Skip to main content
    • Aa
    • Aa

Modelling the transmission dynamics of Echinococcus granulosus in dogs in rural Kazakhstan

  • P. R. TORGERSON (a1) (a2), B. S. SHAIKENOV (a3), A. T. RYSMUKHAMBETOVA (a3), A. E. USSENBAYEV (a4), A. M. ABDYBEKOVA (a5) and K. K. BURTISURNOV (a6)...

Cystic echinococcosis, caused by Echinococcus granulosus, is an emerging disease in many parts of the world and, in particular, in eastern Europe and the former Soviet Union. This paper examines the abundance of infection of E. granulosus in the definitive host in southern Kazakhstan. Observed data are fitted to a mathematical model in order to decide if the parasite population is partly regulated by definitive host immunity and to define parameters in the model. Such data would be useful to develop simulation models for the control of this disease. Maximum likelihood techniques were used to define the parameters and their confidence limits in the model and the negative binomial distribution was used to define the error variance in the observed data. The results indicated that there were 2 distinct populations of dogs in rural Kazakhstan which had significantly different exposures to E. granulosus. Farm dogs, which are closely associated with livestock husbandry, particularly sheep rearing, had a relatively high mean abundance of 631 parasites per dog and a prevalence rate of approximately 23%. The best fit to the model indicated that there was significant herd immunity in the dog at this infection pressure. In contrast, village dogs which were more likely to be kept as pets had a much lower mean abundance of parasites of only 27 parasites per dog and a lower prevalence of 5·8%. With this village population of dogs, the best fit indicated negligible herd immunity.

Corresponding author
Institute of Parasitology, University of Zürich, Winterthurerstrasse 266a, CH-8057, Zürich, Switzerland. Fax +41 1 63 58907. E-mail:
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0031-1820
  • EISSN: 1469-8161
  • URL: /core/journals/parasitology
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 14 *
Loading metrics...

Abstract views

Total abstract views: 95 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 22nd September 2017. This data will be updated every 24 hours.