Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina

Autores
Scavuzzo, Carlos Matias; Campero, Micaela Natalia; Maidana, Rosana Elizabeth; Oberto, María Georgina; Periago, Maria Victoria; Porcasi Gomez, Ximena
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Argentina has a heterogeneous prevalence of infections by intestinal parasites (IPs), with the north in the endemic area, especially for soil-transmitted helminths (STHs). We analyzed the spatial patterns of these infections in the city of Tartagal, Salta province, by an observational, correlational, and cross-sectional study in children and adolescents aged 1 to 15 years from native communities. One fecal sample per individual was collected to detect IPs using various diagnostic techniques: Telemann sedimentation, Baermann culture, and Kato-Katz. Moran’s global and local indices were applied together with SaTScan to assess the spatial distribution, with a focus on cluster detection. The extreme gradient boosting (XGBoost) machine-learning model was used to predict the presence of IPs and their transmission pathways. Based on the analysis of 572 fecal samples, a prevalence of 78.3% was found. The most frequent parasite was Giardia lamblia (30.9%). High- and low-risk clusters were observed for most species, distributed in an east-west direction and polarized in two large foci, one near the city of Tartagal and the other in the km 6 community. Spatial XGBoost models were obtained based on distances with a minimum median accuracy of 0.69. Different spatial patterns reflecting the mechanisms of transmission were noted. The distribution of the majority of the parasites studied was aligned in a westerly direction close to the city, but the STH presence was higher in the km 6 community, toward the east. The purely spatial analysis provides a different and complementary overview for the detection of vulnerable hotspots and strategic intervention. Machine-learning models based on spatial variables explain a large percentage of the variability of the IPs.
Fil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Campero, Micaela Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Maidana, Rosana Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Oberto, María Georgina. Universidad Nacional de Córdoba; Argentina
Fil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; Argentina
Fil: Porcasi Gomez, Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Materia
Machine learning
Intestinal parasites
Spatial analysis
Argentina
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/247788
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in ArgentinaScavuzzo, Carlos MatiasCampero, Micaela NataliaMaidana, Rosana ElizabethOberto, María GeorginaPeriago, Maria VictoriaPorcasi Gomez, XimenaMachine learningIntestinal parasitesSpatial analysisArgentinahttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Argentina has a heterogeneous prevalence of infections by intestinal parasites (IPs), with the north in the endemic area, especially for soil-transmitted helminths (STHs). We analyzed the spatial patterns of these infections in the city of Tartagal, Salta province, by an observational, correlational, and cross-sectional study in children and adolescents aged 1 to 15 years from native communities. One fecal sample per individual was collected to detect IPs using various diagnostic techniques: Telemann sedimentation, Baermann culture, and Kato-Katz. Moran’s global and local indices were applied together with SaTScan to assess the spatial distribution, with a focus on cluster detection. The extreme gradient boosting (XGBoost) machine-learning model was used to predict the presence of IPs and their transmission pathways. Based on the analysis of 572 fecal samples, a prevalence of 78.3% was found. The most frequent parasite was Giardia lamblia (30.9%). High- and low-risk clusters were observed for most species, distributed in an east-west direction and polarized in two large foci, one near the city of Tartagal and the other in the km 6 community. Spatial XGBoost models were obtained based on distances with a minimum median accuracy of 0.69. Different spatial patterns reflecting the mechanisms of transmission were noted. The distribution of the majority of the parasites studied was aligned in a westerly direction close to the city, but the STH presence was higher in the km 6 community, toward the east. The purely spatial analysis provides a different and complementary overview for the detection of vulnerable hotspots and strategic intervention. Machine-learning models based on spatial variables explain a large percentage of the variability of the IPs.Fil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Campero, Micaela Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Maidana, Rosana Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Oberto, María Georgina. Universidad Nacional de Córdoba; ArgentinaFil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; ArgentinaFil: Porcasi Gomez, Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaUniv Naples Federico Ii2024-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/247788Scavuzzo, Carlos Matias; Campero, Micaela Natalia; Maidana, Rosana Elizabeth; Oberto, María Georgina; Periago, Maria Victoria; et al.; Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina; Univ Naples Federico Ii; Geospatial Health; 19; 1; 5-2024; 1-121827-1987CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.geospatialhealth.net/gh/article/view/1279info:eu-repo/semantics/altIdentifier/doi/10.4081/gh.2024.1279info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:41:25Zoai:ri.conicet.gov.ar:11336/247788instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:41:25.391CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
title Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
spellingShingle Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
Scavuzzo, Carlos Matias
Machine learning
Intestinal parasites
Spatial analysis
Argentina
title_short Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
title_full Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
title_fullStr Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
title_full_unstemmed Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
title_sort Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina
dc.creator.none.fl_str_mv Scavuzzo, Carlos Matias
Campero, Micaela Natalia
Maidana, Rosana Elizabeth
Oberto, María Georgina
Periago, Maria Victoria
Porcasi Gomez, Ximena
author Scavuzzo, Carlos Matias
author_facet Scavuzzo, Carlos Matias
Campero, Micaela Natalia
Maidana, Rosana Elizabeth
Oberto, María Georgina
Periago, Maria Victoria
Porcasi Gomez, Ximena
author_role author
author2 Campero, Micaela Natalia
Maidana, Rosana Elizabeth
Oberto, María Georgina
Periago, Maria Victoria
Porcasi Gomez, Ximena
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Machine learning
Intestinal parasites
Spatial analysis
Argentina
topic Machine learning
Intestinal parasites
Spatial analysis
Argentina
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Argentina has a heterogeneous prevalence of infections by intestinal parasites (IPs), with the north in the endemic area, especially for soil-transmitted helminths (STHs). We analyzed the spatial patterns of these infections in the city of Tartagal, Salta province, by an observational, correlational, and cross-sectional study in children and adolescents aged 1 to 15 years from native communities. One fecal sample per individual was collected to detect IPs using various diagnostic techniques: Telemann sedimentation, Baermann culture, and Kato-Katz. Moran’s global and local indices were applied together with SaTScan to assess the spatial distribution, with a focus on cluster detection. The extreme gradient boosting (XGBoost) machine-learning model was used to predict the presence of IPs and their transmission pathways. Based on the analysis of 572 fecal samples, a prevalence of 78.3% was found. The most frequent parasite was Giardia lamblia (30.9%). High- and low-risk clusters were observed for most species, distributed in an east-west direction and polarized in two large foci, one near the city of Tartagal and the other in the km 6 community. Spatial XGBoost models were obtained based on distances with a minimum median accuracy of 0.69. Different spatial patterns reflecting the mechanisms of transmission were noted. The distribution of the majority of the parasites studied was aligned in a westerly direction close to the city, but the STH presence was higher in the km 6 community, toward the east. The purely spatial analysis provides a different and complementary overview for the detection of vulnerable hotspots and strategic intervention. Machine-learning models based on spatial variables explain a large percentage of the variability of the IPs.
Fil: Scavuzzo, Carlos Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Campero, Micaela Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Maidana, Rosana Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Oberto, María Georgina. Universidad Nacional de Córdoba; Argentina
Fil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; Argentina
Fil: Porcasi Gomez, Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
description Argentina has a heterogeneous prevalence of infections by intestinal parasites (IPs), with the north in the endemic area, especially for soil-transmitted helminths (STHs). We analyzed the spatial patterns of these infections in the city of Tartagal, Salta province, by an observational, correlational, and cross-sectional study in children and adolescents aged 1 to 15 years from native communities. One fecal sample per individual was collected to detect IPs using various diagnostic techniques: Telemann sedimentation, Baermann culture, and Kato-Katz. Moran’s global and local indices were applied together with SaTScan to assess the spatial distribution, with a focus on cluster detection. The extreme gradient boosting (XGBoost) machine-learning model was used to predict the presence of IPs and their transmission pathways. Based on the analysis of 572 fecal samples, a prevalence of 78.3% was found. The most frequent parasite was Giardia lamblia (30.9%). High- and low-risk clusters were observed for most species, distributed in an east-west direction and polarized in two large foci, one near the city of Tartagal and the other in the km 6 community. Spatial XGBoost models were obtained based on distances with a minimum median accuracy of 0.69. Different spatial patterns reflecting the mechanisms of transmission were noted. The distribution of the majority of the parasites studied was aligned in a westerly direction close to the city, but the STH presence was higher in the km 6 community, toward the east. The purely spatial analysis provides a different and complementary overview for the detection of vulnerable hotspots and strategic intervention. Machine-learning models based on spatial variables explain a large percentage of the variability of the IPs.
publishDate 2024
dc.date.none.fl_str_mv 2024-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/247788
Scavuzzo, Carlos Matias; Campero, Micaela Natalia; Maidana, Rosana Elizabeth; Oberto, María Georgina; Periago, Maria Victoria; et al.; Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina; Univ Naples Federico Ii; Geospatial Health; 19; 1; 5-2024; 1-12
1827-1987
CONICET Digital
CONICET
url http://hdl.handle.net/11336/247788
identifier_str_mv Scavuzzo, Carlos Matias; Campero, Micaela Natalia; Maidana, Rosana Elizabeth; Oberto, María Georgina; Periago, Maria Victoria; et al.; Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina; Univ Naples Federico Ii; Geospatial Health; 19; 1; 5-2024; 1-12
1827-1987
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.geospatialhealth.net/gh/article/view/1279
info:eu-repo/semantics/altIdentifier/doi/10.4081/gh.2024.1279
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Univ Naples Federico Ii
publisher.none.fl_str_mv Univ Naples Federico Ii
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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