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Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases

BACKGROUND: There have been many prediction studies for imported infectious diseases, employing air-travel volume or the importation risk (IR) index, which is the product of travel-volume and disease burden in the source countries, as major predictors. However, there is a lack of studies validating...

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Autores principales: Min, Kyung-Duk, Kim, Sun-Young, Cho, Yoon Young, Kim, Seyoung, Yeom, Joon-Sup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496286/
https://www.ncbi.nlm.nih.gov/pubmed/37700251
http://dx.doi.org/10.1186/s12889-023-16380-6
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author Min, Kyung-Duk
Kim, Sun-Young
Cho, Yoon Young
Kim, Seyoung
Yeom, Joon-Sup
author_facet Min, Kyung-Duk
Kim, Sun-Young
Cho, Yoon Young
Kim, Seyoung
Yeom, Joon-Sup
author_sort Min, Kyung-Duk
collection PubMed
description BACKGROUND: There have been many prediction studies for imported infectious diseases, employing air-travel volume or the importation risk (IR) index, which is the product of travel-volume and disease burden in the source countries, as major predictors. However, there is a lack of studies validating the predictability of the variables especially for infectious diseases that have rarely been reported. In this study, we analyzed the prediction performance of the IR index and air-travel volume to predict disease importation. METHODS: Rabies and African trypanosomiasis were used as target diseases. The list of rabies and African trypanosomiasis importation events, annual air-travel volume between two specific countries, and incidence of rabies and African trypanosomiasis in the source countries were obtained from various databases. RESULTS: Logistic regression analysis showed that IR index was significantly associated with rabies importation risk (p value < 0.001), but the association with African trypanosomiasis was not significant (p value = 0.923). The univariable logistic regression models showed reasonable prediction performance for rabies (area under curve for Receiver operating characteristic [AUC] = 0.734) but poor performance for African trypanosomiasis (AUC = 0.641). CONCLUSIONS: Our study found that the IR index cannot be generally applicable for predicting rare importation events. However, it showed the potential utility of the IR index by suggesting acceptable performance in rabies models. Further studies are recommended to explore the generalizability of the IR index’s applicability and to propose disease-specific prediction models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16380-6.
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spelling pubmed-104962862023-09-13 Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases Min, Kyung-Duk Kim, Sun-Young Cho, Yoon Young Kim, Seyoung Yeom, Joon-Sup BMC Public Health Research BACKGROUND: There have been many prediction studies for imported infectious diseases, employing air-travel volume or the importation risk (IR) index, which is the product of travel-volume and disease burden in the source countries, as major predictors. However, there is a lack of studies validating the predictability of the variables especially for infectious diseases that have rarely been reported. In this study, we analyzed the prediction performance of the IR index and air-travel volume to predict disease importation. METHODS: Rabies and African trypanosomiasis were used as target diseases. The list of rabies and African trypanosomiasis importation events, annual air-travel volume between two specific countries, and incidence of rabies and African trypanosomiasis in the source countries were obtained from various databases. RESULTS: Logistic regression analysis showed that IR index was significantly associated with rabies importation risk (p value < 0.001), but the association with African trypanosomiasis was not significant (p value = 0.923). The univariable logistic regression models showed reasonable prediction performance for rabies (area under curve for Receiver operating characteristic [AUC] = 0.734) but poor performance for African trypanosomiasis (AUC = 0.641). CONCLUSIONS: Our study found that the IR index cannot be generally applicable for predicting rare importation events. However, it showed the potential utility of the IR index by suggesting acceptable performance in rabies models. Further studies are recommended to explore the generalizability of the IR index’s applicability and to propose disease-specific prediction models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16380-6. BioMed Central 2023-09-12 /pmc/articles/PMC10496286/ /pubmed/37700251 http://dx.doi.org/10.1186/s12889-023-16380-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Min, Kyung-Duk
Kim, Sun-Young
Cho, Yoon Young
Kim, Seyoung
Yeom, Joon-Sup
Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title_full Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title_fullStr Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title_full_unstemmed Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title_short Potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
title_sort potential applicability of the importation risk index for predicting the risk of rarely imported infectious diseases
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496286/
https://www.ncbi.nlm.nih.gov/pubmed/37700251
http://dx.doi.org/10.1186/s12889-023-16380-6
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