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Tytuł pozycji:

Modelling appropriate use of trypanocides to restrict wide-spread multi-drug resistance during chemotherapy of animal African trypanosomiasis.

Tytuł :
Modelling appropriate use of trypanocides to restrict wide-spread multi-drug resistance during chemotherapy of animal African trypanosomiasis.
Autorzy :
Wangwe II; Centre for Biotechnology and Bioinformatics, University of Nairobi, P.O. Box 30197, Nairobi, Kenya.; International Centre of Insect Physiology and Ecology, P.O. Box 30772, Nairobi, Kenya.
Wamwenje SA; Centre for Biotechnology and Bioinformatics, University of Nairobi, P.O. Box 30197, Nairobi, Kenya.; International Centre of Insect Physiology and Ecology, P.O. Box 30772, Nairobi, Kenya.
Mirieri C; Kiboko Zoological Investigations and Efficacy Trials Centre, P.O. Box 21, Kiboko, Makindu, Kenya.
Masila NM; Kenya Tsetse and Trypanosomiasis Eradication Council (KENTTEC), P.O. Box 106-80403, Kwale, Kenya.
Wambua L; International Centre of Insect Physiology and Ecology, P.O. Box 30772, Nairobi, Kenya.; School of Biological Sciences, University of Nairobi, P.O. Box 30197, Nairobi, Kenya.
Kulohoma BW; Centre for Biotechnology and Bioinformatics, University of Nairobi, P.O. Box 30197, Nairobi, Kenya.; International Centre of Insect Physiology and Ecology, P.O. Box 30772, Nairobi, Kenya.
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Źródło :
Parasitology [Parasitology] 2019 May; Vol. 146 (6), pp. 774-780. Date of Electronic Publication: 2018 Dec 20.
Typ publikacji :
Journal Article
Język :
English
Imprint Name(s) :
Original Publication: London, New York, Cambridge University Press.
Contributed Indexing :
Keywords: Mathematical models; multi-drug resistance; smallholder farmers; trypanocides; trypanosomes
Entry Date(s) :
Date Created: 20181221 Latest Revision: 20210916
Update Code :
20220302
DOI :
10.1017/S0031182018002093
PMID :
30567619
Czasopismo naukowe
Trypanocide resistance remains a huge challenge in the management of animal African trypanosomiasis. Paucity of data on the prevalence of multi-drug resistant trypanosomes has greatly hindered optimal veterinary management practices. We use mathematical model predictions to highlight appropriate drug regimens that impede trypanocide resistance development in cattle. We demonstrate that using drugs in decreasing resistance order results in a negligible increase in number of cattle with resistant infection, in contrast to a more pronounced increase from trypanocide use in increasing resistance order. We demonstrate that the lowest levels of trypanocide resistance are achieved with combination therapy. We also show that increasing the number of cattle treated leads to a progressive reduction in the number of cattle with drug resistant infections for treatments of up to 80% of the cattle population for the combination treatment strategy. Our findings provide an initial evidence-based framework on some essential practices that promote optimal use of the handful of trypanocides. We anticipate that our modest forecasts will improve therapeutic outcomes by appropriately informing on the best choice, and combination of drugs that minimize treatment failure rates.

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