High mortality in a sheep flock caused by coinfection of louping ill virus and Anaplasma phagocytophilum

Presence of Anaplasma phagocytophilum Ecotype I in UK Ruminants and Associated Zoonotic Risk

Anaplasma phagocytophilum is the causative agent of tick-borne fever in sheep, pasture fever in cattle, and granulocytic anaplasmosis in humans. The increasing prevalence and transboundary spread of A. phagocytophilum in livestock, ticks, and wildlife in the UK poses a potential zoonotic risk that has yet to be estimated. Several ecotypes of A. phagocytophilum show variable zoonotic potential. To evaluate the possible risk associated with the transmission of A. phagocytophilum from ruminants to humans, the ecotype was determined by sequencing the groEL gene from 71 positive blood and tissue samples from UK ruminants. Thirty-four groEL sequences were obtained, fourteen of which were identified in multiple samples. Of the 13 nucleotide polymorphisms identified through pairwise comparison, all corresponded to synonymous substitutions. The subsequent phylogenetic estimation of the relationship with other European/world isolates indicated that all the groEL sequences clustered with other ecotype I sequences. The presence of ecotype I closely reflects that observed in ruminants in continental Europe and suggests a lower risk of zoonotic transmission from this reservoir.

Predicting the current and future risk of ticks on livestock farms in Britain using random forest models

The most abundant tick species in northern Europe, Ixodes ricinus, transmits a range of pathogens that cause disease in livestock. As I. ricinus distribution is influenced by climate, tick-borne disease risk is expected to change in the future. The aims of this work were to build a spatial model to predict current and future risk of ticks on livestock farms across Britain. Variables relating both to tick hazard and livestock exposure were included, to capture a niche which may be missed by broader scale models. A random forest machine learning model was used due to its ability to cope with correlated variables and interactions. Data on tick presence and absence on sheep and cattle farms was obtained from a retrospective questionnaire survey of 926 farmers. The ROC of the final model was 0.80. The model outputs matched observed patterns of tick distribution, with areas of highest tick risk in southwest and northwest England, Wales, and west Scotland. Overall, the probability of tick presence on livestock farms was predicted to increase by 5-7 % across Britain under future climate scenarios. The predicted increase is greater at higher altitudes and latitudes, further increasing the risk of tick-borne disease on farms in these areas.