Epi

We collect and analyze health data to uncover patterns, detect outbreaks, and guide public health interventions—especially in underserved and high-risk populations. Our goal is to use epidemiological evidence to drive policy, protect communities, and prepare for emerging threats.

🔍 Our Core Epidemiological Work

1. Surveillance & Outbreak Detection

We support national and local surveillance systems in identifying trends in infectious diseases, antimicrobial resistance, and zoonotic spillover. By applying spatial and temporal analyses, we help detect outbreaks early and respond swiftly.

2. Vulnerability Mapping

We use data-driven models to identify populations most at risk due to geographic, socioeconomic, or health-related factors. This supports the equitable allocation of resources and targeted interventions.

3. Data for Decision-Making

Our epidemiological insights translate into dashboards, risk maps, and briefs that inform government agencies, hospitals, and global health partners.

4. Research & Policy Translation

We conduct record-based and field epidemiology studies that shape national AMR strategies, surgical infection prevention policies, and One Health preparedness efforts.

📊 Current & Past Studies

• Time Series Analysis of Measles Incidence in Nigeria Using Surveillance Data from 2011 to 2022
  A data-driven epidemiological study using SARIMA models to analyze and forecast measles incidence in Nigeria from 2011–2022, with predictions through 2026. 

• Genomic Characterization of Fecal Escherichia coli Isolates with Reduced Susceptibility to Beta‑Lactam Antimicrobials from Wild Hogs and Coyotes
  Surveillance study combining epidemiology and genomics to explore AMR strains in wildlife populations; includes population-level epidemiological insights.

• Beta‑Lactamase Resistance Genes in Enterobacteriaceae from Nigeria: A Systematic Review and Meta‑Analysis
  A comprehensive epidemiological synthesis of ESBL, AmpC, and carbapenemase gene prevalence across human, animal, and environmental samples in Nigeria.

Why These Matter for Our Epi Focus

• Rigorous data modeling (e.g., measles incidence forecasting) guides preparedness and vaccination policy.

• One Health surveillance integrates wildlife–environmental epidemiology with disease risk mapping.

• Meta-analysis approaches provide evidence-based insight into the spread of beta‑lactamase genes across sectors.