Mark Arnold

OverviewAI-generated summary

Mark Arnold's research focuses on the application of mathematical and computational modeling to public health issues, particularly in animal and veterinary health surveillance. His work has involved developing and analyzing models to understand disease dynamics, assess surveillance strategies, and inform policy decisions. He has investigated the distribution of prion infectivity in human tissues, contributing to the understanding of transmissible spongiform encephalopathies.

Arnold has applied Bayesian methods to attribute sources of Salmonella infections in human and animal populations in England and Wales. He has also utilized machine learning techniques to predict disease control outcomes, specifically in the context of bovine tuberculosis in England. His research extends to analyzing the effectiveness of diagnostic assays for prion diseases in sheep and reviewing the epidemic and risk factors associated with classical Bovine Spongiform Encephalopathy in Great Britain.

With a scholarly output reflected in an h-index of 28 and over 2,475 citations across 122 publications, Arnold's work demonstrates a significant contribution to the fields of veterinary epidemiology, disease modeling, and the application of advanced analytical techniques in public health. He has collaborated with researchers such as Robert E. Babcock at the University of Arkansas at Fayetteville.

Metrics

• h-index: 28
• Publications: 122
• Citations: 2,475