Perform statistical analyses to inform and generate surveillance protocols and recommendations for ornithodoros turicata americanus (OTA) in the event of an african swine fever (ASF) introduction

The Department of Agriculture Animal and Plant Health Inspection Service awarded a Cooperative Agreement valued at $124,999.93 to the University of Florida Division of Sponsored Research on December 5, 2025, under the Plant and Animal Disease, Pest Control, and Animal Care program (CFDA 10.025).

The award funds statistical analyses to develop surveillance protocols and standard operating procedures for Ornithodoros turicata americanus (OTA) ticks in Florida in preparation for a potential African Swine Fever (ASF) introduction. The work will generate field collection methodologies across Florida's ecoregions and translate existing field data and tick population models into implementable approaches to support ASF preparedness and mitigation strategies. If an ASF outbreak occurs, demonstrating whether ticks are involved will inform the timeline for the U.S. to reestablish disease freedom. Florida represents a high-risk region due to proximity to the Caribbean, backyard domestic farm production, heavy feral swine populations, and known vector presence.

Performance occurs in Florida with a period of performance extending through December 4, 2026. The recipient administers the award through its Division of Sponsored Research unit at the University of Florida.

In the event of an ASF outbreak, the ability to demonstrate whether or not ticks are involved in the outbreak will inform the timeline under which the U.S. Can reestablish disease freedom. This work will provide sops on where and how to collect OTA across the ecoregions of florida, a known high risk state due the proximity the caribbean, backyard domestic farm production, heavy feral swine population presence, and known presence of the vector. This work will leverage field data and tick population models generated from prior year agreements. Overall, this work will translate field data into implementable approaches to inform ASF preparedness and mitigations strategies.