Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata.
Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and hou...
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ftdoajarticles:oai:doaj.org/article:375a39c117444e0fae284a57d8ca620e 2023-05-15T15:13:08+02:00 Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. B K M Case Jean-Gabriel Young Daniel Penados Carlota Monroy Laurent Hébert-Dufresne Lori Stevens 2022-06-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0010436 https://doaj.org/article/375a39c117444e0fae284a57d8ca620e EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0010436 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0010436 https://doaj.org/article/375a39c117444e0fae284a57d8ca620e PLoS Neglected Tropical Diseases, Vol 16, Iss 6, p e0010436 (2022) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2022 ftdoajarticles https://doi.org/10.1371/journal.pntd.0010436 2022-12-31T00:24:31Z Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and housing improvements has been shown to yield lasting results. However, the additional resources and personnel required by such an intervention likely hinders its widespread adoption. One solution to this problem would be to target only a subset of houses in a community while still eliminating enough infestations to interrupt disease transfer. Here we develop a sequential sampling framework that adapts to information specific to a community as more houses are visited, thereby allowing us to efficiently find homes with domiciliary vectors while minimizing sampling bias. The method fits Bayesian geostatistical models to make spatially informed predictions, while gradually transitioning from prioritizing houses based on prediction uncertainty to targeting houses with a high risk of infestation. A key feature of the method is the use of a single exploration parameter, α, to control the rate of transition between these two design targets. In a simulation study using empirical data from five villages in southeastern Guatemala, we test our method using a range of values for α, and find it can consistently select fewer homes than random sampling, while still bringing the village infestation rate below a given threshold. We further find that when additional socioeconomic information is available, much larger savings are possible, but that meeting the target infestation rate is less consistent, particularly among the less exploratory strategies. Our results suggest new options for implementing long-term T. dimidiata control. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 16 6 e0010436 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 B K M Case Jean-Gabriel Young Daniel Penados Carlota Monroy Laurent Hébert-Dufresne Lori Stevens Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and housing improvements has been shown to yield lasting results. However, the additional resources and personnel required by such an intervention likely hinders its widespread adoption. One solution to this problem would be to target only a subset of houses in a community while still eliminating enough infestations to interrupt disease transfer. Here we develop a sequential sampling framework that adapts to information specific to a community as more houses are visited, thereby allowing us to efficiently find homes with domiciliary vectors while minimizing sampling bias. The method fits Bayesian geostatistical models to make spatially informed predictions, while gradually transitioning from prioritizing houses based on prediction uncertainty to targeting houses with a high risk of infestation. A key feature of the method is the use of a single exploration parameter, α, to control the rate of transition between these two design targets. In a simulation study using empirical data from five villages in southeastern Guatemala, we test our method using a range of values for α, and find it can consistently select fewer homes than random sampling, while still bringing the village infestation rate below a given threshold. We further find that when additional socioeconomic information is available, much larger savings are possible, but that meeting the target infestation rate is less consistent, particularly among the less exploratory strategies. Our results suggest new options for implementing long-term T. dimidiata control. |
format |
Article in Journal/Newspaper |
author |
B K M Case Jean-Gabriel Young Daniel Penados Carlota Monroy Laurent Hébert-Dufresne Lori Stevens |
author_facet |
B K M Case Jean-Gabriel Young Daniel Penados Carlota Monroy Laurent Hébert-Dufresne Lori Stevens |
author_sort |
B K M Case |
title |
Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
title_short |
Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
title_full |
Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
title_fullStr |
Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
title_full_unstemmed |
Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata. |
title_sort |
spatial epidemiology and adaptive targeted sampling to manage the chagas disease vector triatoma dimidiata. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2022 |
url |
https://doi.org/10.1371/journal.pntd.0010436 https://doaj.org/article/375a39c117444e0fae284a57d8ca620e |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 16, Iss 6, p e0010436 (2022) |
op_relation |
https://doi.org/10.1371/journal.pntd.0010436 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0010436 https://doaj.org/article/375a39c117444e0fae284a57d8ca620e |
op_doi |
https://doi.org/10.1371/journal.pntd.0010436 |
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PLOS Neglected Tropical Diseases |
container_volume |
16 |
container_issue |
6 |
container_start_page |
e0010436 |
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