Comparison of the dynamic networks of four equine boarding and training facilities

"HerdGPS-Preprocessor"-A Tool to Preprocess Herd Animal GPS Data; Applied to Evaluate Contact Structures in Loose-Housing Horses

Sensors delivering information on the position of farm animals have been widely used in precision livestock farming. Global Positioning System (GPS) sensors are already known from applications in military, private and commercial environments, and their application in animal science is increasing. However, as trade-offs between sensor cost, battery life and sensor weight have to be made, GPS based studies scheduling long data collection periods and including a high number of animals, have to deal with problems like high hardware costs and data disruption during recharging of sensors. Furthermore, human-animal interaction due to sensor changing at the end of battery life interferes with the animal behaviour under analysis. The present study thus proposes a setting to deal with these challenges and offers the software tool "HerdGPS-Preprocessor", because collecting position data from multiple animals nonstop for several weeks produces a high amount of raw data which needs to be sorted, preprocessed and provided in a suitable format per animal and day. The software tool "HerdGPS-Preprocessor" additionally outputs contact lists to enable a straight analysis of animal contacts. The software tool was exemplarily deployed for one month of daily and continuous GPS data of 40 horses in a loose-housing boarding facility in northern Germany. Contact lists were used to generate separate networks for every hour, which are then analysed with regard to the network parameter density, diameter and clique structure. Differences depending on the day and the day time could be observed. More dense networks with more and larger cliques were determined in the hours prior to the opening of additional pasture.

Risk factors for duration of equine rhinitis A virus respiratory disease

BACKGROUND

Infectious respiratory disease is common in young horses and can impact athletic performance and long-term health. Significant variation in the duration of clinical disease has been observed, even in the absence of secondary complications. The determination of factors associated with disease chronicity may facilitate clinical decision-making and the development of improved biosecurity protocols.

OBJECTIVE

To investigate contact network characteristics, and demographic variables associated with time to clinical recovery from Equine Rhinitis A virus respiratory disease.

STUDY DESIGN

Prospective cohort study.

METHODS

Yearling Standardbred racehorses (n = 58) housed in a multi-barn training facility in Southern Ontario were included. Horses were monitored daily for clinical signs of acute respiratory disease over a 41-day period in Autumn 2017. Contact patterns between horses, including older racehorses, were determined through use of proximity loggers attached to halters during the initial 7-day of the study. Associations between duration of disease, demographic factors (birth month, gait, sex and yearling sale), serologic titres and network metrics (degree, betweenness and Eigenvector centrality) were investigated using a Cox proportional hazard model.

RESULTS

Yearling attack rate for infectious respiratory disease was 87.9% (n = 51). Median time to recovery was 6 days (IQR = 1-32) and 17 horses were censored due to early withdrawal or failure to recover during the study period. In those yearlings born February-May, birth month was significant in the Cox proportional hazard model (Hazard Ratio 0.7, 95% CI 0.49-1, P = 0.05).

MAIN LIMITATION

Probability of censoring was not independent of outcome which necessitated use of sensitivity analysis.

CONCLUSIONS

These findings suggest late born foals are less likely to recover quickly from infectious respiratory disease.

Equine Rhinitis A Virus Infection at a Standardbred Training Facility: Incidence, Clinical Signs, and Risk Factors for Clinical Disease

Respiratory disease is a common morbidity of young racehorses. Infections can lead to compromised welfare, and economic loss. Identification of risk factors for infection through clinical signs monitoring and collection of demographic, serologic, and contact network data can aid in the development of prevention and control strategies. The study objectives were to: (1) describe the transmission and clinical course of infectious respiratory disease in standardbred racehorses in a multi-barn training facility and, (2) identify demographic, serological, and contact network risk factors associated with Equine Rhinitis A virus (ERAV) respiratory disease. The study population included standardbred racehorses (age 1-5 years: n = 96) housed at a multi-barn training facility in southern Ontario. Clinical signs were monitored daily over a 41-day period in fall 2017. Descriptive statistics, including incidence rate, prevalence and incidence risk were calculated for the observed period. Associations between demographic, serologic, and contact pattern variables, and clinical disease status were investigated using multivariable logistic regression. Respiratory disease cases were characterized by mucopurulent discharge (100%), intermittent cough (37.7%), and ocular discharge (62.3%). Fever (>38.5°C) and inappetence were rarely reported (15.2 and 3.8%). Seroconversion to ERAV among cases was 75%. Total, and yearling-specific incidence risks were 52.5 and 87.9%. The cumulative incidence was 0.027 new cases/horse day. A negative association (OR = 0.011) between increasing age and respiratory disease was significant (p = < 0.001) in the final regression model. Yearling horses were at increased risk of infectious respiratory disease as demonstrated by the high yearling-specific incidence risk, and the negative association between age and infection. Disease control strategies, such as vaccination programs and isolation of new horses arriving from auction, should be targeted at young animals entering training facilities.

Comparing the effects of non-homogenous mixing patterns on epidemiological outcomes in equine populations: A mathematical modelling study

Disease transmission models often assume homogenous mixing. This assumption, however, has the potential to misrepresent the disease dynamics for populations in which contact patterns are non-random. A disease transmission model with an SEIR structure was used to compare the effect of weighted and unweighted empirical equine contact networks to weighted and unweighted theoretical networks generated using random mixing. Equine influenza was used as a case study. Incidence curves generated with the unweighted empirical networks were similar in epidemic duration (5-8 days) and peak incidence (30.8-46.4%). In contrast, the weighted empirical networks resulted in a more pronounced difference between the networks in terms of the epidemic duration (8-15 days) and the peak incidence (5-25%). The incidence curves for the empirical networks were bimodal, while the incidence curves for the theoretical networks were unimodal. The incorporation of vaccination and isolation in the model caused a decrease in the cumulative incidence for each network, however, this effect was only seen at high levels of vaccination and isolation for the complete network. This study highlights the importance of using empirical networks to describe contact patterns within populations that are unlikely to exhibit random mixing such as equine populations.