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Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes

SIMPLE SUMMARY: The mosquito is the deadliest animal on earth, transmitting diseases that cause nearly a million deaths and >700 million infections each year. Yet only relatively few mosquito species are “vectors” that transmit diseases. Unfortunately, identifying these vector species is a diffic...

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Autores principales: Carney, Ryan M., Mapes, Connor, Low, Russanne D., Long, Alex, Bowser, Anne, Durieux, David, Rivera, Karlene, Dekramanjian, Berj, Bartumeus, Frederic, Guerrero, Daniel, Seltzer, Carrie E., Azam, Farhat, Chellappan, Sriram, Palmer, John R. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9409379/
https://www.ncbi.nlm.nih.gov/pubmed/36005301
http://dx.doi.org/10.3390/insects13080675
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author Carney, Ryan M.
Mapes, Connor
Low, Russanne D.
Long, Alex
Bowser, Anne
Durieux, David
Rivera, Karlene
Dekramanjian, Berj
Bartumeus, Frederic
Guerrero, Daniel
Seltzer, Carrie E.
Azam, Farhat
Chellappan, Sriram
Palmer, John R. B.
author_facet Carney, Ryan M.
Mapes, Connor
Low, Russanne D.
Long, Alex
Bowser, Anne
Durieux, David
Rivera, Karlene
Dekramanjian, Berj
Bartumeus, Frederic
Guerrero, Daniel
Seltzer, Carrie E.
Azam, Farhat
Chellappan, Sriram
Palmer, John R. B.
author_sort Carney, Ryan M.
collection PubMed
description SIMPLE SUMMARY: The mosquito is the deadliest animal on earth, transmitting diseases that cause nearly a million deaths and >700 million infections each year. Yet only relatively few mosquito species are “vectors” that transmit diseases. Unfortunately, identifying these vector species is a difficult and time-consuming manual process. A promising and scalable solution involves “citizen science”, whereby the general public provides images of mosquito specimens and breeding habitats using smartphones. However, data from such previous efforts have lacked the necessary integration for a thorough and global understanding of mosquito presence. Here, we standardize and combine data from multiple international citizen science apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to aid researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we used citizen science imagery to develop artificial intelligence software to automatically identify the species and anatomical regions of mosquitoes. Ultimately, we establish a new surveillance system to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide. ABSTRACT: Mosquito-borne diseases continue to ravage humankind with >700 million infections and nearly one million deaths every year. Yet only a small percentage of the >3500 mosquito species transmit diseases, necessitating both extensive surveillance and precise identification. Unfortunately, such efforts are costly, time-consuming, and require entomological expertise. As envisioned by the Global Mosquito Alert Consortium, citizen science can provide a scalable solution. However, disparate data standards across existing platforms have thus far precluded truly global integration. Here, utilizing Open Geospatial Consortium standards, we harmonized four data streams from three established mobile apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to facilitate interoperability and utility for researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we leveraged pooled image data to develop a toolset of artificial intelligence algorithms for future deployment in taxonomic and anatomical identification. Ultimately, by harnessing the combined powers of citizen science and artificial intelligence, we establish a next-generation surveillance framework to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide.
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spelling pubmed-94093792022-08-26 Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes Carney, Ryan M. Mapes, Connor Low, Russanne D. Long, Alex Bowser, Anne Durieux, David Rivera, Karlene Dekramanjian, Berj Bartumeus, Frederic Guerrero, Daniel Seltzer, Carrie E. Azam, Farhat Chellappan, Sriram Palmer, John R. B. Insects Article SIMPLE SUMMARY: The mosquito is the deadliest animal on earth, transmitting diseases that cause nearly a million deaths and >700 million infections each year. Yet only relatively few mosquito species are “vectors” that transmit diseases. Unfortunately, identifying these vector species is a difficult and time-consuming manual process. A promising and scalable solution involves “citizen science”, whereby the general public provides images of mosquito specimens and breeding habitats using smartphones. However, data from such previous efforts have lacked the necessary integration for a thorough and global understanding of mosquito presence. Here, we standardize and combine data from multiple international citizen science apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to aid researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we used citizen science imagery to develop artificial intelligence software to automatically identify the species and anatomical regions of mosquitoes. Ultimately, we establish a new surveillance system to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide. ABSTRACT: Mosquito-borne diseases continue to ravage humankind with >700 million infections and nearly one million deaths every year. Yet only a small percentage of the >3500 mosquito species transmit diseases, necessitating both extensive surveillance and precise identification. Unfortunately, such efforts are costly, time-consuming, and require entomological expertise. As envisioned by the Global Mosquito Alert Consortium, citizen science can provide a scalable solution. However, disparate data standards across existing platforms have thus far precluded truly global integration. Here, utilizing Open Geospatial Consortium standards, we harmonized four data streams from three established mobile apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to facilitate interoperability and utility for researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we leveraged pooled image data to develop a toolset of artificial intelligence algorithms for future deployment in taxonomic and anatomical identification. Ultimately, by harnessing the combined powers of citizen science and artificial intelligence, we establish a next-generation surveillance framework to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide. MDPI 2022-07-27 /pmc/articles/PMC9409379/ /pubmed/36005301 http://dx.doi.org/10.3390/insects13080675 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Carney, Ryan M.
Mapes, Connor
Low, Russanne D.
Long, Alex
Bowser, Anne
Durieux, David
Rivera, Karlene
Dekramanjian, Berj
Bartumeus, Frederic
Guerrero, Daniel
Seltzer, Carrie E.
Azam, Farhat
Chellappan, Sriram
Palmer, John R. B.
Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title_full Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title_fullStr Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title_full_unstemmed Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title_short Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes
title_sort integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9409379/
https://www.ncbi.nlm.nih.gov/pubmed/36005301
http://dx.doi.org/10.3390/insects13080675
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