Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data.
Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which ma...
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ftdoajarticles:oai:doaj.org/article:1171df1ba7fb433ab0f1023f4c04755f 2023-05-15T15:06:36+02:00 Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. Ari Whiteman Michael R Desjardins Gilberto A Eskildsen Jose R Loaiza 2019-09-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0007266 https://doaj.org/article/1171df1ba7fb433ab0f1023f4c04755f EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0007266 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007266 https://doaj.org/article/1171df1ba7fb433ab0f1023f4c04755f PLoS Neglected Tropical Diseases, Vol 13, Iss 9, p e0007266 (2019) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2019 ftdoajarticles https://doi.org/10.1371/journal.pntd.0007266 2022-12-31T07:48:36Z Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 13 9 e0007266 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Ari Whiteman Michael R Desjardins Gilberto A Eskildsen Jose R Loaiza Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales. |
format |
Article in Journal/Newspaper |
author |
Ari Whiteman Michael R Desjardins Gilberto A Eskildsen Jose R Loaiza |
author_facet |
Ari Whiteman Michael R Desjardins Gilberto A Eskildsen Jose R Loaiza |
author_sort |
Ari Whiteman |
title |
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
title_short |
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
title_full |
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
title_fullStr |
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
title_full_unstemmed |
Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data. |
title_sort |
detecting space-time clusters of dengue fever in panama after adjusting for vector surveillance data. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2019 |
url |
https://doi.org/10.1371/journal.pntd.0007266 https://doaj.org/article/1171df1ba7fb433ab0f1023f4c04755f |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 13, Iss 9, p e0007266 (2019) |
op_relation |
https://doi.org/10.1371/journal.pntd.0007266 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007266 https://doaj.org/article/1171df1ba7fb433ab0f1023f4c04755f |
op_doi |
https://doi.org/10.1371/journal.pntd.0007266 |
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PLOS Neglected Tropical Diseases |
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13 |
container_issue |
9 |
container_start_page |
e0007266 |
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1766338171709161472 |