Determining mechanisms to quantify the spread and severity of diseases afflicting wildlife populations is important for disease ecology, animal ecology, and conservation. Giraffes (Giraffa camelopardalis), for example, are in the midst of a dramatic decline referred to as the “silent extinction”. It is presently unknown whether disease may be playing an important role in the broad scale population reductions observed. In 1995, a skin disorder referred to as giraffe skin disease (GSD) was recorded in one giraffe population in Uganda. Since then, GSD has been detected in 13 populations in seven African countries and robust descriptions of the severity of this disease are presently unknown. Here, we photogrammetrically analyzed camera-trap images from both Ruaha and Serengeti National Parks in Tanzania to quantify GSD severity. As GSD afflicts the limbs of giraffes in Tanzania, we quantified severity by measuring the vertical length of the GSD affliction in relation to the total leg length. Applying the Jenks Natural Breaks algorithm to the proportions deriving from this technique, we classified individual giraffes into disease categories (none, mild, moderate, and severe). Scaling up to the population-level, we predicted the proportion of the Ruaha and Serengeti giraffe populations with mild, moderate, and severe GSD. This study serves to demonstrate that camera traps present an informative platform for examinations of skin disease ecology. We demonstrate that our analytical framework is not species-specific and we discuss the ways in which camera trap data could be used to study skin diseases across a wide range of wildlife species.
