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Factors influencing infections in Rhipicephalus appendiculatus ticks fed on cattle infected with Theileria parva

Published online by Cambridge University Press:  06 April 2009

A. S. Young
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
T. T. Dolan*
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
S. P. Morzaria
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
F. N. Mwakima
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
R. A. I. Norval
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
J. Scott
Affiliation:
International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya
A. Sherriff
Affiliation:
Department of Statistics and Modelling Science, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, Scotland, UK
G. Gettinby
Affiliation:
Department of Statistics and Modelling Science, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, Scotland, UK
*
Corresponding author: Tel: + 254 2 630743. Fax: + 254 2 631499. E-mail: ilri-kenya@cgnet.com.

Summary

A large database on the transmission of a stabilate of the Theileria parva Muguga stock from one breed of cattle using two stocks of Rhipicephalus appendiculatus, Muguga and Ol Pejeta was developed and analysed. Factors associated with the ticks and cattle, and the infections developing in cattle were studied in relation to the infection variables in the tick batches harvested daily from cattle. Generalized Linear Interactive Modelling (GLIM) was used to determine the importance of factors and interactions in influencing the levels of tick infection variables using Type I and Type III sums of squares analyses. Analysis of the 6 variables, prevalence (percentage of ticks infected), abundance (mean number of infected salivary gland acini per tick examined) and intensity (mean number of infected salivary gland acini per infected tick) in batches of 30 male and 30 female ticks showed that 24 covariates, factors or interactions had a significant effect (P> 0·05). Certain covariates and factors were particularly important for all 6 tick infection variables; parasitaemia of animal on the day of tick harvest, stabilate dilution administered to animal, month in which tick batch was harvested, minimum packed cell volume of animal over the sampling period, age of animal, and the minimum leukocyte count of the animal over the sampling period. The GLIM analyses were found to be a useful tool in identifying factors that influence infection levels and in devising methods of producing tick batches with more predictable infections.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1996

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