Seasonality of Bovine Respiratory Disease (BRD) and Mitigation Techniques Used in Receiving Beef Cattle in the Last 10 Years: A Meta-analysis

Despite recent advances in technology, biological, nutritional, and pharmaceutical products designed to mitigate disease, bovine respiratory disease (BRD) remains the leading cause of feedlot morbidity and mortality. Thus, the objectives of this study were to 1) examine various mitigation techniques that have been reported in the literature within the United States for the previous decade, and 2) to investigate seasonality effects on BRD incidence and severity. A detailed literature search was conducted using Preferred Reporting Items for Systematic Reviews and Meta-analyses methods. A total of 103 records across 56 studies met criteria by providing percentages of cattle treated at least once for BRD and reporting a control. Available data (morbidity percentages, experimental treatments, sample size, location, season, and sex) were extracted from each study for control groups and treatment groups (metaphylactic, nutritional, drug application, appeasing substance). Logs risk ratio of both metrics (ai = controlBRD, bi = controlHealthy, ci = treatmentBRD, di = treatmentHealthy) was calculated for each record using the escalc function in the R package metafor (v4.8) in R (v4.5). A multi-level meta-analytical (MLMA) model was used to determine overall effects on BRD morbidity because data non-independence existed. The MLMA model resulted in a pooled estimate for log ratios of 0.0719 (P = 0.0917, 95% CI: -0.0117 – 0.1555) which revealed a tendency for BRD percentages to differ for control and treated groups of cattle. Results suggested that there was a significant presence of heterogeneity (Q = 336, P < 0.0001) demonstrating great variation among studies. Moderators were then added to the MLMA model to test study level characteristics that might explain this variation. The test for moderators reported that study location (P = 0.0147), treatment type (P = 0.0089), and sample size (P < 0.0001) all influenced overall BRD morbidity percentages, but sex did not (P = 0.6333). Additionally, this revealed season (P = 0.0253) affected overall morbidity with Spring resulting in the greatest BRD outbreaks (P = 0.0002). All log ratios reported from this analysis were less than 1.00 which indicated that treatment groups involved in each study did decrease morbidity percentages reported for BRD incidence compared to control groups, which is expected. The Egger’s regression test for funnel plot asymmetry was performed which revealed significant asymmetry (P = 0.0016, 95% CI: -0.2091 – 0.0484) which suggests there was evidence of publication bias. A file drawer analysis was performed using the random effects model to ensure the precision of the results generated which revealed a relatively small average effect size across all studies (0.1009) but did achieve significance (P = 0.0058). The meta-analysis conducted was a broad investigation that included a variety of factors that affect BRD outbreaks which produced evidence of seasonal and management trends.