Icon Aquatic Animal Health

Epidemiology and Risk Modelling

The Epidemiology and Risk Modelling team has an established record in disease and risk modelling. Our ecologists have a broad range of expertise including pathway analysis, network modelling, scenario tree modelling, data analysis, GIS, outreach, risk profiling and analysis, and catchment modelling. Our work straddles the four Cefas Science Themes of the Cefas Science & Evidence Strategy (2019-2025), and as such we apply our skills to a wide range of project delivery including:

Risk Modelling and Pathway Analysis

We have specialist expertise in a range of risk modelling approaches, including pathway analysis to assess and quantify the risk associated with different routes diseases and non-native species introduction and spread, network modelling to forecast the spread of diseases and highlight marine connectivity, and scenario tree modelling to assess the efficiency of disease and non-indigenous species surveillance methods. We also undertake risk assessments relating to international trade in aquatic animals. We have developed broad tools that can be parameterised for application to multiple species, pathogens, or parasites.

This work regularly highlights gaps in our scientific understanding of pathogen transmission and species spread dynamics which we address through collaboration with other teams in Cefas.

GIS and Catchment Modelling

Geographic Information Systems (GIS) software (ArcGIS and qGIS) and spatial analysis packages in R are routinely applied by the team. Some example applications include site risk assessment for non-indigenous species introduction and spread, highlighting marine connectivity, and calculating site connectivity and distances via the river network. We develop tools using this software to assist in disease network modelling, develop risk ranking procedures for marine and freshwater sites, and facilitate disease outbreak rapid responses.

Data Analysis and Statistics

Our team use the statistical programming language R to analyse big datasets rapidly and reproducibly, employing git version control software to enhance traceability. We have expertise to advise on the use of statistics to answer research questions, and to execute proposed analyses. We regularly support collation and reporting of monitoring data on potentially invasive marine non-native species in England & Wales in support of Marine Strategy Framework Directive requirements. We are also able to assist with development of R packages.

 

team lead

Jessica Witt - Veterinary Epidemiologist

Email: jessica.witt@cefas.gov.uk