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High accuracy automated tick classification using computer vision

Award Number: R44AI162425
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/18/2022
PERIOD OF PERFORMANCE END DATE: 09/30/2026

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High accuracy automated tick classification using computer vision - Abstract. The incidence of US tick-borne diseases has more than doubled in the last two decades. Today, Lyme disease is the most common vector-borne disease in the United States, impacting over half-a-million Americans each year. Due to lack of effective vaccines for tick-borne diseases, prevention of tick bites and early tick bite treatment is the primary focus of disease mitigation. Tick vector surveillance—monitoring an area to understand tick species composition, abundance, and spatial distribution—is key to providing the public with accurate and up-to-date information when they are in areas of high risk, and enabling precision vector control when necessary. Despite the importance of vector surveillance, current practices are highly resource intensive and require significant labor and time to collect and identify vector specimens. Acarologist or field taxonomist expertise is a limited resource required for tick identification, creating a significant capability barrier for national tick surveillance practice. While mobile applications to facilitate passive surveillance and reporting of human-tick encounters have grown in popularity, variable image quality, limited engagement, and scientist misidentification of rare, invasive, or morphologically similar tick species hinder the scalability of this approach. To date, no automated solutions exist to build tick identification capacity. We seek to advance Phase I work that successfully achieved an imaging and automated identification system capable of instantaneously and accurately identifying twelve adult tick species with 98% accuracy. This proposal will first improve the Phase I optical design for scalability to accommodate imaging of additional intra-specific tick species variability as nymphs, adult males, and unfed or engorged adult females. In parallel, we develop methods to optimize quality of guided user imaging of ticks in a mobile app approach for the general public. This will enable the development of a representative image database with partners including TickSpotters, TickCheck, the Walter Reed Biosystems Unit (WRBU), and others. The resulting database will be used to train, validate, test and deploy high-accuracy computer vision models in two tick identification products for professional public health and the general public. Ultimately the approaches developed here will enable vector management organizations to leverage image recognition in a practical system that will increase capacity and capability for biosurveillance, and equip the general public with improved tools to identify ticks during a human-tick encounter.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $0 )
2026	2025	VECTECH, INC.	3600 CLIPPER MILL RD STE 401	BALTIMORE	MD	21211	BALTIMORE CITY	USA	Allergy and Infectious Diseases Research	000	4	4/27/2026	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $970,682 )
2025	2025	VECTECH, INC.	3600 CLIPPER MILL RD	BALTIMORE	MD	21211	BALTIMORE CITY	USA	Allergy and Infectious Diseases Research	000	4	4/16/2025	NON-COMPETING CONTINUATION	$970,682
														Subtotal = $970,682

Issue Date FY: 2024 ( Subtotal = $942,842 )
2024	2024	VECTECH, INC.	3600 CLIPPER MILL RD	BALTIMORE	MD	21211	BALTIMORE CITY	USA	Allergy and Infectious Diseases Research	000	3	3/28/2024	NON-COMPETING CONTINUATION	$942,842
														Subtotal = $942,842

Issue Date FY: 2023 ( Subtotal = $950,392 )
2023	2023	VECTECH, INC.	3600 CLIPPER MILL RD	BALTIMORE	MD	21211	BALTIMORE CITY	USA	Allergy and Infectious Diseases Research	000	2	4/27/2023	COMPETING CONTINUATION	$950,392
														Subtotal = $950,392

Grand Total All Awards = $2,863,916

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High accuracy automated tick classification using computer vision

Award Number: R44AI162425

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 04/18/2022

PERIOD OF PERFORMANCE END DATE: 09/30/2026

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