This single-pathogen challenge model successfully yielded clinical signs and pathological effects consistent with naturally acquired respiratory disease. Routine laboratory variables and subjective measures were not reliable indicators of lung involvement or the progression of pneumonia. However, activity, objectively measured with pedometers and accelerometers, appeared to be a promising indicator for early recognition of bovine respiratory disease.

Abstract. Bovine respiratory disease continues to be the most important ailment of feed yard cattle. While the disease is multifactorial in nature, therapy continues to target the primary bacterial pathogens, Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni. A survey of records from a single diagnostic laboratory was conducted to evaluate the percentage of M. haemolytica isolates that were resistant to multiple antimicrobials and if coresistance patterns could be detected. All susceptibility test results for M. haemolytica recovered from lung tissues of cattle were eligible for inclusion in the survey. There were no isolates over the course of the analysis that were resistant to all 6 antimicrobials, primarily due to a lack of resistance to ceftiofur. In 2009, just over 5% of isolates were resistant to 5 or more antimicrobials (pan-resistant). In 2011, more than 35% of the M. haemolytica isolates were characterized as pan-resistant. Significant antimicrobial coresistance patterns were only seen with oxytetracycline and tilmicosin; bacterial isolates that were resistant to either oxytetracycline or tilmicosin were more likely to be resistant to at least one other antimicrobial. The mechanisms by which M. haemolytica is developing multidrug resistance warrant investigation if antimicrobial utility in the therapy of bovine respiratory disease is to be preserved.

This project investigates the macroepidemiological aspects of porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection by veterinary diagnostic laboratories (VDLs) for the period 2007 through 2018. Standardized submission data and PRRSV real-time reverse-transcriptase polymerase chain reaction (RT-qPCR) test results from porcine samples were retrieved from four VDLs representing 95% of all swine samples tested in NAHLN laboratories in the US. Anonymized data were retrieved and organized at the case level using SAS (SAS® Version 9.4, SAS® Institute, Inc., Cary, NC) with the use of PROC DATA, PROC MERGE, and PROC SQL scripts. The final aggregated and anonymized dataset comprised of 547,873 unique cases was uploaded to Power Business Intelligence—Power BI® (Microsoft Corporation, Redmond, Washington) to construct dynamic charts. The number of cases tested for PRRSV doubled from 2010 to 2018, with that increase mainly driven by samples typically used for monitoring purposes rather than diagnosis of disease. Apparent seasonal trends for the frequency of PRRSV detection were consistently observed with a higher percentage of positive cases occurring during fall or winter months and lower during summer months, perhaps due to increased testing associated with well-known seasonal occurrence of swine respiratory disease. PRRSV type 2, also known as North American genotype, accounted for 94.76% of all positive cases and was distributed across the US. PRRSV type 1, also known as European genotype, was geographically restricted and accounted for 2.15% of all positive cases. Co-detection of both strains accounted for 3.09% of the positive cases. Both oral fluid and processing fluid samples, had a rapid increase in the number of submissions soon after they were described in 2008 and 2017, respectively, suggesting rapid adoption of these specimens by the US swine industry for PRRSV monitoring in swine populations. As part of this project, a bio-informatics tool defined as Swine Disease Reporting System (SDRS) was developed. This tool has real-time capability to inform the US swine industry on the macroepidemiological aspects of PRRSV detection, and is easily adaptable for other analytes relevant to the swine industry.

We identified influenza C virus (ICV) in samples from US cattle with bovine respiratory disease through real-time PCR testing and sequencing. Bovine ICV isolates had high nucleotide identities (≈98%) with each other and were closely related to human ICV strains (≈95%). Further research is needed to determine bovine ICV’s zoonotic potential.

The potential distribution of Amblyomma americanum ticks in Kansas was modeled using maximum entropy (MaxEnt) approaches based on museum and field-collected species occurrence data. Various bioclimatic variables were used in the model as potentially influential factors affecting the A. americanum niche. Following reduction of dimensionality among predictor variables using principal components analysis, which revealed that the first two principal axes explain over 87% of the variance, the model indicated that suitable conditions for this medically important tick species cover a larger area in Kansas than currently believed. Soil moisture, temperature, and precipitation were highly correlated with the first two principal components and were influential factors in the A. americanum ecological niche. Assuming that the niche estimated in this study covers the occupied distribution, which needs to be further confirmed by systematic surveys, human exposure to this known disease vector may be considerably under-appreciated in the state.