Updated May 20, 2020

Tristan Ford

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VecTech is developing an AI-driven, low cost and high accuracy system for rapid image recognition of mosquitoes, enabling mosquito control to be targeted to areas of highest risk.

VecTech sprung from the VectorWEB project, low-cost network of cloud connected ovitraps for automated mosquito surveillance. Development of a novel low-cost, cloud connected system of smart ovitraps that will provide real-time mosquito surveillance data to health administrators, communities, and individuals. This proposed mosquito surveillance allows for outbreak modeling, targeted resource al...
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VecTech sprung from the VectorWEB project, low-cost network of cloud connected ovitraps for automated mosquito surveillance. Development of a novel low-cost, cloud connected system of smart ovitraps that will provide real-time mosquito surveillance data to health administrators, communities, and individuals. This proposed mosquito surveillance allows for outbreak modeling, targeted resource allocation/redirection, and community-driven interventions.
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Stage 3: Proof of Concept

VecTech has developed functional prototypes capable of classifying mosquitoes by species. We are completing lab validation of our prototypes and expanding image classification to include relevant species to target regions for field testing.

Focus Areas:

Infectious & Vector Diseases, Climate Change and Resilience, Data/Analytics and 2 MoreSEE ALL

Infectious & Vector Diseases, Climate Change and Resilience, Data/Analytics, Technology and AISEE LESS

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Key Partners
Verified Funding
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Problem

Mosquitoes kill nearly half a million people each year and cause disease and disability to hundreds of millions more. Targeted elimination of disease-carrying mosquito populations prevents disease, but requires precision control to optimize insecticide use and other biological control technologies specific to target species. Generating this data is slow, expensive, and requires a trained entomologist, often leading to improper control and misused resources.

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Solution

VecTech has developed an AI-driven computer vision system for identifying disease-carrying mosquito species. This technology is being integrated in devices designed to bring rapid high accuracy entomological identification at a low-cost to public health systems around the world. With VecTech's system, the training and labor burden of morphological identification is reduced, and vector surveillance programs are able to increase their capacity for rapid decision making that saves lives.

Target Beneficiaries

Thousands of mosquito control organizations around the world are responsible for protecting their citizens against the ongoing threat of vector-borne diseases. In the current system, field staff collect mosquito specimens from an area for identification by a trained entomologist. VecTech's system aims to scale high accuracy entomological identification to field staff with minimal training and at rates that meet or exceed those of a professional entomologist.

Mission and Vision

VecTech believes public health systems should have reliable data that empowers them to prevent disease. While our initial technology is focused on mosquito-borne diseases, our team is driven by an overall vision of precision public health so resources and interventions make the biggest impact, improve quality of life, and save lives.
Funding Goal500,000

The Team Behind the Innovation

EXECUTIVE TEAM INCLUDES WOMEN AND YOUTH

Milestone

Mar 2020
Key Partnership
Other
Nov 2019
Key Partnership
ORGANIZATIONMicrosoftMicrosoft
Dec 2018
Funds RaisedPENDING
TITLEGraduate Student Award
TYPEGrant
FOCUS AREAS
Health
Oct 2018
Funds RaisedPENDING
TITLEOutbreak Innovations Pitch Competition
TYPEGrant
FOCUS AREAS
Health