Probability models to facilitate a declaration of pest-free status, with special reference to tsetse (Diptera: Glossinidae)

Barclay, Hugh J.; Hargrove, John W.

doi:10.1079/ber2004331

Cited by 65 publications

(58 citation statements)

References 33 publications

(24 reference statements)

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“…From Eq. 3 above, P(0|k Barclay and Hargrove 2005). The use of (1 -r) in the calculations both simplifies the computations and also circumvents the necessity of determining the prior distribution, which is arbitrary unless there is some information about it.…”

Section: Probability Modelmentioning

confidence: 97%

“…So long as no individuals of a given species are being trapped, it is usually assumed that the species has not yet arrived. (ii) Following an eradication program, continued attempts to sample the species that give null results can be taken as evidence that the species has been eliminated from the trapping area (Barclay and Hargrove 2005). (iii) Determination of pest-free areas or areas of low pest prevalence; identifying such a status may facilitate the export of certain commodities.…”

Section: Introductionmentioning

confidence: 99%

“…Once these measures are known, probability estimates of existence of the pests can then be formulated from null results (as was done by Barclay and Hargrove (2005) to follow an eradication program). The area of attraction probably also depends on weather and other factors, but these are hard to predict and thus not explicitly considered here.…”

Section: Introductionmentioning

confidence: 99%

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Probability models to facilitate a declaration that an exotic insect species has not yet invaded an area

Barclay

Humble

2008

Biol Invasions

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A procedure is presented to facilitate a declaration that an area has not yet been invaded by a specific exotic insect pest following a trapping campaign to detect the pest species. For this we use a probability model to assess null trapping results and also a growth model to help verify that pests were not present at a given time in the past. The probability model is developed to calculate the probability of negative trapping results if in fact there were insects present, and then the hypothesis that insects are present can be rejected. The model depends on knowledge of the efficiency of the traps and also the area of attractiveness of the traps. If an incipient and undetected population does become established, then natural growth should eventually make it apparent. Using a growth model, the rate of increase of an insect population starting from one gravid female insect is calculated. For both the probability model and the growth model, the conclusion that no invaders were present relates to some period in the past, the lag being defined by the time interval during the trapping activity or the time taken for one fertilized female to produce a population detectable by trapping. If no insects are observed after a suitable waiting period, then a conclusion can be drawn that none were present. The methodology is applied to hypothetical insects with discrete or continuous reproduction.

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Section: Probability Modelmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Probability models to facilitate a declaration that an exotic insect species has not yet invaded an area

Barclay

Humble

2008

Biol Invasions

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“…In southern Senegal, T. congolense predominates (65 % of the infections) (Fall et al, 1993) and even in trypanotolerant breeds such as Ndama, AAT reduces significantly animal draught power and hematocrite (Seck et al, 2002). The parasitological survey complemented the entomological baseline data collection effort and aimed at the indirect detection of presence of tsetse (Barclay & Hargrove, 2005;Vreysen, 2005). As a result, in sites with a herd prevalence above 10 % and where the distance to the nearest tsetse fly captured was more than 10 km (e.g.…”

Section: Discussionmentioning

confidence: 99%

The prevalence of African animal trypanosomoses and tsetse presence in Western Senegal

Seck

Bouyer

Sall³

et al. 2010

Parasite

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(Mulligan, 1970) which is widespread in sub-Saharan Africa (Itard et al., 2003). AAT is Summary:In 2005, the Government of Senegal initiated a tsetse eradication campaign in the Niayes and La Petite Côte aiming at the removal of African Animal Trypanosomosis (AAT), which is one of the main constraints to the development of more effective cattle production systems. The target area has particular meteorological and ecological characteristics that provide great potential for animal production, but it is unfortunately still infested by the riverine tsetse species Glossina palpalis gambiensis Vanderplank (Diptera: Glossinidae). The tsetse project in Senegal has adopted an areawide integrated pest management (AW-IPM) approach that targets the entire tsetse population within a delimited area. During the first phase of the programme, a feasibility study was conducted that included the collection of entomological, veterinary, population genetics, environmental and socio-economic baseline data. This paper presents the parasitological and serological prevalence data of AAT in cattle residing inside and outside the tsetse-infested areas of the target zone prior to the control effort. At the herd level, a mean parasitological prevalence of 2.4 % was observed, whereas a serological prevalence of 28.7 %, 4.4 %, and 0.3 % was obtained for Trypanosoma vivax, T. congolense and T. brucei brucei, respectively. The observed infection risk was 3 times higher for T. congolense and T. vivax in the tsetse-infested than in the assumed tsetse-free areas. Moreover, AAT prevalence decreased significantly with distance from the nearest tsetse captured which indicated that cyclical transmission of the parasites by tsetse was predominant over mechanical transmission by numerous other biting flies present. The importance of these results for the development of a control strategy for the planned AW-IPM campaign is discussed.

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“…Even fairly high rates of dispersal would not yield high trap efficiency unless the daily linear dispersal rate was several km. Secondly, we used a default value of trap efficiency of 1%, and this was taken from Table 3 in the paper by Barclay and Hargrove (2005); this table gave relatively pessimistic estimates of trapping efficiency for tsetse using stationary traps. At any rate, our default value is only provided as an example to demonstrate the model; the value to be used in any model run is under the control of the user, and presumably any serious user will be cognisant of the dispersal rates characteristic of the target species as well as the efficiencies of the traps being used.…”

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confidence: 99%

Conclusions from a dynamic population model for tsetse: response to comments

Barclay¹,

Vreysen²

2011

Population Ecology

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The critique by Hargrove et al. (Popul Ecol, 2011) of our recently published paper on a tsetse population model (Barclay and Vreysen in Popul Ecol 53:89-110, 2011) has made some good points but has also misinterpreted the intent of some of our results as we presented them. Hargrove et al. rightly say that there is a mismatch between the size of the unit cells in the model (1 ha) and the iteration rate of the model (every 5 days), yielding too low a dispersal rate to simulate reality. However, they have misconstrued several of our results that we presented as examples to imply that those results were a necessary condition for control of tsetse, especially using traps and targets.Keywords Glossina Á Insecticidal cattle Á Integrated insect control Á SIT Á Traps Hargrove and his co-workers, Torr and Vale (Hargrove et al. 2011; hereafter called HTV) state that the model published by us (Barclay and Vreysen 2011) (BV) is full of problems so severe that it provides a misleading picture of the various options for tsetse control. While accepting that any model has its limitations, this statement is too broad and general for us to respond to effectively, so we will start out by saying that some of the criticisms are justified, while others are certainly not.The paper had just been published electronically when the senior author (HB) realized, after re-reading the paper by Williams et al. (1992), that the interaction of dispersal and the effectiveness of trapping was not treated properly in our model. This was aided by the unfortunate choice of a dispersal algorithm in which the rate of dispersal from one cell (hectare) to adjacent cells in the model was determined by the attractiveness of the recipient cells, and this was directly proportional to the equilibrium population levels in those cells. This resulted in equal numbers of insects being transferred back and forth between adjacent cells at equilibrium, so the effect on population levels and control efficiency was minimal. This limitation in the model could have been addressed if dispersal were to be based on something other than attractiveness, as the percentage of flies dispersing was limited by the upper limit imposed by highly clumped groups of cells. In addition, our 5-day iteration would also have to be changed to accommodate higher rates of dispersal. We have thus developed another version of the model in which the dispersal is a constant percentage (across all cells, and under user control) of those insects present in each cell and the iteration rate is now daily.Dr. Hargrove has kindly supplied us with mathematical formulations for temperature-dependent pupal developmental rate (and hence duration of the pupal stage), age at first larviposition, and inter-larval period, as well as temperature-independent mating probabilities of newly emerged males and females, all of which fit the published data better than do those originally used by us. The duration of the pupal stage would be important in the timing of This reply refers to the ''notes and comments'' at

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Probability models to facilitate a declaration of pest-free status, with special reference to tsetse (Diptera: Glossinidae)

Cited by 65 publications

References 33 publications

Probability models to facilitate a declaration that an exotic insect species has not yet invaded an area

Probability models to facilitate a declaration that an exotic insect species has not yet invaded an area

The prevalence of African animal trypanosomoses and tsetse presence in Western Senegal

Conclusions from a dynamic population model for tsetse: response to comments

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