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ANALYSIS OF EFFECTS OF TSETSE CONTROL ON LIVESTOCK PRODUCTIVITY AND HEALTH. Nicholas N. Ndiwa, Woudyalew Mulatu and John Rowlands International Livestock Research Institute. BACKGROUND.
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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.
Drug treatments for disease cases Time-line of treatments and tsetse control interventions Invasion of third tsetse species Drug treatment for all cattle Drug treatment for all cattle Jul-89 Jul-91 Jul-93 Jul-87 Jul-95 Jul-97 Mar-90 Mar-92 Mar-94 Mar-86 Mar-88 Mar-96 Mar-98 Nov-90 Nov-92 Nov-94 Nov-86 Nov-88 Nov-96 Targets Pour-on Theft of the targets
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.
Productivity and health variables calculated • 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
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
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
Genstat output for analysis of body weights for bulls Estimates of parameters 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 Accumulated analysis of variance 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 4.21 1 237.91 3.18
Variable Tsetse control without withSEDP Change (%) Bulls Body weight (kg) 226.52 237.91 5.28 <0.001 8 PCV (%) 22.8 23.8 0.64 <0.01 7 Trypanasome prevalence (%) 0.36 0.31 0.042 <0.05 24 Annual mortality (%) 0.20 0.11 0.039 <0.001 62 Calves Growth rate – wet season (kg/month) 0.22 0.23 0.025 0. 4 Body weight at 12 months (kg) 68 76 2.2 <0.01 12 Effect of tsetse control on selected variables
Targets Pour-on
Targets Pour-on
Targets Pour-on
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.