Methodology for Sampling Questing Nymphs ofIxodes Ricinus(Acari: Ixodidae), the Principal Vector of Lyme Disease in Europe

Autor: Bruno Pichon, Marie Vassallo, Jacques Cabaret, Claude Figureau, Claudine Perez-Eid
Rok vydání: 2000
Předmět:
Zdroj: Journal of Medical Entomology. 37:335-339
ISSN: 1938-2928
0022-2585
Popis: To assess the Lyme borreliosis vector population density we set up a methodology for sampling the Ixodes ricinus L. population host questing on the vegetation. We focused on the collection of the nymphal stage, which is the principal stage of disease transmission to humans. This study was carried out in Rambouillet forest (Yvelines, France) where seven study areas were demarcated. These areas are maximally homogeneous for plant species using a finer scale than the phytosociological classification as defined by the method of landscape diagnostics. Out of 23 collections performed from March 1997 to May 1998, 2,906 I. ricinus nymphs were collected. The sampling technique chosen was the cloth lure technique. The technical parameters were studied and fixed (cloth type, cloth size, sample size, researcher position). It appeared that toweling was the best cloth type to optimize the number of ticks collected; the position of the researcher had no effect on tick samples. To satisfy the criteria for correct sampling, we studied representativity, randomness, and nonselectivity of our methodology. The spatial distribution of nymphs in a homogeneous area was close to random and thus very few subsamples were needed to obtain a relative density which was representative. No significant differences were found between random samples and following transect samples; and nonselectivity was totally satisfied because we only worked on questing nymphs. We grouped the samples that presented no significant differences to attribute a density index, which varied from 0 to 5. This methodology, applied with the same parameters, offers potential for producing comparable results from studies in different geographical areas and at different times of the years.
Databáze: OpenAIRE