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There was no association between body weight and BCoV prevalence p=0.9, H. somni prevalence p=0.4, M. haemolytica prevalence p=0.2, or P. multocida prevalence p=0.6.
Of the epidemiological factors for which data was available, property of origin appeared to have the most significant association with both nasal and seroprevalence. When differences
in nasal prevalence between properties was taken into account, no significant differences were detected between animals from different states or of different sex, type Bos indicus vs
Bos taurus, class feeder, slaughter, breeder, or weight categories.
Co-mingling of cattle from multiple sources has been linked to an increased incidence of BRD in feedlot cattle.
65
Co-mingling is considered likely to be a source of stress and exposure of animals of unknown health status to a variety of viral and bacterial organisms.
Under Australian export conditions, the majority of animals on long-haul voyages are sourced directly from their property of origin to meet import protocol requirements. The first
opportunity for co-mingling in the export supply chain therefore occurs as animals arrive at the assembly depot. The wide range in nasal and sero-prevalence between properties does
support the hypothesis that there may be substantial opportunity for spread of pathogens from groups with higher prevalence to groups with lower prevalence once they are co-
mingled in the assembly depot. This is consistent with our findings see Section 8.3 of a rise in pathogen prevalence from first to second sampling in groups of animals that were
sampled twice at different time periods.
8.5 Seroprevalence
Serum samples were collected from 334 animals distributed across four cohort groups, all from one voyage.
Table 38 shows summary information on seroprevalence results by sampling cohort. Each row presents summary information from one cohort and displays a count of the number of
animals tested, the number and that tested positive prevalence and the 95 confidence interval for the prevalence.
65
Sanderson, Dargatz, and Wagner 2008; Taylor et al. 2010
Page 111 of 201 Table 38: Summary of seroprevalence results presented by virus and cohort group. Prevalence
presented as a percentage of the animals tested in each cohort and with 95 confidence intervals CI.
Prevalence 95 CI
Cohort No.
tested No. with
conclusive results
No. positive
of tested Lower
Upper n
n n
BoHV-1 8a
25 25
23 92.0
75.0 97.8
9 91
85 49
53.8 43.7
63.7 11
75 74
59 78.7
68.1 86.4
12a 143
140 14
9.8 5.9
15.8 Subtotal all
334 324
145 43.4
38.2 48.8
Subtotal new arrivals 309
299 122
39.5 34.2
45.0 BRSV
8a 25
25 25
100.0 86.7
100.0 9
91 90
34 37.4
28.1 47.6
11 75
75 10
13.3 7.4
22.8 12a
143 143
98 68.5
60.5 75.6
Subtotal all 334
333 167
50.0 38.2
48.8 Subtotal new arrivals
309 308
142 46.0
40.5 51.5
BVDV 8a
25 25
21 84.0
65.3 93.6
9 91
84 51
56.0 45.8
65.8 11
75 71
54 72.0
61.0 80.9
12a 143
142 67
46.9 38.9
55.0 Subtotal all
334 322
193 57.8
38.2 48.8
Subtotal new arrivals 309
297 172
55.7 50.1
61.1 BPIV-3
8a 25
24 24
96.0 80.5
99.3 9
91 91
72 79.1
69.7 86.2
11 75
75 59
78.7 68.1
86.4 12a
143 143
139 97.2
93.0 98.9
Subtotal all 334
333 294
88.0 38.2
48.8 Subtotal new arrivals
309 309
270 87.4
83.2 90.6
Cohort 8a represented animals that had been carried over in the assembly feedlot from the previous voyage preparation. There was interest in whether carry-over animals may have
increased opportunity to be exposed to circulating pathogens because of the additional time they spend in the feedlot. If this was the case then carry-over animals might be expected to
have a higher seroprevalence than animals that were entering the assembly feedlot for the first time.
Chi-squared tests were used to compare the prevalence in carry-over animals vs all other cohorts combined. Carry-over animals had a higher prevalence of BoHV-1 p0.001, BRSV
p0.001, and BVDV p0.001 but there was no difference in seroprevalence of BPIV-3 p=0.17.
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When individual animal seroprevalence status results were assessed, animals were more likely to be seropositive to multiple viruses based on testing of the same sample than to be
seropositive to a single virus and negative to all other viruses that were tested. These findings indicate that it is very common for multiple viruses to be circulating at the same time
and for animals to be exposed to multiple viruses at once.
Animals that were tested on arrival at the assembly depot for the first time avoiding carry over animals and that had both serological test results and nasal swab qPCR results
available from the same animals, were aggregated for comparison of serology and qPCR results Table 39.
Table 39: Summary results for those animals sampled on entry to assembly feedlot omitting carry over animals and tested by both serological test negative or positive and nasal swab.
Results presented as percentage of animals tested.
Serological and nasal shedding status Serostatus
negative negative
positive positive
Nasal swab status positive
negative positive
negative Virus
Percentage of animals with serum nasal results
BoHV-1 0.7
58.5 1.3
39.5 BRSV
53.9 46.1
BVDV 3.4
38.7 1
56.9 BPIV-3
2.6 10
0.6 86.7
Animals were most likely to be either negative on both serology and qPCR – indicating they
had not been previously exposed and were not shedding virus – or they were seropositive
and qPCR-negative indicating that they had been previously exposed and had developed an antibody response. Animals were believed to have not been vaccinated against respiratory
disease pathogens prior to being sampled.
A small percentage of animals were seropositive and qPCR positive which may be consistent with animals that had been previously exposed and were nasal carriers, or they
were seronegative and qPCR positive which may indicate animals that had either recently been exposed or were carriers.
Animals in the carry-over cohort had a higher percentage that were seronegative and qPCR- positive 3 from 25 or 12 which may reflect increased opportunity for exposure with
increased time in the feedlot.
9 Results - Retrospective data on voyage mortality
Retrospective data for sea voyages between January 1995 and December 2012 was obtained from the Shipboard Mortality Database SMDB. Between January 1995 and
December 2012, cattle were transported by sea from 29 ports in Australia to 124 ports in 30 countries around the globe. South East Asia accounted for the majority of exported cattle,
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followed by MENA and NE Asia. The number of cattle exported to each market varies each year Figure 9.
Table 40: Summary statistics for all voyages from Australia to all destinations between 1995- 2012, MENA=Middle East and North Africa, SE= south east, NE= north east, Misc =
miscellaneous.
Parameters Units
MENA SE Asia
NE Asia SE Europe Misc Total
Voyages N
1,028 4,909
395 14
101 6,447
Cattle loaded N
2,632,296 9,378,399
700,567 75,170
198,084 12,984,516
Mortality overall of cattle
loaded 0.44
0.09 0.12
0.28 0.46
0.17 Voyage mortality range
0-41.5 0-4.8
0-2.6 0-0.87
0-74.7 0-74.7
Average voyage duration days
17.5 6.6
17 28.8
18.6 9.2
Average discharge period days
3.8 0.9
1.3 3.6
1.4 1.4
Voyages with zero mortalities
N 293
2,533 118
1 31
2,976
Across all voyages the average mortality percentage number of cattle deadnumber of cattle loaded was 0.17. On 2,976 out of 6,447 voyages 46.2 there were no mortalities.
The percentage mortality reported for voyages to MENA provides a long-term estimate based on a similar destination group as the twenty voyages enrolled in this project and
described in more detail in Section 7.3. The overall percentage mortality reported in Table 40 for MENA 0.44 was higher than the percentage mortality reported for the twenty voyages
enrolled in this study 0.38.
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Figure 9 shows total numbers of cattle exported from Australia by year and destination region.
Figure 9: Total numbers of cattle exported from Australia by year and destination region between 1995 and 2012. Includes all data. Sourced from the Shipboard Mortality Database
SMDB.
Preliminary analyses of the SMDB data indicated that there were four voyages that had mortality percentages that were notably above the mortality percentages for all other
voyages. Brief descriptive information from these four voyages is presented here:
1998: 346 voyage deaths on a voyage to Jordan on the “MV Charolais Express”, as a result of a heat stress event and inadequate ventilation.
1999: 830 cattle suffocated when power loss caused ventilation failure on the “Temburong” in January 1999.
1999: 191 cattle died on the “Kalymnian Express” in December 1999. 2002: 127 cattle died on the “MV Becrux”, as a result of temperatures and humidity in the
Arabian Gulf. These voyages all had mortality investigations completed and were all described as being
special events associated with a combination of vessel mishaps ventilation breakdown and extreme weather conditions. The voyage mortality percentage for these four voyages was
more than two-fold and up to nine times higher than the next highest voyage mortality percentage estimates from the entire dataset. In the years in which these voyages occurred,
100 200
300 400
500 600
700 800
1994 1996
1998 2000
2002 2004
2006 2008
2010 2012
2014
N u
mb er
o f
ca tt
le loa
d ed
00 h
ea d
Year
MENA MISC
NE ASIA SE ASIA
SE EUROPE
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the mean mortality estimate and 95 confidence intervals were meaningfully different in appearance when these voyages were either included or removed. A decision was made to
remove these four voyages from the dataset for all subsequent modelling conducted in this section. The reason for this was because these voyages were extreme events and were not
considered likely to represent long term trends or overall population patterns which were important objectives for this section.
Once these four voyages were removed the dataset used for analyses included 6,443 voyages.
9.1 Mortality rate
