Description: The Bedbug Map Explorer (New York City at Building Level) displays all recently reported building infestations in New York City, covering the latest 8-week period—the timeframe needed for confirming eradication of an infestation. Zero-day reported infestations are represented by a bedbug icon. The opacity and color of each marker indicate the age of the report, while the marker size reflects the total number of infestations at that address since 2019. To identify infestation clusters, we employed DBSCAN (Density-Based Spatial Clustering Application with Noise), an unsupervised machine learning algorithm. This algorithm creates clusters based on the density of data points. Settings for DBSCAN include a 10-day window, an epsilon value of 0.5km, and a minimum of 12 samples. We utilized the ball tree algorithm with the Haversine distance metric.