Ecological Niche Modelling
We use ecological niche modeling to predict a species' potential distribution by analyzing environmental conditions and species occurrence data. This approach is important for mapping disease risk, understanding pathogen spread, and guiding public health interventions.
Current Projects
Our geostatistical modeling projects focus on spatial analysis and risk mapping to support evidence-based public health interventions and resource allocation decisions.
Healthcare Accessibility to Rabies Post-Exposure Vaccines in Rural Kenya
Utilizing geostatistical modeling to map access barriers and optimize distribution of rabies post-exposure prophylaxis in rural communities, ensuring timely vaccination coverage in high-risk areas.
Key Research Areas:
- Rural healthcare accessibility mapping
- Vaccine distribution optimization
- Travel time and distance analysis
- Resource allocation strategies
Estimating Zero Dose Vaccination of Measles Containing Vaccine in Kenya
Advanced geostatistical analysis to identify areas with children who have received zero doses of measles-containing vaccines, supporting targeted immunization campaigns and equity improvements.
Key Research Areas:
- Zero dose children identification
- Vaccination coverage gaps analysis
- Targeted campaign planning
- Health equity assessment
Identifying Cholera Hotspots in Kenya
Comprehensive spatial risk modeling to identify cholera transmission hotspots across Kenya, integrating environmental, socioeconomic, and epidemiological data for prevention strategies.
Key Research Areas:
- Disease hotspot identification
- Environmental risk factor analysis
- Transmission pattern mapping
- Prevention strategy optimization
Identify Areas with the Highest Burden of Taeniasis in Kenya
Spatial analysis and geostatistical modeling to map the burden of taeniasis across different regions in Kenya, supporting targeted control interventions and resource planning.
Key Research Areas:
- Burden distribution mapping
- High-risk area identification
- Control intervention targeting
- Surveillance system optimization