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Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania

Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania

Auty, Harriet K., Picozzi, Kim, Malele, Imna, Torr, Steve J., Cleaveland, Sarah and Welburn, Sue (2012) Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania. PLoS Neglected Tropical Diseases, 6 (1). e1501. ISSN 1935-2735 (doi:10.1371/journal.pntd.0001501)

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Abstract

Background: Measuring the prevalence of transmissible Trypanosoma brucei rhodesiense in tsetse populations is essential for understanding transmission dynamics, assessing human disease risk and monitoring spatio-temporal trends and the impact of control interventions. Although an important epidemiological variable, identifying flies which carry transmissible infections is difficult, with challenges including low prevalence, presence of other trypanosome species in the same fly, and concurrent detection of immature non-transmissible infections. Diagnostic tests to measure the prevalence of T. b. rhodesiense in tsetse are applied and interpreted inconsistently, and discrepancies between studies suggest this value is not consistently estimated even to within an order of magnitude.

Methodology/Principal Findings: Three approaches were used to estimate the prevalence of transmissible Trypanosoma brucei s.l. and T. b. rhodesiense in Glossina swynnertoni and G. pallidipes in Serengeti National Park, Tanzania: (i) dissection/microscopy; (ii) PCR on infected tsetse midguts; and (iii) inference from a mathematical model. Using dissection/microscopy the prevalence of transmissible T. brucei s.l. was 0% (95% CI 0–0.085) for G. swynnertoni and 0% (0–0.18) G. pallidipes; using PCR the prevalence of transmissible T. b. rhodesiense was 0.010% (0–0.054) and 0.0089% (0–0.059) respectively, and by model inference 0.0064% and 0.00085% respectively.

Conclusions/Significance: The zero prevalence result by dissection/microscopy (likely really greater than zero given the results of other approaches) is not unusual by this technique, often ascribed to poor sensitivity. The application of additional techniques confirmed the very low prevalence of T. brucei suggesting the zero prevalence result was attributable to insufficient sample size (despite examination of 6000 tsetse). Given the prohibitively high sample sizes required to obtain meaningful results by dissection/microscopy, PCR-based approaches offer the current best option for assessing trypanosome prevalence in tsetse but inconsistencies in relating PCR results to transmissibility highlight the need for a consensus approach to generate meaningful and comparable data.

Item Type: Article
Additional Information: [1] Published on January 31, 2012. [2] ISSN 1935-2735 (Online). [3] Citation: Auty HK, Picozzi K, Malele I, Torr SJ, Cleaveland S, et al. (2012) Using Molecular Data for Epidemiological Inference: Assessing the Prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania. PLoS Negl Trop Dis 6(1): e1501. doi:10.1371/journal.pntd.0001501. [4] Copyright: (c) 2012 Auty et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords: sleeping sickness, human African trypanosomiasis, tsetse, Glossina, Trypanosoma brucei rhodesiense, Tanzania, Serengeti
Subjects: S Agriculture > S Agriculture (General)
S Agriculture > SF Animal culture
Faculty / Department / Research Group: Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute > Pest Behaviour Research Group
Related URLs:
Last Modified: 18 Nov 2016 11:17
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/7377

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