Bovine cysticercosis is a zoonotic foodborne disease caused by Taenia saginata involving cattle as the intermediate host and humans as the final host. Humans are infected by eating raw or undercooked meat of infected cattle. Cattle are infected after grazing on pasture infected by human feces. Disease detection in cattle is performed during post-mortem meat inspection at the slaughterhouse through the identification of cysts in muscle tissue. Cysts develop from a viable stage to a degenerated stage in one to nine months, both stages being visible and distinguishable in cattle muscle. Due to the slow development of cysts and the complexity of cattle movements (up to ten different herds from birth to slaughter in France), there is a strong bias to consider the last farm location before slaughter as the location of infection.
Objective
Spatial analysis of infectious diseases enables identification of areas at high risk for infection, a useful tool for implementation of risk-based surveillance. For chronic diseases, the period between infection and detection can be long and when animal movements are important, identifying the place of infection is difficult. The objective of this study is to propose an innovative approach for spatial analysis that takes into account uncertainty regarding the location where animals were infected. An animal-herd-level weighted analysis was used and applied to bovine cysticercosis in France.