Growth trends and potential for crop and livestock productivity
ANALYSIS OF EFFECTS OF TSETSE CONTROL ON LIVESTOCK PRODUCTIVITY AND HEALTH
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Transcript of ANALYSIS OF EFFECTS OF TSETSE CONTROL ON LIVESTOCK PRODUCTIVITY AND HEALTH
ANALYSIS OF EFFECTS OF TSETSE CONTROL ON LIVESTOCK
PRODUCTIVITY AND HEALTH
Nicholas N. Ndiwa, Woudyalew Mulatu and John Rowlands
International Livestock Research Institute
BACKGROUND• Trypanosomosis is a serious disease affecting livestock
in many parts of sub-Saharan Africa including Ethiopia.
• The parasite that causes the disease is carried by the tsetse fly.
• Persistently high levels of trypanosomosis found in cattle at Ghibe in southwest Ethiopia, where ILRI works, occur because of drug resistance.
• Thus, drug therapy on its own at Ghibe does not work.
• The alternative is to reduce the numbers of tsetse flies.
• Two interventions to control tsetse numbers have been implemented
1. - with insecticide impregnated targets 2. - with insecticide pour-on applied to the backs of cattle.
Time-line of treatments and tsetse control interventions
Drug treatments for disease cases
Targets
Invasion of third tsetse species
Drug treatment for
all cattle
Pour-on
Drug treatment for
all cattle
Theft of the targets
Mar
-86
Nov
-86
Jul-
87
Mar
-88
Nov
-88
Jul-
89
Mar
-90
Nov
-90
Jul-
91
Mar
-92
Nov
-92
Jul-
93
Mar
-94
Nov
-94
Jul-
95
Mar
-96
Nov
-96
Jul-
97
Mar
-98
Measurements were made monthly on the following:
Packed cell volume (PCV) Trypanosome prevalence Body weight
Calves were ear-tagged at birth and their details recorded.
Disposal (deaths, disappearance or sales) were also recorded.
Tsetse density
Mean body weight, PCV, trypanosome prevalence,
no. of treatments - separately for males and females
Calf growth rate and 12-month body weight
Mortality rate in males, females and calves
Abortion rate and calf/cow ratio to reflect fertility level
Herd size
Productivity and health variables calculated
Possible time units for analysis
One month? Problems? - handling seasonal variation
- handling increasing ages of cattle - handling pregnancy and lactation - positive serial correlations from month to month
- other confounding random variables (e.g rainfall)
Three months? Problems? - handling seasonal variation
- other confounding random variables - also age, pregnancy, lactation
Six months? - now possible to match with season (wet and dry)
- other factors not so important
Twelve months? - best for matching with agronomic (planting and harvesting) and livestock production / management - matches annual rain cycle
Data set structure
Statistical model
yijk=+si+pj+ck+(pc)jk+eijk
where s=season, p=period and c=control
Interaction not significant for any variable. Hence dropped for final model
estimate s.e. t(18) t pr.
Constant 217.24 5.53 39.28 <.001
SEASON 2 6.48 5.07 1.28 0.217
PERIOD 2 11.06 5.10 2.17 0.044
CONTROL 2 11.40 5.28 2.16 <.045
Change d.f. s.s. m.s. v.r. F pr.
+ SEASON 1 231.11 231.1 1.64 0.217
+ PERIOD 1 762.3 762.3 5.40 0.032
+ CONTROL 1 658.2 658.2 4.66 <.045
Residual 18 2543.3 141.3
Total 21 4194.8 199.8
Least square means
Control Body weight s.e.0 226.52 4.211 237.91 3.18
Genstat output for analysis of body weights for bulls
Accumulated analysis of variance
Estimates of parameters
Effect of tsetse control on selected variables
Variable Tsetse control without with SED P Change (%)
BullsBody weight (kg) 226.52 237.91 5.28 <0.001 8 PCV (%) 22.8 23.8 0.64 <0.01 7Trypanasome prevalence (%) 0.36 0.31 0.042 <0.05 24Annual mortality (%) 0.20 0.11 0.039 <0.001 62
CalvesGrowth rate – wet season (kg/month) 0.22 0.23 0.025 0. 4Body weight at 12 months (kg) 68 76 2.2 <0.01 12
Mean 6-month body weight - bulls
200
220
240
260
28087
-Mar
87-S
ep
88-M
ar
88-S
ep
89-M
ar
89-S
ep
90-M
ar
90-S
ep
91-M
ar
91-S
ep
92-M
ar
92-S
ep
93-M
ar
93-S
ep
94-M
ar
94-S
ep
95-M
ar
95-S
ep
96-M
ar
96-S
ep
97-M
ar
97-S
ep
Bod
y w
eigh
t (k
g)
Targets Pour-on
Mean packed cell volume and trypanosome prevalence - bulls
15
17
19
21
23
25
27
29
87-M
ar
87-S
ep
88-M
ar
88-S
ep
89-M
ar
89-S
ep
90-M
ar
90-S
ep
91-M
ar
91-S
ep
92-M
ar
92-S
ep
93-M
ar
93-S
ep
94-M
ar
94-S
ep
95-M
ar
95-S
ep
96-M
ar
96-S
ep
97-M
ar
97-S
ep
Pa
cke
d c
ell
volu
me
(%
)
0
0.1
0.2
0.3
0.4
0.5
0.6
Try
pa
no
som
e p
reva
len
ce
PCV Prevalence
Targets Pour-on
Body weight at 12 months - calves
40
60
80
100
120
87-M
ar
87-S
ep
88-M
ar
88-S
ep
89-M
ar
89-S
ep
90-M
ar
90-S
ep
91-M
ar
91-S
ep
92-M
ar
92-S
ep
93-M
ar
93-S
ep
94-M
ar
94-S
ep
95-M
ar
95-S
ep
96-M
ar
96-S
ep
97-M
ar
97-S
ep
Bo
dy
we
igh
t (kg
)
Body weight
Targets Pour-on
Wet season growth rate per month - calves
0
0.1
0.2
0.3
0.4
87-M
ar
87-S
ep
88-M
ar
88-S
ep
89-M
ar
89-S
ep
90-M
ar
90-S
ep
91-M
ar
91-S
ep
92-M
ar
92-S
ep
93-M
ar
93-S
ep
94-M
ar
94-S
ep
95-M
ar
95-S
ep
96-M
ar
96-S
ep
97-M
ar
97-S
ep
Bo
dy
we
igh
t (kg
)
Growth rate
Targets Pour-on
Conclusions
• The general health of cattle improved with increased body weights and reduced mortality.
• This corresponded to decreased trypanosome prevalence, although the average trypanosome prevalence still remained comparatively high.
• Insecticidal pour-on has an effect, not only on tsetse, but also on other nuisance flies. This may also have helped towards improved cattle health over this period.
• The analytical approach we adopted provided an analysis that simplified the difficulties in dealing with confounding factors and serial correlations between successive measurements.
Conclusions (continued)
• We lagged the effect of tsetse control by 6-months based on the knowledge that the intervention of tsetse control has a delayed effect. The data appeared to show this.
• Our method resulted in 13 observational units when tsetse control was applied and 9 when not; this was more than adequate for the statistical analysis.
• The length of the study demonstrated that application of tsetse control can be sustainable.