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

Authors
 Min, Kyung-Duk  ;  Kim, Sun-Young  ;  Cho, Yoon Young  ;  Kim, Seyoung  ;  Yeom, Joon-Sup 
Citation
 BMC PUBLIC HEALTH, Vol.23(1), 2023-09 
Article Number
 1776 
Journal Title
BMC PUBLIC HEALTH
ISSN
 1471-2458 
Issue Date
2023-09
Keywords
Rabies ; Sleeping sickness ; Disease importation
Abstract
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.
DOI
10.1186/s12889-023-16380-6
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Yeom, Joon Sup(염준섭) ORCID logo https://orcid.org/0000-0001-8940-7170
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/196483
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