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.