Tick and mosquito vectors of human pathogens are invading new habitats worldwide, likely driven by climate change. At the same time, climate change may also be driving the emergence of novel strains of these pathogens, some of which could infect humans more readily or cause more severe disease when a human is infected. Vector-borne pathogens are already a leading cause of morbidity and mortality worldwide, with risks increasing and becoming more unpredictable due to climate change. However, current climate modeling approaches of VBDs are not adequate to provide management-ready information about local transmission risks or pathogen evolution. Local surveillance for vector borne pathogens is therefore indispensable to public health. Our proposed research will investigate the capacity of the current range pathogen surveillance approaches across three US states to provide in-time data to public health practitioners about climate-change driven geographic expansion of vector-borne pathogens and the emergence of new pathogen strains. We will use a novel, interdisciplinary approach to answer these questions, pairing measures of local public health surveillance-systems capacity and estimates of vector-borne pathogen occurrence in three U.S. states with retrospective phylogenetic analysis of existing pathogen datasets. By comparing multiple vector-borne pathogens, we will create a pathogen-agnostic measure of local surveillance capacity and identify variation in capacity at the pathogen level. We will specifically compare variation between strain emergences detected by established surveillance mechanisms with phylogenetic estimates of strain emergence timing to measure the role of local surveillance approaches in capturing novel strains. We will also use phylogenetic methods to identify the probable lag in timing between a pathogen invading a new location and the time when it was first detected. Finally, we will also compare similar communities, with divergent disease surveillance systems, to describe variation in local-surveillance vector-borne disease estimates across similar settings with similar risks.