Christopher Aidan Gilligan

The paper introduces OM-NPE, a Bayesian inference framework for heterogeneous epidemiological data, demonstrating its ability to recover parameters and uncertainties efficiently.

This study predicts the spread of cassava brown streak disease across sub-Saharan Africa using an epidemiological model informed by field data.

The paper estimates epidemiological parameters of banana bunchy top virus from small field experiments using a Bayesian framework, showing parameter estimates generalize across regions and identifying key transmission risks.

This study evaluates strategies to sustain banana production in areas affected by Banana Bunchy Top Disease by integrating clean seed programs, roguing, and farmer training.

This study evaluates BBTV dynamics in Benin using satellite data, field surveys, and modeling, identifying high-risk areas and effective control strategies.

This study identifies optimal crop clustering strategies to minimize pathogen invasion rates by analyzing dispersal kernels and agricultural landscapes.

The paper presents an analytical method to identify priority areas for refining spatial host data to improve epidemic prediction accuracy in cassava disease modeling.

This study evaluates varietal mixtures for managing cassava viral diseases using a web-based model, finding that mixtures benefit CBSD but not CMD, and highlights the need for integrated management strategies.