Spatial and temporal distribution of incidence of acquired equine polyneuropathy in Norway and Sweden, 1995-2012.

Abstract

BackgroundAcquired equine polyneuropathy (AEP) is an emerging disease in horses in Sweden, Norway and Finland since 1995. Affected horses show bilateral pelvic limb knuckling and weakness, sometimes progressing to recumbency and euthanasia. The aetiology is unknown but is thought to be non-infectious and non-genetic, though possibly toxic or toxico-infectious. The objectives of this study were to describe the spatial, temporal and spatio-temporal features of AEP in Norway and Sweden for the period of 1995 to 2012. Data from all documented case farms (n = 136) were used. Space-time interaction clustering of case farms was investigated with a retrospective space-time scan statistic with a space-time permutation model, the space-time K-function and the Jacquez k nearest neighbour (kNN) test.ResultsThere was a clear seasonality in disease occurrence, as 123 case farms presented their first case from January to May. However, there was large variation in the number of case farms between years. Case farms were more numerous in certain regions. Despite the larger horse population in Sweden, 120 of the case farms were in Norway. Space-time clustering was supported by the K-function and partly by the space-time scan, but not by the Jacquez k nearest neighbour (kNN) test.ConclusionsThe results suggest an aetiology for AEP where the exposure is not consistent in time, but varies during and between years, assuming that the incubation period does not vary greatly. The results further suggest that the exposure varies between regions as well. Two out of three different analytical methods supported spatio-temporal clustering of case farms, which rendered inconclusive results. The negative result in the kNN test might be explained by lack of power, which is due to the small number of outbreaks in relation to the size of the study area and length of the study period, and further by the low to moderate power of methods to detect space-time clustering when the background population is unknown. Further research is needed to study how management, meteorological variables and other factors with local or regional differences may explain outbreaks of AEP.