What do we have learned about mastitis spatial analysis during the last 30 years?

Amado Kent Ruiz Gil; Carlos Arturo AGUIRRE-SALADO; Osvaldo FONSECA-RODRÍGUEZ; Gilberto BALLESTEROS-RODEA; Luisa Eugenia del Socorro HERNÁNDEZ-ARTEAGA; Gregorio ÁLVAREZ-FUENTES

Amado Kent Ruiz Gil PhD Student UASLP, Mexico
Carlos Arturo AGUIRRE-SALADO UASLP https://orcid.org/0000-0003-3422-7193
Osvaldo FONSECA-RODRÍGUEZ Umea University https://orcid.org/0000-0002-0253-5928
Gilberto BALLESTEROS-RODEA UASLP https://orcid.org/0000-0001-5283-6975
Luisa Eugenia del Socorro HERNÁNDEZ-ARTEAGA UASLP https://orcid.org/0000-0002-1839-9852
Gregorio ÁLVAREZ-FUENTES UASLP https://orcid.org/0000-0001-8767-4232

Keywords: milk, somatic cell count, geographic information systems, cluster, review

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 databases of dairy production for each country may be a limiting factor for conducting spatial epidemiology research at both the national and local levels.