| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 4.51 MB | Adobe PDF |
Advisor(s)
Abstract(s)
No âmbito da Rede de Vigilância de Vetores (REVIVE ), é realizada a vigilância
entomológica em mosquitos desde 2008 em Portugal. O projeto
REVIVE é uma componente dos programas de vigilância epidemiológica
indispensável à avaliação do risco de transmissão de agentes patogénicos
transmitidos por vetores e é fundamental para a implementação de uma
estratégia integrada de controlo de vetores e prevenção de doenças.
As atividades previstas nos programas de vigilância entomológica e doenças
associadas exigem elevados custos com recursos humanos especializados
e com a logística que é investida nas inspeções periódicas das
armadilhas de insetos. É essencial o desenvolvimento de estratégias sustentáveis
para a monitorização de vetores. O projeto VECTRACK propõe o
desenvolvimento de um método inovador na vigilância de mosquitos vetores
de agentes de doença que vai possibilitar a identificação da espécie,
sexo, idade e potencial de infeção das populações de mosquitos, mas de
forma automatizada e remota. Neste artigo apresentamos os principais
protocolos usados no projeto VECTRACK para a configuração de um sensor
acoplado a uma armadilha que proceda à identificação automatizada
de mosquitos através de machine learning.
Within the scope of the Vector Surveillance Network (REVIVE ), entomological surveillance of mosquitoes has been carried out since 2008 in Portugal. REVIVE project is an essential component of epidemiological surveillance programs to assess the risk of transmission of vector-borne pathogens and is essential for the implementation of an integrated strategy for vector control and disease prevention. The activities foreseen in the entomological surveillance programs and associated diseases demand high costs with specialized human resources and with the logistics that are invested in the periodic inspections of insect traps. The development of sustainable strategies for vector monitoring is essential. The VECTRACK project proposes the development of an innovative method in the surveillance of mosquito vectors of disease agents that will make it possible to identify the species, sex, age and infection potential of mosquito populations, but in an automated and remote way. In this manuscript, we present the main protocols used in the VECTRACK project for the configuration of a sensor coupled to a trap that performs the automated identification of mosquitoes through machine learning.
Within the scope of the Vector Surveillance Network (REVIVE ), entomological surveillance of mosquitoes has been carried out since 2008 in Portugal. REVIVE project is an essential component of epidemiological surveillance programs to assess the risk of transmission of vector-borne pathogens and is essential for the implementation of an integrated strategy for vector control and disease prevention. The activities foreseen in the entomological surveillance programs and associated diseases demand high costs with specialized human resources and with the logistics that are invested in the periodic inspections of insect traps. The development of sustainable strategies for vector monitoring is essential. The VECTRACK project proposes the development of an innovative method in the surveillance of mosquito vectors of disease agents that will make it possible to identify the species, sex, age and infection potential of mosquito populations, but in an automated and remote way. In this manuscript, we present the main protocols used in the VECTRACK project for the configuration of a sensor coupled to a trap that performs the automated identification of mosquitoes through machine learning.
Description
Keywords
Doenças Transmitidas por Vetores Vigilância Epidemiológica Vetores Culicídeos Colheita Armadilhas Rede de Vigilância de Vetores REVIVE VECTRACK Infecções Sistémicas e Zoonosese Vetores Estudos de Vetores e Doenças Infeciosas Saúde Pública Portugal
Pedagogical Context
Citation
Boletim Epidemiológico Observações. 2022 mai-ago;11(32):5-12
Publisher
Instituto Nacional de Saúde Doutor Ricardo Jorge, IP
