Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach.
The situation of human rabies in Thailand has gradually declined over the past four decades. However, the number of animal rabies cases has slightly increased in the last ten years. This study thus aimed to describe the characteristics of animal rabies between 2017 and 2018 in Thailand in which the...
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ftdoajarticles:oai:doaj.org/article:067e26d5051e475887f526aa9ace8b42 2023-12-03T10:18:14+01:00 Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. Weerapong Thanapongtharm Sarin Suwanpakdee Arun Chumkaeo Marius Gilbert Anuwat Wiratsudakul 2021-12-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0009980 https://doaj.org/article/067e26d5051e475887f526aa9ace8b42 EN eng Public Library of Science (PLoS) https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0009980&type=printable https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009980 https://doaj.org/article/067e26d5051e475887f526aa9ace8b42 PLoS Neglected Tropical Diseases, Vol 15, Iss 12, p e0009980 (2021) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2021 ftdoajarticles https://doi.org/10.1371/journal.pntd.0009980 2023-11-05T01:37:23Z The situation of human rabies in Thailand has gradually declined over the past four decades. However, the number of animal rabies cases has slightly increased in the last ten years. This study thus aimed to describe the characteristics of animal rabies between 2017 and 2018 in Thailand in which the prevalence was fairly high and to quantify the association between monthly rabies occurrences and explainable variables using the generalized additive models (GAMs) to predict the spatial risk areas for rabies spread. Our results indicate that the majority of animals affected by rabies in Thailand are dogs. Most of the affected dogs were owned, free or semi-free roaming, and unvaccinated. Clusters of rabies were highly distributed in the northeast, followed by the central and the south of the country. Temporally, the number of cases gradually increased after June and reached a peak in January. Based on our spatial models, human and cattle population density as well as the spatio-temporal history of rabies occurrences, and the distances from the cases to the secondary roads and country borders are identified as the risk factors. Our predictive maps are applicable for strengthening the surveillance system in high-risk areas. Nevertheless, the identified risk factors should be rigorously considered and integrated into the strategic plans for the prevention and control of animal rabies in Thailand. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 15 12 e0009980 |
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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 Weerapong Thanapongtharm Sarin Suwanpakdee Arun Chumkaeo Marius Gilbert Anuwat Wiratsudakul Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
The situation of human rabies in Thailand has gradually declined over the past four decades. However, the number of animal rabies cases has slightly increased in the last ten years. This study thus aimed to describe the characteristics of animal rabies between 2017 and 2018 in Thailand in which the prevalence was fairly high and to quantify the association between monthly rabies occurrences and explainable variables using the generalized additive models (GAMs) to predict the spatial risk areas for rabies spread. Our results indicate that the majority of animals affected by rabies in Thailand are dogs. Most of the affected dogs were owned, free or semi-free roaming, and unvaccinated. Clusters of rabies were highly distributed in the northeast, followed by the central and the south of the country. Temporally, the number of cases gradually increased after June and reached a peak in January. Based on our spatial models, human and cattle population density as well as the spatio-temporal history of rabies occurrences, and the distances from the cases to the secondary roads and country borders are identified as the risk factors. Our predictive maps are applicable for strengthening the surveillance system in high-risk areas. Nevertheless, the identified risk factors should be rigorously considered and integrated into the strategic plans for the prevention and control of animal rabies in Thailand. |
format |
Article in Journal/Newspaper |
author |
Weerapong Thanapongtharm Sarin Suwanpakdee Arun Chumkaeo Marius Gilbert Anuwat Wiratsudakul |
author_facet |
Weerapong Thanapongtharm Sarin Suwanpakdee Arun Chumkaeo Marius Gilbert Anuwat Wiratsudakul |
author_sort |
Weerapong Thanapongtharm |
title |
Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
title_short |
Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
title_full |
Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
title_fullStr |
Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
title_full_unstemmed |
Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach. |
title_sort |
current characteristics of animal rabies cases in thailand and relevant risk factors identified by a spatial modeling approach. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doi.org/10.1371/journal.pntd.0009980 https://doaj.org/article/067e26d5051e475887f526aa9ace8b42 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 15, Iss 12, p e0009980 (2021) |
op_relation |
https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0009980&type=printable https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009980 https://doaj.org/article/067e26d5051e475887f526aa9ace8b42 |
op_doi |
https://doi.org/10.1371/journal.pntd.0009980 |
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PLOS Neglected Tropical Diseases |
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15 |
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12 |
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e0009980 |
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