Citizen science as an approach for responding to the threat of anopheles stephensi in Africa

Even as novel technologies emerge and medicines advance, pathogen-transmitting mosquitoes pose a deadly and accelerating public health threat. Detecting and mitigating the spread of Anopheles stephensi in Africa is now critical to the fight against malaria, as this invasive mosquito poses urgent and...

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Detalles Bibliográficos
Autores: Carney, Ryan M., Long, Alex, Low, Russanne D., Zohdy, Sarah, Palmer, John R. B., Elias, Peter, Bartumeus, Frederic, Njoroge, Laban, Muniafu, Maina, Uelmen, Johnny A., Rahola, Nil, Chellappan, Sriram
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/59858
Acceso en línea:http://hdl.handle.net/10230/59858
http://dx.doi.org/10.5334/cstp.616
Access Level:acceso abierto
Palabra clave:Africa
Anopheles stephensi
Artificial intelligence
Citizen science
Malaria
Mosquito
Descripción
Sumario:Even as novel technologies emerge and medicines advance, pathogen-transmitting mosquitoes pose a deadly and accelerating public health threat. Detecting and mitigating the spread of Anopheles stephensi in Africa is now critical to the fight against malaria, as this invasive mosquito poses urgent and unprecedented risks to the continent. Unlike typical African vectors of malaria, An. stephensi breeds in both natural and artificial water reservoirs, and flourishes in urban environments. With An. stephensi beginning to take hold in heavily populated settings, citizen science surveillance supported by novel artificial intelligence (AI) technologies may offer impactful opportunities to guide public health decisions and community-based interventions. Coalitions like the Global Mosquito Alert Consortium (GMAC) and our freely available digital products can be incorporated into enhanced surveillance of An. stephensi and other vector-borne public health threats. By connecting local citizen science networks with global databases that are findable, accessible, interoperable, and reusable (FAIR), we are leveraging a powerful suite of tools and infrastructure for the early detection of, and rapid response to, (re)emerging vectors and diseases.