Leveraging artificial intelligence to improve malaria epidemics' response
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.25761/anaisihmt.25 |
Resumo: | As the world advances toward malaria elimination, the elimination management paradigm has to change to address early case detection in more local and remote areas. Remote areas face additional difficulties in both detection and treatment demanding innovative approaches. Malaria elimination needs evidence-based decision-making with real-time access to malaria-cases data. Years of endeavor towards malaria elimination have created several databases, which often lack interoperability, making the crossing of data difficult. The access to early alerts can promote decision-makers quick action in launching early interventions particularly in a low-resources settings. Therefore, a smart, comprehensive, sustainable and integrated information system is required. We propose a collaborative-design implementation strategy, combining elements of gamification, Geographical Information System (GIS) and Artificial Intelligence (AI) to enable early-detection and risk of epidemics alerts, and to direct interventions around detected cases. These technologies can be combined to further reinforce the sustainability of data collection and the behavioral change of public health decision- -makers. The success of such a system depends mostly on how elimination actions will be improved in real settings. Therefore design-science research methodology could engage health professionals and use evidence-based knowledge in the design of an innovative system that responds to what public health professionals’ real needs. |
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Leveraging artificial intelligence to improve malaria epidemics' responsePotenciar a inteligência artificial para melhorar a resposta a epidemias de maláriaAs the world advances toward malaria elimination, the elimination management paradigm has to change to address early case detection in more local and remote areas. Remote areas face additional difficulties in both detection and treatment demanding innovative approaches. Malaria elimination needs evidence-based decision-making with real-time access to malaria-cases data. Years of endeavor towards malaria elimination have created several databases, which often lack interoperability, making the crossing of data difficult. The access to early alerts can promote decision-makers quick action in launching early interventions particularly in a low-resources settings. Therefore, a smart, comprehensive, sustainable and integrated information system is required. We propose a collaborative-design implementation strategy, combining elements of gamification, Geographical Information System (GIS) and Artificial Intelligence (AI) to enable early-detection and risk of epidemics alerts, and to direct interventions around detected cases. These technologies can be combined to further reinforce the sustainability of data collection and the behavioral change of public health decision- -makers. The success of such a system depends mostly on how elimination actions will be improved in real settings. Therefore design-science research methodology could engage health professionals and use evidence-based knowledge in the design of an innovative system that responds to what public health professionals’ real needs.À medida que se avança para a eliminação da malária, o paradigma de gestão deve mudar para abordar a deteção precoce de casos em áreas mais remotas. As áreas remotas enfrentam dificuldades adicionais na deteção e no tratamento que exigem abordagens inovadoras. A eliminação da malária precisa de tomada de decisão baseada em evidências com acesso em tempo-real aos dados de casos de malária. O esforço para a eliminação da malária criou várias bases-de-dados, frquentemente sem interoperabilidade, dificultando o uso dos dados. O acesso a alertas precoces pode promover a ação rápida dos decisores no envio de intervenções. É necessário um sistema de informação abrangente, sustentável e integrado. Propomos uma estratégia de implementação colaborativa, combinando elementos de gamificação, Sistema de Informação Geográfica (SIG) e Inteligência Artificial para permitir alertas-precoces de deteção de risco de epidemias e apoiar o envoi de intervenções. Estas tecnologias podem ser combinadas para reforçar a sustentabilidade da coleta de dados e a mudança comportamental dos decisores de saúde pública. O sucesso desse sistema depende principalmente de como as ações de eliminação serão melhoradas em configurações reais. A envolvência dos profissionais de saúde permite ajustar o desenho de um sistema que responda às necessidades dos profissionais.Universidade Nova de Lisboa2018-04-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.25761/anaisihmt.25oai:ojs.anaisihmt.com:article/25Anais do Instituto de Higiene e Medicina Tropical; Vol 16 (2017): 4.º Congresso Nacional de Medicina Tropical; 35-39Anais do Instituto de Higiene e Medicina Tropical; v. 16 (2017): 4.º Congresso Nacional de Medicina Tropical; 35-392184-23100303-7762reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttp://anaisihmt.com/index.php/ihmt/article/view/25https://doi.org/10.25761/anaisihmt.25http://anaisihmt.com/index.php/ihmt/article/view/25/19Lapão, Luís V.Maia, Mélanie R.Gregório, Joãoinfo:eu-repo/semantics/openAccess2022-09-23T15:30:15Zoai:ojs.anaisihmt.com:article/25Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:03:50.318159Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Leveraging artificial intelligence to improve malaria epidemics' response Potenciar a inteligência artificial para melhorar a resposta a epidemias de malária |
title |
Leveraging artificial intelligence to improve malaria epidemics' response |
spellingShingle |
Leveraging artificial intelligence to improve malaria epidemics' response Lapão, Luís V. |
title_short |
Leveraging artificial intelligence to improve malaria epidemics' response |
title_full |
Leveraging artificial intelligence to improve malaria epidemics' response |
title_fullStr |
Leveraging artificial intelligence to improve malaria epidemics' response |
title_full_unstemmed |
Leveraging artificial intelligence to improve malaria epidemics' response |
title_sort |
Leveraging artificial intelligence to improve malaria epidemics' response |
author |
Lapão, Luís V. |
author_facet |
Lapão, Luís V. Maia, Mélanie R. Gregório, João |
author_role |
author |
author2 |
Maia, Mélanie R. Gregório, João |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Lapão, Luís V. Maia, Mélanie R. Gregório, João |
description |
As the world advances toward malaria elimination, the elimination management paradigm has to change to address early case detection in more local and remote areas. Remote areas face additional difficulties in both detection and treatment demanding innovative approaches. Malaria elimination needs evidence-based decision-making with real-time access to malaria-cases data. Years of endeavor towards malaria elimination have created several databases, which often lack interoperability, making the crossing of data difficult. The access to early alerts can promote decision-makers quick action in launching early interventions particularly in a low-resources settings. Therefore, a smart, comprehensive, sustainable and integrated information system is required. We propose a collaborative-design implementation strategy, combining elements of gamification, Geographical Information System (GIS) and Artificial Intelligence (AI) to enable early-detection and risk of epidemics alerts, and to direct interventions around detected cases. These technologies can be combined to further reinforce the sustainability of data collection and the behavioral change of public health decision- -makers. The success of such a system depends mostly on how elimination actions will be improved in real settings. Therefore design-science research methodology could engage health professionals and use evidence-based knowledge in the design of an innovative system that responds to what public health professionals’ real needs. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-04-27T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.25761/anaisihmt.25 oai:ojs.anaisihmt.com:article/25 |
url |
https://doi.org/10.25761/anaisihmt.25 |
identifier_str_mv |
oai:ojs.anaisihmt.com:article/25 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://anaisihmt.com/index.php/ihmt/article/view/25 https://doi.org/10.25761/anaisihmt.25 http://anaisihmt.com/index.php/ihmt/article/view/25/19 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Nova de Lisboa |
publisher.none.fl_str_mv |
Universidade Nova de Lisboa |
dc.source.none.fl_str_mv |
Anais do Instituto de Higiene e Medicina Tropical; Vol 16 (2017): 4.º Congresso Nacional de Medicina Tropical; 35-39 Anais do Instituto de Higiene e Medicina Tropical; v. 16 (2017): 4.º Congresso Nacional de Medicina Tropical; 35-39 2184-2310 0303-7762 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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