Cargando…

A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment

BACKGROUND: Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens. METHODS: As a case study, we retrospectively analyzed three Q fever outbreaks in the Neth...

Descripción completa

Detalles Bibliográficos
Autores principales: van Leuken, Jeroen P. G., Havelaar, Arie H., van der Hoek, Wim, Ladbury, Georgia A. F., Hackert, Volker H., Swart, Arno N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850919/
https://www.ncbi.nlm.nih.gov/pubmed/24324598
http://dx.doi.org/10.1371/journal.pone.0080412
_version_ 1782294189695827968
author van Leuken, Jeroen P. G.
Havelaar, Arie H.
van der Hoek, Wim
Ladbury, Georgia A. F.
Hackert, Volker H.
Swart, Arno N.
author_facet van Leuken, Jeroen P. G.
Havelaar, Arie H.
van der Hoek, Wim
Ladbury, Georgia A. F.
Hackert, Volker H.
Swart, Arno N.
author_sort van Leuken, Jeroen P. G.
collection PubMed
description BACKGROUND: Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens. METHODS: As a case study, we retrospectively analyzed three Q fever outbreaks in the Netherlands in 2009, each with suspected exposure from a single large dairy goat farm. Model input consisted only of case residential addresses, day of first clinical symptoms, and human population density data. We defined a spatial grid and fitted an exponentially declining function to the incidence-distance data of each grid point. For any grid point with a fit significant at the 95% confidence level, we calculated a measure of risk. For validation, we used results from abortion notifications, voluntary (2008) and mandatory (2009) bulk tank milk sampling at large (i.e. >50 goats and/or sheep) dairy farms, and non-systematic vaginal swab sampling at large and small dairy and non-dairy goat/sheep farms. In addition, we performed a two-source simulation study. RESULTS: Hotspots – areas most likely to contain the actual source – were identified at early outbreak stages, based on the earliest 2–10% of the case notifications. Distances between the hotspots and suspected goat farms varied from 300–1500 m. In regional likelihood rankings including all large dairy farms, the suspected goat farms consistently ranked first. The two-source simulation study showed that detection of sources is most clear if the distance between the sources is either relatively small or relatively large. CONCLUSIONS: Our model identifies the most likely location of sources in an airborne pathogen outbreak area, even at early stages. It can help to reduce the number of potential sources to be investigated by microbial testing and to allow rapid implementation of interventions to limit the number of human infections and to reduce the risk of source-to-source transmission.
format Online
Article
Text
id pubmed-3850919
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-38509192013-12-09 A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment van Leuken, Jeroen P. G. Havelaar, Arie H. van der Hoek, Wim Ladbury, Georgia A. F. Hackert, Volker H. Swart, Arno N. PLoS One Research Article BACKGROUND: Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens. METHODS: As a case study, we retrospectively analyzed three Q fever outbreaks in the Netherlands in 2009, each with suspected exposure from a single large dairy goat farm. Model input consisted only of case residential addresses, day of first clinical symptoms, and human population density data. We defined a spatial grid and fitted an exponentially declining function to the incidence-distance data of each grid point. For any grid point with a fit significant at the 95% confidence level, we calculated a measure of risk. For validation, we used results from abortion notifications, voluntary (2008) and mandatory (2009) bulk tank milk sampling at large (i.e. >50 goats and/or sheep) dairy farms, and non-systematic vaginal swab sampling at large and small dairy and non-dairy goat/sheep farms. In addition, we performed a two-source simulation study. RESULTS: Hotspots – areas most likely to contain the actual source – were identified at early outbreak stages, based on the earliest 2–10% of the case notifications. Distances between the hotspots and suspected goat farms varied from 300–1500 m. In regional likelihood rankings including all large dairy farms, the suspected goat farms consistently ranked first. The two-source simulation study showed that detection of sources is most clear if the distance between the sources is either relatively small or relatively large. CONCLUSIONS: Our model identifies the most likely location of sources in an airborne pathogen outbreak area, even at early stages. It can help to reduce the number of potential sources to be investigated by microbial testing and to allow rapid implementation of interventions to limit the number of human infections and to reduce the risk of source-to-source transmission. Public Library of Science 2013-12-04 /pmc/articles/PMC3850919/ /pubmed/24324598 http://dx.doi.org/10.1371/journal.pone.0080412 Text en © 2013 van Leuken et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
van Leuken, Jeroen P. G.
Havelaar, Arie H.
van der Hoek, Wim
Ladbury, Georgia A. F.
Hackert, Volker H.
Swart, Arno N.
A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title_full A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title_fullStr A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title_full_unstemmed A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title_short A Model for the Early Identification of Sources of Airborne Pathogens in an Outdoor Environment
title_sort model for the early identification of sources of airborne pathogens in an outdoor environment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850919/
https://www.ncbi.nlm.nih.gov/pubmed/24324598
http://dx.doi.org/10.1371/journal.pone.0080412
work_keys_str_mv AT vanleukenjeroenpg amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT havelaararieh amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT vanderhoekwim amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT ladburygeorgiaaf amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT hackertvolkerh amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT swartarnon amodelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT vanleukenjeroenpg modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT havelaararieh modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT vanderhoekwim modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT ladburygeorgiaaf modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT hackertvolkerh modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment
AT swartarnon modelfortheearlyidentificationofsourcesofairbornepathogensinanoutdoorenvironment