Towards a leptospirosis early warning system in northeastern Argentina

Autores
Lotto Batista, Martín; Rees, Eleanor M.; Gomez, Andrea Alejandra; Lopez, Maria Soledad; Castell, Stefanie; Kucharski, Adam J.; Ghozzi, Stéphane; Muller, Gabriela Viviana; Lowe, Rachel
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.
Fil: Lotto Batista, Martín. Helmholtz Centre For Infection Research; Alemania
Fil: Rees, Eleanor M.. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España
Fil: Gomez, Andrea Alejandra. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Lopez, Maria Soledad. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Castell, Stefanie. Helmholtz Centre For Infection Research; Alemania
Fil: Kucharski, Adam J.. Centre For Mathematical Modelling Of Infectious Diseas; Reino Unido
Fil: Ghozzi, Stéphane. Helmholtz Centre For Infection Research; Alemania
Fil: Muller, Gabriela Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina
Fil: Lowe, Rachel. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España
Materia
BAYESIAN MODELLING
CLIMATE
EARLY WARNING SYSTEM
EL NIÑO
LEPTOSPIROSIS
OUTBREAK PREDICTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/225006
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/225006
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Towards a leptospirosis early warning system in northeastern ArgentinaLotto Batista, MartínRees, Eleanor M.Gomez, Andrea AlejandraLopez, Maria SoledadCastell, StefanieKucharski, Adam J.Ghozzi, StéphaneMuller, Gabriela VivianaLowe, RachelBAYESIAN MODELLINGCLIMATEEARLY WARNING SYSTEMEL NIÑOLEPTOSPIROSISOUTBREAK PREDICTIONhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.Fil: Lotto Batista, Martín. Helmholtz Centre For Infection Research; AlemaniaFil: Rees, Eleanor M.. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; EspañaFil: Gomez, Andrea Alejandra. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Lopez, Maria Soledad. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Castell, Stefanie. Helmholtz Centre For Infection Research; AlemaniaFil: Kucharski, Adam J.. Centre For Mathematical Modelling Of Infectious Diseas; Reino UnidoFil: Ghozzi, Stéphane. Helmholtz Centre For Infection Research; AlemaniaFil: Muller, Gabriela Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; ArgentinaFil: Lowe, Rachel. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; EspañaThe Royal Society2023-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/225006Lotto Batista, Martín; Rees, Eleanor M.; Gomez, Andrea Alejandra; Lopez, Maria Soledad; Castell, Stefanie; et al.; Towards a leptospirosis early warning system in northeastern Argentina; The Royal Society; Journal of the Royal Society Interface; 20; 202; 5-2023; 1-81742-5689CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0069info:eu-repo/semantics/altIdentifier/doi/10.1098/rsif.2023.0069info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:05:59Zoai:ri.conicet.gov.ar:11336/225006instacron: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:34982025-10-15 15:06:00.228CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Towards a leptospirosis early warning system in northeastern Argentina
title Towards a leptospirosis early warning system in northeastern Argentina
spellingShingle Towards a leptospirosis early warning system in northeastern Argentina
Lotto Batista, Martín
BAYESIAN MODELLING
CLIMATE
EARLY WARNING SYSTEM
EL NIÑO
LEPTOSPIROSIS
OUTBREAK PREDICTION
title_short Towards a leptospirosis early warning system in northeastern Argentina
title_full Towards a leptospirosis early warning system in northeastern Argentina
title_fullStr Towards a leptospirosis early warning system in northeastern Argentina
title_full_unstemmed Towards a leptospirosis early warning system in northeastern Argentina
title_sort Towards a leptospirosis early warning system in northeastern Argentina
dc.creator.none.fl_str_mv Lotto Batista, Martín
Rees, Eleanor M.
Gomez, Andrea Alejandra
Lopez, Maria Soledad
Castell, Stefanie
Kucharski, Adam J.
Ghozzi, Stéphane
Muller, Gabriela Viviana
Lowe, Rachel
author Lotto Batista, Martín
author_facet Lotto Batista, Martín
Rees, Eleanor M.
Gomez, Andrea Alejandra
Lopez, Maria Soledad
Castell, Stefanie
Kucharski, Adam J.
Ghozzi, Stéphane
Muller, Gabriela Viviana
Lowe, Rachel
author_role author
author2 Rees, Eleanor M.
Gomez, Andrea Alejandra
Lopez, Maria Soledad
Castell, Stefanie
Kucharski, Adam J.
Ghozzi, Stéphane
Muller, Gabriela Viviana
Lowe, Rachel
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv BAYESIAN MODELLING
CLIMATE
EARLY WARNING SYSTEM
EL NIÑO
LEPTOSPIROSIS
OUTBREAK PREDICTION
topic BAYESIAN MODELLING
CLIMATE
EARLY WARNING SYSTEM
EL NIÑO
LEPTOSPIROSIS
OUTBREAK PREDICTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.
Fil: Lotto Batista, Martín. Helmholtz Centre For Infection Research; Alemania
Fil: Rees, Eleanor M.. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España
Fil: Gomez, Andrea Alejandra. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Lopez, Maria Soledad. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Castell, Stefanie. Helmholtz Centre For Infection Research; Alemania
Fil: Kucharski, Adam J.. Centre For Mathematical Modelling Of Infectious Diseas; Reino Unido
Fil: Ghozzi, Stéphane. Helmholtz Centre For Infection Research; Alemania
Fil: Muller, Gabriela Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina
Fil: Lowe, Rachel. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España
description Leptospirosis is a zoonotic disease with a high burden in Latin America, including northeastern Argentina, where flooding events linked to El Niño are associated with leptospirosis outbreaks. The aim of this study was to evaluate the value of using hydrometeorological indicators to predict leptospirosis outbreaks in this region. We quantified the effects of El Niño, precipitation, and river height on leptospirosis risk in Santa Fe and Entre Ríos provinces between 2009 and 2020, using a Bayesian modelling framework. Based on several goodness of fit statistics, we selected candidate models using a long-lead El Niño 3.4 index and shorter lead local climate variables. We then tested predictive performance to detect leptospirosis outbreaks using a two-stage early warning approach. Three-month lagged Niño 3.4 index and one-month lagged precipitation and river height were positively associated with an increase in leptospirosis cases in both provinces. El Niño models correctly detected 89% of outbreaks, while short-lead local models gave similar detection rates with a lower number of false positives. Our results show that climatic events are strong drivers of leptospirosis incidence in northeastern Argentina. Therefore, a leptospirosis outbreak prediction tool driven by hydrometeorological indicators could form part of an early warning and response system in the region.
publishDate 2023
dc.date.none.fl_str_mv 2023-05
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/11336/225006
Lotto Batista, Martín; Rees, Eleanor M.; Gomez, Andrea Alejandra; Lopez, Maria Soledad; Castell, Stefanie; et al.; Towards a leptospirosis early warning system in northeastern Argentina; The Royal Society; Journal of the Royal Society Interface; 20; 202; 5-2023; 1-8
1742-5689
CONICET Digital
CONICET
url http://hdl.handle.net/11336/225006
identifier_str_mv Lotto Batista, Martín; Rees, Eleanor M.; Gomez, Andrea Alejandra; Lopez, Maria Soledad; Castell, Stefanie; et al.; Towards a leptospirosis early warning system in northeastern Argentina; The Royal Society; Journal of the Royal Society Interface; 20; 202; 5-2023; 1-8
1742-5689
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://royalsocietypublishing.org/doi/10.1098/rsif.2023.0069
info:eu-repo/semantics/altIdentifier/doi/10.1098/rsif.2023.0069
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv The Royal Society
publisher.none.fl_str_mv The Royal Society
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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score 13.22299

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