Mohamed A. Yusuf, PhD

• Led development of an integrated pipeline combining polio surveillance (POLIS), conflict (ACLED), and humanitarian (DTM) data to support weekly and strategic decision-making. • Built an automated bulletin system for routine data cleaning, analysis, and visualization, used in 60+ weekly slide decks for 600+ stakeholders across country, regional, and global levels. • Created the poliprep R package to standardize workflows across WHO, supporting API integration, geoname cleaning, and automated reporting. • Co-developed the AgePopDenom R package with WorldPop to generate high-resolution, age-disaggregated population estimates from DHS and raster data. • Led a two-month WHO AFRO mission to Nigeria, coordinating a three-person team to deliver harmonized data structures, SOPs, and reproducible R pipelines designed for national ownership and sustainability. • Designed and applied a novel small-area estimation method combining GPS-tracked GTS data and GRID3 surfaces, generating ward-level coverage estimates to identify missed children and target campaigns. • Contributed analysis for the 2022 WPV1 outbreak closure in Malawi and Mozambique, integrating campaign, surveillance, and sequencing data. • Served as technical lead for the 2025 Madagascar cVDPV1 desk review, coordinating analytics and final outputs. • Supported scenario planning for the 2024–2026 Africa Polio Surveillance Action Plan and contributed to the 23rd IMB report. • Co-developed the tidypolis and sirfunctions packages with CDC to scale polio analytics across regions. • Built R capacity through regional and country training, mentoring, and rollout of standardized tools in country teams.

• Supported mortality estimation during the 2022–2023 Somalia drought with WHO, CDC, and UNICEF, informing humanitarian planning and resource allocation. • Built data pipelines integrating survey, displacement, climate, and service data to model monthly subnational mortality. • Applied DAG-based causal frameworks and ensemble approaches (incl. Bayesian networks) to improve robustness under sparse data conditions. • Developed tools for counterfactual scenario modeling (e.g. alternative rainfall or conflict patterns) to increase operational relevance of forecasts. • Co-authored reports and briefs translating model outputs into actionable insights for high-level coordination forums. • Contributed to reproducible R-based workflows and an R package for crisis mortality analysis and visualization. • Supported capacity building with national teams, strengthening analytical skills and promoting sustainable, country-led approaches.

• Supported the Global Malaria Program’s (GMP) Strategic Information for Response (SIR) team in delivering subnational tailoring and impact analyses for countries preparing Global Fund applications. • Cleaned, validated, and analyzed complex national malaria surveillance datasets from Pakistan and Congo, integrating routine data with contextual information to inform programmatic decision-making. • Produced country-specific analytical briefs and visualizations, contributing to strategic guidance on intervention prioritization and funding alignment. • Developed and maintained modular R code to support reproducible DHS-based analysis workflows, forming the basis for malaria stratification in the 2023 World Malaria Report and future technical support.