Light-baited suction traps are one of the most widely used tools for vector surveillance. Their popularity stems from ease of use even in remote locations, range and abundance of species caught, and low cost. The availability of smaller, portable models, like the CDC miniature light trap, have further increased their ubiquity in entomological field studies. However, when researchers have looked, light trap collections are usually biased in ways that may affect data interpretation for epidemiological studies. If used alone, light traps may fail to collect important or infected vectors, and light traps are inefficient or ineffective when competing ambient light is present. In this article, we discuss these biases and limitations in terms of their effect on collection efficiency, population data, and pathogen detection. While light trap data certainly have a purpose, an over-reliance on light trapping risks drawing false conclusions about vector populations and vector-borne disease epidemiology. These concerns are especially troubling when light trap data are used to inform policy decisions meant to protect human and animal health. Particularly when a species' response to light is unknown or poorly characterized, light traps should be used in conjunction with supplemental sampling methods. Researchers conducting vector surveillance field studies should carefully consider their study design and objectives when deciding on a trapping method or methods, and specifically endeavor to understand the limitations of their data. Only then can researchers take advantage of the best attributes of light traps while avoiding their dark side.
