A new dimension of epidemiology
Division: Epidemiology | Locations: Worldwide
Dominating the terrain.
Geospatial epidemiology is the use of GIS techniques in epidemiological applications. Using spatial graph databases, geospatial agent based models and cutting edge techniques to analyse risk and disease propagation, plan emergency response and evaluate geospatial factors of health and disease.
Supported by a cutting edge team of GIS analysts, data specialists and engineers, the geospatial epidemiology team has unparalleled expertise in geospatial analytics and a track record of successful engagements for both public and private sector consumers.
- Geospatial propagation modelling
- Origin and propagation determination
- Monitoring strategy development in urban areas
- Cluster investigation
- High performance mapping services
- Biosecurity consulting for urban planning
- Service provision mapping and consulting
- Emergency service prioritisation
- Quarantine strategy development
- Expert witness services
- Military and defence
- Government and public sector
- Public health
- Healthcare providers
- Insurance providers
- Ambulance and rescue services
- Urban planning and construction
- Legal and litigation
- GIS experts
- GIS developers
- Healthcare GIS analysts
- Clinical service provision analysts
- Public health analysts
- Healthcare economists
- Support staff
- Urban planning specialists
- Preparedness specialists
Using cutting-edge techniques in spatial epidemiology and GIS, our analysts can investigate the geospatial patterns underlying phenomena of health and disease, from outbreaks to chronic illness.
Our experienced healthcare GIS analysts assist healthcare providers by identifying the best locations for healthcare facilities, reducing costs and increasing coverage. Through geospatial prioritisation, coverage can be reduced without increasing cost.
The CBRD Geospatial Epdiemiology Research Team (GERT) is constantly working on the development of actionable advances for faster, more efficient and more reliable computational methods for geospatial epidemiology.