#Geodist radian stata free#

The results may have implications for health- and economic-risk management, especially for high-risk calves and calves that are transported long distances.įOREWORD Travelers' choices are central to the performance of a transportation system, but little is known about what influences such choices or the impact they have on system performance.

Several weather conditions on day P and during the first week after arrival were associated with incidence of BRDC mortality. Higher mean maximum temperature on day P increased the incidence of cumulative mortality among calves with low body weights (< 275.5 kg). Precipitation and wind speed on day P were associated with lower cumulative BRDC mortality incidence, but wind speed was associated only among calves transported long distances (≥ 1,082.4 km). Significant factors in the final model were weaning status degree of commingling body weight transport distance season precipitation, mean wind speed, and maximum environmental temperature on day P environmental temperature range in the first week after arrival at the feeding location and interactions between distance and wind speed and between body weight and maximum environmental temperature. To evaluate associations between weather conditions and management factors with the incidence of death attributable to bovine respiratory disease complex (BRDC) in high-risk auction-sourced beef calves.Ĭohorts (n = 3,339) of male beef calves (545,866) purchased by 1 large cattle feeding operation from 216 locations and transported to 1 of 89 feeding locations (backgrounding location or feedlot) with similar management protocols.Īssociations between weather conditions and management factors on the day of purchase (day P) and during the first week at the feeding location and cumulative BRDC mortality incidence within the first 60 days on feed were estimated in a mixed-effects negative binomial regression model. Future studies should consider building iterative models that utilize the strongest predictors identified in this study. Although high mortality purchase groups were not accurately predicted utilizing the models in this study, the models may potentially have utility as a screening tool for very low mortality purchase groups after arrival. The models performed well among purchase groups with low weekly mortality but performed poorly in high mortality purchase groups. The best predictors were maximum temperature and purchase weight, although this varied by week. The models had high accuracy (>90%), but the RMSE estimates were high (range = 1.0% to 4.1%). Models were evaluated by calculating the root mean squared error (RMSE) and accuracy (as defined as the percent of purchase groups that had predictions within 0.25% and 0.50% of actual mortality).

In this study, random forest models to predict weekly mortality for cattle purchase groups (n = 14,217 purchase groups 860,545 animals) from arrival at the feeding location (Day 1) to Day 42 and cumulative mortality from Day 43 until slaughter were built using records, weather, and transport data available at the time of purchase. To the best of our knowledge, there are no publications on predictive models for weekly all-cause mortality in feedlot cattle. Diagnosed patients should be promptly and carefully linked to a treatment unit for treatment initiation.įeedlot mortality negatively affects animal welfare and profitability.

#Geodist radian stata free#

PLTFU among TB patients remains a significant issue despite the availability of free anti-tuberculosis treatment in Cameroon. Travelling for >30 min to the DTU (aOR 2.19, 95%CI 1.56-3.09) and an urban location of DTU (aOR 2.51, 95%CI 1.51-4.17) were also significant risk factors for PLTFU. In the multivariable logistic regression model, travelling >30 km to the DTU was a risk factor for PLTFU (adjusted odds ratio 2.31, 95%CI 1.63-3.27) compared with travelling 30 km. PLTFU was defined as failure to initiate treatment within 7 days of diagnosis.Īmong 1174 bacteriologically confirmed PTB cases, the proportion of PLTFU was 16.7% (95%CI 14.7-18.9). To determine the proportion of pre-treatment loss to follow-up (PLTFU) of bacteriologically confirmed pulmonary tuberculosis (PTB) patients and its risk factors.Ī retrospective cohort study was conducted to retrieve information from the TB laboratory and treatment registers for all bacteriologically confirmed PTB patients diagnosed in the 39 DTUs during the last 6 months of 2015. Thirty-nine tuberculosis diagnosis and treatment units (DTUs) in the North-West and South-West Regions of Cameroon.