modeling to inform national malaria intervention planning in Nigeria" and the modeling outputs also present in the manuscript and related R Shiny Application. ## Summary of the Modeling Framework A three-step process was used to generate LGA-level predictions of potential national strategic plans. At the outset, the goal was to capture the intrinsic potential of each LGA to support malaria transmission in a baseline period before 2010 when most interventions were not scaled up nationwide. Data and geospatial modeled surfaces from 2010 or before were used to group LGAs into epidemiological archetypes. For each archetype, baseline malaria transmission was calibrated to 2010 data. Next, Nigeria’s intervention history from 2010-20 at the LGA level was imposed on the baseline models to generate 774 LGA-level models up through 202 …

Visit

github.com

Tags

data-visualizationdistrictsmalaria-modelingnigeria

Licenses

Apache-2.0