Development of resistance to sarcoptic mange in ibex

Sarcoptic mange affects mammal host species worldwide and, particularly, wild Caprinae throughout much of Eurasia. In the Iberian Peninsula, several outbreaks of sarcoptic mange in Iberian ibex (Capra pyrenaica) have been reported since the 1980s. Using data from a period of long‐term monitoring and a seasonal autoregressive integrated moving average (SARIMA)‐generalized autoregressive conditional heteroscedasticity (GARCH) model approach, we performed a time‐series analysis of the monthly prevalence of sarcoptic mange in the Iberian ibex population in Sierra Nevada Natural Space in southern Spain. In January 2003–March 2021, we documented a significant negative trend in sarcoptic mange prevalence, albeit with some interannual peaks. These findings can only be explained if a certain level of resistance to sarcoptic mange exists in hosts that, along with other factors, could provoke this reduced prevalence. Prevalence values varied seasonally, with maximum values in spring and minimum values at the end of summer, which may be due to factors linked to climate, host behavior, and endocrine activity. Our model predicts that the prevalence of sarcoptic mange in the Iberian ibex will continue to decrease over the next 2 years. Despite the inherent challenges involved, diagnosing and monitoring of wildlife diseases are integral to obtaining reliable epidemiological data and designing appropriate management strategies. In 2003–2021 an anlysis of the prevalence of sarcoptic mange in an Ibex population showed a significant decreasing and seasonal trend, which suggests that a degree of resistance to this parasitosis has developed in this host. We also predict a decrease in prevalence values over the following 2 years based on our models. Obtaining reliable data on wildlife disease prevalence and other epidemiological variables is pivotal for the appropriate management of such diseases and long‐term monitoring of these variables can help improve knowledge of how host‐parasite relationships influence the dynamics of diseases.