Descriptive network analysis and the influence of timescale on centrality and cohesion metrics from a system of between-herd dairy cow movements in Ontario, Canada.

Previous research has demonstrated that static monthly networks of between-herd dairy cow movements in Ontario, Canada were highly fragmented, reducing potential for large-scale outbreaks. Extrapolating results from static networks can become problematic for diseases with an incubation period that exceeds the timescale of the network. The objectives of this research were to: 1) describe the networks of dairy cow movements in Ontario, and 2) describe the changes that occur among network analysis metrics when conducted at seven different timescales. Networks of dairy cow movements were created using Lactanet Canada milk recording data collected in Ontario between 2009 and 2018. Centrality and cohesion metrics were calculated after aggregating the data at seven timescales: weekly, monthly, semi-annual, annual, biennial, quinquennial, and decennial. There were 50,598 individual cows moved between Lactanet-enrolled farms, representing approximately 75% of provincially registered dairy herds. Most movements occurred over short distances (median = 39.18 km), with fewer long-range movements (maximum = 1150.80 km). The number of arcs increased marginally relative to the number of nodes with longer network timescales. Both mean out-degree, and mean clustering coefficients increased disproportionately with increasing timescale. Conversely, mean network density decreased with increasing timescale. The largest weak and strong components at the monthly timescale were small relative to the full network (267 and 4 nodes), whereas yearly networks had much higher values (2213 and 111 nodes). Higher relative connectivity in networks with longer timescales suggests pathogens with long incubation periods and animals with subclinical infection present increased potential for wide-spread disease transmission among dairy farms in Ontario. Careful consideration of disease-specific dynamics should be made when using static networks to model disease transmission among dairy cow populations.

Variability in Risk Assessment and Management Plan (RAMP) scores completed as part of the Ontario Johne's Education and Management Assistance Program(2010-2013).

As a proactive measure toward controlling the nontreatable and contagious Johne's disease in cattle, the Ontario dairy industry launched the voluntary Ontario Johne's Education and Management Assistance Program in 2010. The objective of this study was to describe the results of the first 4 yr of the program and to investigate the variability in Risk Assessment and Management Plan (RAMP) scores associated with the county, veterinary clinic, and veterinarian. Of 4,158 Ontario dairy farms, 2,153 (51.8%) participated in the program between January 2010 and August 2013. For this study, RAMP scores and whole-herd milk or serum ELISA results were available from 2,103 farms. Herd-level ELISA-positive prevalence (herds with one or more test-positive cows were considered positive) was 27.2%. Linear mixed model analysis revealed that the greatest RAMP score variability was at the veterinarian level (24.2%), with relatively little variability at the county and veterinary clinic levels. Consequently, the annual RAMP should be done by the same veterinarian to avoid misleading or discouraging results.