Screwworm Tracker

Screwworm Tracker is a free field reporting tool that helps ranchers, veterinarians, and wildlife professionals document and report suspected New World Screwworm (NWS) cases directly from the field.

THE PROBLEM The New World Screwworm, eradicated from the US in 1982, is re-emerging at the US-Mexico border with over 161,000 animal cases in the current outbreak. During the 2016 Florida Keys outbreak, 84 days passed between the first field observation and laboratory confirmation. There is no public-facing digital tool for reporting suspect cases.

HOW IT WORKS PHOTOGRAPH - Guided photo capture helps you take diagnostically useful images of wounds and larvae ASSESS - Compare what you see to annotated reference images of screwworm vs. common blow fly species REPORT - If you suspect screwworm, the app generates a structured FAD investigation report with your photos, GPS location, and assessment DELIVER - Reports are automatically emailed to your state veterinarian's office with all information needed to initiate an investigation

KEY FEATURES Works offline: All core features function without cell service, essential for rural ranch environments Visual reference guide: Side-by-side comparisons of NWS larvae vs. common blow flies (C. macellaria, L. sericata, P. regina) with diagnostic markers highlighted Specimen collection guidance: Step-by-step USDA APHIS protocols for collecting and preserving larvae Emergency contacts: APHIS hotline, state veterinarian offices, NVSL specimen submission Observation map: See where reports are coming from across your region Self-assessment checklist: 5-question morphological triage based on established identification criteria

WHO IT'S FOR Cattle ranchers and livestock producers Large animal veterinarians Wildlife biologists and game wardens Extension agents Anyone who works with animals in screwworm-risk areas

This app supplements the existing APHIS reporting chain. It does not replace calling the APHIS emergency hotline (866-536-7593) for confirmed or highly suspect cases.

Built by a data engineer to close the detection gap between field observation and official response.