Predicting the Impact of Subnational Tailoring of Interventions in Guinea

Biostatistician, Data Scientist & Epidemiologist specializing in health data analytics, statistical modeling, large-scale data management, and clinical research.

Author

Ousmane Diallo, MPH-PhD

Period: 2020–2021
Role: Lead Modeler & Data Analyst

Context & Objective

Modeled malaria intervention scenarios to guide national planning and resource allocation in Guinea.

Methods & Tools

EMOD malaria model
R (data wrangling, visualization)
GIS risk mapping

Key Deliverables

Scenario models and reports for NMCP
Maps and decision briefs

Impact

Supported subnational targeting and resource allocation decisions.

Links:
- Code: to be added
- Report/Publication: to be added
- Contact: Email

Ousmane Diallo, MPH-PhD – Biostatistician, Data Scientist & Epidemiologist based in Chicago, Illinois, USA. Specializing in SAS programming, CDISC standards, and real-world evidence for clinical research.