| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m21b.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP5W34M/3GD3GBB |
| Repository | sid.inpe.br/mtc-m21b/2014/05.30.02.19.39 (restricted access) |
| Last Update | 2014:06.17.14.54.58 (UTC) marcelo.pazos@inpe.br |
| Metadata Repository | sid.inpe.br/mtc-m21b/2014/05.30.02.19.40 |
| Metadata Last Update | 2018:06.04.03.04.10 (UTC) administrator |
| DOI | 10.1016/j.actatropica.2014.01.015 |
| ISSN | 0001-706X 1873-6254 |
| Label | scopus 2014-05 FonsecaFreDutGuiCar:2014:SpMoSc |
| Citation Key | FonsecaFreDutGuiCar:2014:SpMoSc |
| Title | Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression  |
| Year | 2014 |
| Access Date | 2024, May 19 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 1802 KiB |
| 2. Context | |
| Author | 1 Fonseca, Fernanda Rodrigues 2 Freitas, Corina da Costa 3 Dutra, Luciano Vieira 4 Guimarães, Ricardo J. P. S. 5 Carvalho, O. |
| Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JHMA |
| Group | 1 DPI-OBT-INPE-MCTI-GOV-BR 2 DPI-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-INPE-MCTI-GOV-BR |
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais/INPE, Av. dos Astronautas, 1758 Jd. Granja, CEP 12227-010 São José dos Campos, SP, Brazil; Instituto Evandro Chagas/IEC, Rodovia BR-316 km 7 Levilândia, CEP 67030-000 Ananindeua, PA, Brazil 5 Centro de Pesquisas René Rachou/FIOCRUZ, Av. Augusto de Lima, 1715 Barro Preto, CEP 30190-002 Belo Horizonte, MG, Brazil |
| Author e-Mail Address | 1 ffonseca@dpi.inpe.br 2 3 dutra@dpi.inpe.br |
| e-Mail Address | marcelo.pazos@inpe.br |
| Journal | Acta Tropica |
| Volume | 133 |
| Number | 1 |
| Pages | 56-63 |
| Secondary Mark | A1_INTERDISCIPLINAR A1_CIÊNCIAS_AGRÁRIAS_I A1_ZOOTECNIA_/_RECURSOS_PESQUEIROS A1_GEOGRAFIA A2_GEOCIÊNCIAS A2_ENFERMAGEM A2_NUTRIÇÃO A2_MEDICINA_VETERINÁRIA A2_SAÚDE_COLETIVA A2_BIODIVERSIDADE B1_MATERIAIS B1_MEDICINA_II B1_CIÊNCIAS_BIOLÓGICAS_I B1_BIOTECNOLOGIA B1_CIÊNCIAS_BIOLÓGICAS_III B1_FARMÁCIA B1_MEDICINA_I B1_CIÊNCIAS_BIOLÓGICAS_II B1_QUÍMICA B1_MEDICINA_III B2_EDUCAÇÃO_FÍSICA B2_ASTRONOMIA_/_FÍSICA B2_ENSINO C_ENGENHARIAS_II |
| History (UTC) | 2016-07-03 20:59:18 :: administrator -> marcelo.pazos@inpe.br :: 2014 2016-08-26 16:18:16 :: marcelo.pazos@inpe.br -> administrator :: 2014 2018-06-04 03:04:10 :: administrator -> marcelo.pazos@inpe.br :: 2014 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Version Type | publisher |
| Keywords | disease spread health impact health risk neighborhood public health regression analysis schistosomiasis spatial analysis taxonomy article Brazil climate disease course disease transmission environmental factor health care management human human development mathematical variable medical information neighborhood precipitation prevalence risk assessment river sanitation schistosomiasis mansoni socioeconomics spatial modeling spatial regression statistical analysis statistical model temperature topography traffic and transport vegetation Brazil Minas Gerais |
| Abstract | Schistosomiasis is a transmissible parasitic disease caused by the etiologic agent Schistosoma mansoni, whose intermediate hosts are snails of the genus Biomphalaria. The main goal of this paper is to estimate the prevalence of schistosomiasis in Minas Gerais State in Brazil using spatial disease information derived from the state transportation network of roads and rivers. The spatial information was incorporated in two ways: by introducing new variables that carry spatial neighborhood information and by using spatial regression models. Climate, socioeconomic and environmental variables were also used as co-variables to build models and use them to estimate a risk map for the whole state of Minas Gerais. The results show that the models constructed from the spatial regression produced a better fit, providing smaller root mean square error (RMSE) values. When no spatial information was used, the RMSE for the whole state of Minas Gerais reached 9.5%; with spatial regression, the RMSE reaches 8.8% (when the new variables are added to the model) and 8.5% (with the use of spatial regression). Variables representing vegetation, temperature, precipitation, topography, sanitation and human development indexes were important in explaining the spread of disease and identified certain conditions that are favorable for disease development. The use of spatial regression for the network of roads and rivers produced meaningful results for health management procedures and directing activities, enabling better detection of disease risk areas. © 2014 Elsevier B.V. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Spatial modeling of... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| Target File | Fernanda_Acta_2104.pdf |
| User Group | administrator banon marcelo.pazos@inpe.br self-uploading-INPE-MCTI-GOV-BR |
| Reader Group | administrator banon marcelo.pazos@inpe.br |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft12 |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Mirror Repository | iconet.com.br/banon/2006/11.26.21.31 |
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 |
| Citing Item List | sid.inpe.br/bibdigital/2013/09.09.15.05 4 sid.inpe.br/mtc-m21/2012/07.13.14.53.50 1 |
| Dissemination | WEBSCI; PORTALCAPES; SCOPUS. |
| Host Collection | sid.inpe.br/mtc-m21b/2013/09.26.14.25.20 |
| 6. Notes | |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Description control | |
| e-Mail (login) | marcelo.pazos@inpe.br |
| update | |