Nathalia de Bem Bidone, Grazziane Maciel Rigon, Priscila Teixeira Ferreira, Ana Luiza Loch, Fernando Groff, Rovaina Laureano Doyle, José Reck, Guilherme Marcondes Klafke
Acaricide resistance in Rhipicephalus microplus represents a major constraint to sustainable cattle production in tropical and subtropical regions, yet official veterinary services often lack structured tools to integrate laboratory diagnostics with spatial information for decision-making. This study describes the development of a georeferenced monitoring dashboard for acaricide resistance using Rio Grande do Sul as a pilot model. Laboratory diagnostic data generated by the official State Veterinary Diagnostic Laboratory between 2023 and 2025 were compiled into a structured database linked to georeferenced cattle farm information. Data from a statewide resistance survey conducted in 2023 were incorporated as the baseline dataset, while subsequent results from 2024 and 2025 were derived mainly from routine passive diagnostic submissions. Resistance to major acaricide classes was categorized using a standardized four-level classification system, and a Multiresistance Index (MRAi) was calculated to summarize multidrug resistance at the farm level. The dataset included 468 georeferenced diagnostic records. High levels of multiresistance were widespread throughout the study period, with median MRAi values consistently above 2.0 and 44.6% of diagnostic records classified as presenting high multiple resistance (MRAi ≥2.5). Synthetic pyrethroids, fipronil, ivermectin, and fluazuron showed the highest proportions of moderate to high resistance. The interactive dashboard enables regularly updated visualization of resistance patterns across space and time, identification of areas with high multiple resistance, and prioritization of monitoring and extension activities. By transforming routine laboratory diagnostics into actionable, spatially explicit intelligence, this monitoring platform represents a significant step toward operational surveillance of acaricide resistance and provides a scalable model for adoption by official veterinary services and coordinated resistance management programs.