Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal

Detalhes bibliográficos
Autor(a) principal: Capinha, César
Data de Publicação: 2009
Outros Autores: Gomes, Eduardo, Reis, Eusébio, Rocha, Jorge, Sousa, Carla A., Do Rosário, V. E., Almeida, A. Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/36984
Resumo: Malaria was a major health problem in the first half of the 20th Century in mainland Portugal. Nowadays, although the disease is no longer endemic, there is still the risk of future endemic infections due to the continuous occurrence of imported cases and the possibility of transmission in the country by Anopheles atroparvus Van Thiel, 1927. Since vector abundance constitute one of the foremost factors in malaria transmission, we have created several habitat suitability models to describe this vector species' current distribution. Three different correlative models; namely (i) a multilayer perceptron artificial neural network (MLP-ANN); (ii) binary logistic regression (BLR); and (iii) Mahalanobis distance were used to combine the species records with a set of five environmental predictors. Kappa coefficient values from k-fold cross-validation records showed that binary logistic regression produced the best predictions, while the other two models also produced acceptable results. Therefore, in order to reduce uncertainty, the three suitability models were combined. The resulting model identified high suitability for An. atroparvus in the majority of the country with exception of the northern and central coastal areas. Malaria distribution during the last endemic period in the country was also compared with the combined suitability model, and a high degree of spatial agreement was obtained (kappa = 0.62). It was concluded that habitat suitability for malaria vectors can constitute valuable information on the assessment of several spatial attributes of the disease. In addition, the results suggest that the spatial distribution of An. atroparvus in the country remains very similar to the one known about seven decades ago.
id RCAP_7115c00e9fe21a38c0b0d1e270c6c343
oai_identifier_str oai:repositorio.ul.pt:10451/36984
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland PortugalAnimalsMalariaModels, StatisticalNeural Networks (Computer)PortugalAnophelesEcosystemPopulation DensityMalaria was a major health problem in the first half of the 20th Century in mainland Portugal. Nowadays, although the disease is no longer endemic, there is still the risk of future endemic infections due to the continuous occurrence of imported cases and the possibility of transmission in the country by Anopheles atroparvus Van Thiel, 1927. Since vector abundance constitute one of the foremost factors in malaria transmission, we have created several habitat suitability models to describe this vector species' current distribution. Three different correlative models; namely (i) a multilayer perceptron artificial neural network (MLP-ANN); (ii) binary logistic regression (BLR); and (iii) Mahalanobis distance were used to combine the species records with a set of five environmental predictors. Kappa coefficient values from k-fold cross-validation records showed that binary logistic regression produced the best predictions, while the other two models also produced acceptable results. Therefore, in order to reduce uncertainty, the three suitability models were combined. The resulting model identified high suitability for An. atroparvus in the majority of the country with exception of the northern and central coastal areas. Malaria distribution during the last endemic period in the country was also compared with the combined suitability model, and a high degree of spatial agreement was obtained (kappa = 0.62). It was concluded that habitat suitability for malaria vectors can constitute valuable information on the assessment of several spatial attributes of the disease. In addition, the results suggest that the spatial distribution of An. atroparvus in the country remains very similar to the one known about seven decades ago.PAGEpressRepositório da Universidade de LisboaCapinha, CésarGomes, EduardoReis, EusébioRocha, JorgeSousa, Carla A.Do Rosário, V. E.Almeida, A. Paulo2019-02-13T14:40:49Z20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/36984engCapinha, C., Gomes, E., Reis, E., Rocha, J., Sousa, C. A., do Rosário, V. E., Almeida, A. P. (2009). Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal. Geospatial Health, 3(2), pp. 177–187. https://doi.org/10.4081/gh.2009.2191827-198710.4081/gh.2009.219info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:33:54Zoai:repositorio.ul.pt:10451/36984Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:51:07.023656Repositório 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 Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
title Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
spellingShingle Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
Capinha, César
Animals
Malaria
Models, Statistical
Neural Networks (Computer)
Portugal
Anopheles
Ecosystem
Population Density
title_short Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
title_full Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
title_fullStr Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
title_full_unstemmed Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
title_sort Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal
author Capinha, César
author_facet Capinha, César
Gomes, Eduardo
Reis, Eusébio
Rocha, Jorge
Sousa, Carla A.
Do Rosário, V. E.
Almeida, A. Paulo
author_role author
author2 Gomes, Eduardo
Reis, Eusébio
Rocha, Jorge
Sousa, Carla A.
Do Rosário, V. E.
Almeida, A. Paulo
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Capinha, César
Gomes, Eduardo
Reis, Eusébio
Rocha, Jorge
Sousa, Carla A.
Do Rosário, V. E.
Almeida, A. Paulo
dc.subject.por.fl_str_mv Animals
Malaria
Models, Statistical
Neural Networks (Computer)
Portugal
Anopheles
Ecosystem
Population Density
topic Animals
Malaria
Models, Statistical
Neural Networks (Computer)
Portugal
Anopheles
Ecosystem
Population Density
description Malaria was a major health problem in the first half of the 20th Century in mainland Portugal. Nowadays, although the disease is no longer endemic, there is still the risk of future endemic infections due to the continuous occurrence of imported cases and the possibility of transmission in the country by Anopheles atroparvus Van Thiel, 1927. Since vector abundance constitute one of the foremost factors in malaria transmission, we have created several habitat suitability models to describe this vector species' current distribution. Three different correlative models; namely (i) a multilayer perceptron artificial neural network (MLP-ANN); (ii) binary logistic regression (BLR); and (iii) Mahalanobis distance were used to combine the species records with a set of five environmental predictors. Kappa coefficient values from k-fold cross-validation records showed that binary logistic regression produced the best predictions, while the other two models also produced acceptable results. Therefore, in order to reduce uncertainty, the three suitability models were combined. The resulting model identified high suitability for An. atroparvus in the majority of the country with exception of the northern and central coastal areas. Malaria distribution during the last endemic period in the country was also compared with the combined suitability model, and a high degree of spatial agreement was obtained (kappa = 0.62). It was concluded that habitat suitability for malaria vectors can constitute valuable information on the assessment of several spatial attributes of the disease. In addition, the results suggest that the spatial distribution of An. atroparvus in the country remains very similar to the one known about seven decades ago.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009-01-01T00:00:00Z
2019-02-13T14:40:49Z
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 http://hdl.handle.net/10451/36984
url http://hdl.handle.net/10451/36984
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Capinha, C., Gomes, E., Reis, E., Rocha, J., Sousa, C. A., do Rosário, V. E., Almeida, A. P. (2009). Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal. Geospatial Health, 3(2), pp. 177–187. https://doi.org/10.4081/gh.2009.219
1827-1987
10.4081/gh.2009.219
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 PAGEpress
publisher.none.fl_str_mv PAGEpress
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799134446634401792