Skip to main content
ARS Home » Pacific West Area » Hilo, Hawaii » Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center » Tropical Crop and Commodity Protection Research » Research » Publications at this Location » Publication #388973

Research Project: Development of New and Improved Surveillance, Detection, Control, and Management Technologies for Fruit Flies and Invasive Pests of Tropical and Subtropical Crops

Location: Tropical Crop and Commodity Protection Research

Title: Probability of insect capture in a trap network: Low prevalence and detection trapping with TrapGrid

item Manoukis, Nicholas
item HILL, M - Commonwealth Scientific And Industrial Research Organisation (CSIRO)

Submitted to: ArXiv
Publication Type: Pre-print Publication
Publication Acceptance Date: 10/24/2021
Publication Date: 10/24/2021
Citation: Manoukis, N., Hill, M.P. 2021. Probability of insect capture in a trap network: low prevalence and detection trapping with TrapGrid. ArXiv. 2110.11432.

Interpretive Summary: Here we describe an extension of a computer model used for measuring the effectiveness of trap networks targeting insect pests. The model is called "TrapGrid" and is freely available for download. The original version provides the average probability of insect capture over time for a given network of traps with a particular attraction per trap. A new mode, described here, allows the user to calculate the probability of one or more insect being captured over time. This new mode will be useful for situations of low insect pest prevalence, while the original is more helpful for comparing the sensitivity of surveillance networks.

Technical Abstract: Attractant-based trap networks targeting insects are ubiquitous worldwide. These networks have diverse targets, goals, and efficiencies, but all are constrained by practical considerations like cost and available lures. An important way to balance goals and constrains is through quantitative mathematical modeling. Here we describe an extension of a computer model of trapping networks known as "TrapGrid" to include an alternative mode of calculating the probability of capture over time in a trapping network: Strict detection ("capture of one or more") as compared with the average probability of capture as implemented in the original version. We suggest that this new calculation may be useful in situations of low prevalence where trap network operators wish to interpret the meaning of a single capture in a trap. The original remains preferred for comparing the sensitivity and suitability of alternate trap networks especially in surveillance scenarios (i.e. density of traps, their placement, lure attractiveness, etc).