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Identification of the area sampled by traps: A modelling study with tsetse

Vale, Glyn A., Hargrove, John W. and Torr, Steve ORCID: (2023) 'Identification of the area sampled by traps: A modelling study with tsetse'. PLoS Neglected Tropical Diseases, Vol 17, Issue 1, e0010902.

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Sampling with traps provides the most common means of investigating the abundance, composition and condition of tsetse populations. It is thus important to know the size of the area from which the samples originate, but that topic is poorly understood.

Methods and principal findings
The topic was clarified with the aid of a simple deterministic model of the mobility, births and deaths of tsetse. The model assessed how the sampled area changed according to variations in the numbers, arrangement and catching efficiency of traps deployed for different periods in a large block of homogeneous habitat subject to different levels of fly mortality. The greatest impacts on the size of the sampled area are produced by the flies’ mean daily step length and the duration of trapping. There is little effect of trap type. The daily death rate of adult flies is unimportant unless tsetse control measures increase the mortality several times above the low natural rates.

Conclusions Formulae for predicting the probability that any given captured fly originated from various areas around the trap are produced. Using a mean daily step length (d) of 395m, typical of a savannah species of tsetse, any fly caught by a single trap in a 5-day trapping period could be regarded, with roughly 95% confidence, as originating from within a distance of 1.3km of the trap that is from an area of 5.3km2.

Item Type: Article
Subjects: QX Parasitology > QX 20 Research (General)
QX Parasitology > Insects. Other Parasites > QX 505 Diptera
QX Parasitology > Insects. Other Parasites > QX 600 Insect control. Tick control
Faculty: Department: Biological Sciences > Vector Biology Department
Digital Object Identifer (DOI):
SWORD Depositor: JISC Pubrouter
Depositing User: JISC Pubrouter
Date Deposited: 21 Feb 2023 15:57
Last Modified: 21 Feb 2023 15:57


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