An envisioned command-and-control (C2) dashboard for monitoring mosquito biothreats and optimizing their suppression using AI-based forecasts generated from a real-time sensor network and just-in-time genomic analyses deployed across Harris County, TX. The mock-up shown is a functional dashboard built in phase 1 that integrates existing data sets where available and synthetic data sets where data is unavailable – and incorporates human-centered design principles. The key requirements of the system and its C2 layer are as follows: (1) Biological situational awareness (bio-SA): a county-wide real-time map of: disease risks incorporating multi-modal biological and ecological data, overlays of countermeasure deployments, and overall health of sensor network with autonomous alerts to replan operations in real-time; (2) 24-hour forecasts and planning: forecasts of the spatial-temporal locations of disease transmitting mosquito species (i.e. vector species) one day in advance, and recommended optimal intervention plans including specific truck routes for precise deployment of insecticidal treatments; (3) Long term prediction and tracking: prediction of West Nile Virus (WNV) hotspots, emergence risk of insecticide resistance to plan future countermeasures, and efficient detection of invasive species. Diverse data layers must be fused to achieve these requirements. The map shows probabilistic temporal-spatial nowcast of biothreats built on top these data sets. This system enables optimal control and HCPH will measure the efficiencies gained to derive economically sustainable deployment blueprints. Based on phase 1 user studies, we anticipate per unit data costs will be reduced by at least an order of magnitude.