abstract

• Mastitis is the main disease in dairy farms worldwide. However, even after decades of research, mastitis is still a difficult disease to control, because multiple environmental, management and pathogen factors are involved. This review aims to analyze the most influential research works, in order to systematize the knowledge body on spatial analysis of mastitis. Our results indicate that the main techniques found for spatial data analysis of mastitis using udder health indicators like somatic cell count (SCC) and somatic cell score (SCS), are clustering, spatial correlation, and interpolation. We finally perceived that the lack of national data-bases of dairy production for each country may be a limiting factor for conducting spatial epidemiology research at both the national and local levels. © 2022, Massimo Morgante. All rights reserved.

authors

• Aguirre Salado Carlos Arturo
• Ballesteros Rodea Gilberto
• Álvarez Fuentes Gregorio

publication date

• 2022-01-01

published in

• Large Animal Review  Journal

keywords

• cluster; geographic information systems; Milk; review; somatic cell count

Digital Object Identifier (DOI)

PubMed ID

start page

• 153

end page

• 160

volume

• 28

issue

• 3