A description of the demographic characteristics of the New Zealand non-commercial horse population with data collected using a generalised random-tessellation stratified sampling design

We conducted a cross-sectional survey to determine the demographic characteristics of non-commercial horses in New Zealand. A sampling frame of properties with non-commercial horses was derived from the national farms database, AgriBase™. Horse properties were stratified by property size and a generalised random-tessellated stratified (GRTS) sampling strategy was used to select properties (n = 2912) to take part in the survey. The GRTS sampling design allowed for the selection of properties that were spatially balanced relative to the distribution of horse properties throughout the country. The registered decision maker of the property, as identified in AgriBase™, was sent a questionnaire asking them to describe the demographic characteristics of horses on the property, including the number and reason for keeping horses, as well as information about other animals kept on the property and the proximity of boundary neighbours with horses. The response rate to the survey was 38% (1044/2912) and the response rate was not associated with property size or region. A total of 5322 horses were kept for recreation, competition, racing, breeding, stock work, or as pets. The reasons for keeping horses and the number and class of horses varied significantly between regions and by property size. Of the properties sampled, less than half kept horses that could have been registered with Equestrian Sports New Zealand or either of the racing codes. Of the respondents that reported knowing whether their neighbours had horses, 58.6% (455/776) of properties had at least one boundary neighbour that kept horses. The results of this study have important implications for New Zealand, which has an equine population that is naïve to many equine diseases considered endemic worldwide. The ability to identify, and apply accurate knowledge of the population at risk to infectious disease control strategies would lead to more effective strategies to control and prevent disease spread during an exotic, infectious disease outbreak, but could also highlight groups within the population that require targeted surveillance.