Imisau/Family-Planning-Donor-Investment-Impact-Simulation

I develop a 10000 record donor investment simulation model across nine Nigeria states to evaluate cost, coverage, equity, system readiness, and political feasibility under multiple scale-up scenario, enabling evidence-based FP funding decisions # Family-Planning-Donor-Investment-Impact-Simulation # Project Overview This project applies **scenario-based analytics** to evaluate potential **Family Planning (FP) expansion strategies** across geographic units. Using simulated scale-up scenarios, the analysis assesses **trade-offs between cost, coverage, equity, and operational feasibility,** enabling donors and policymakers to make informed investment decisions. The Power BI dashboard translates complex programmatic data into **clear, donor-ready insights and visuals** that support strategic planning, prioritization, and resource allocation for FP scale-up. # Analytical Purpose Family Planning investments require balancing multiple, often competing objectives: • Expanding coverage efficiently • Ensuring equitable access across populations • Managing program costs • Maintaining operational feasibility within health systems This project addresses the need for a **decision-support tool** that allows stakeholders to **compare alternative FP expansion scenarios** and understand the implications of each option before committing resources. # Project Objectives - Simulate multiple FP expansion scenarios across regions - Quantify **cost, coverage, equity, and feasibility outcomes** for each scenario - Compare scenarios using standardized metrics - Highlight trade-offs and opportunity costs - Produce **donor-ready summaries and interactive visuals** to support scale-up decisions # Data Inputs (Simulated & Assumed) The analysis is based on simulated or modeled datasets typically used in FP planning, including: - Baseline FP service coverage - Target population estimates - Unit costs of FP service delivery - Health system and operational readiness indicators - Geographic and demographic attributes ⚠️ _Data used for this project is assumed to be aggregated, anonymized, and simulated for strategic planning rather than individual-level analysis._ # Data Processing & Transformation Using **Power Query, SQL, Python and E …