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Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness

BACKGROUND: Measles, a highly contagious disease, still poses a huge burden worldwide. Lately, a trend of resurgence threatened the developed countries. A measles outbreak occurred in the Hong Kong International Airport (HKIA) between March and April 2019, which infected 29 airport staff. During the...

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Autores principales: Zhao, Shi, Tang, Xiujuan, Liang, Xue, Chong, Marc K C, Ran, Jinjun, Musa, Salihu S, Yang, Guangpu, Cao, Peihua, Wang, Kai, Zee, Benny C Y, Wang, Xin, He, Daihai, Wang, Maggie H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308762/
https://www.ncbi.nlm.nih.gov/pubmed/32606834
http://dx.doi.org/10.2147/IDR.S258035
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author Zhao, Shi
Tang, Xiujuan
Liang, Xue
Chong, Marc K C
Ran, Jinjun
Musa, Salihu S
Yang, Guangpu
Cao, Peihua
Wang, Kai
Zee, Benny C Y
Wang, Xin
He, Daihai
Wang, Maggie H
author_facet Zhao, Shi
Tang, Xiujuan
Liang, Xue
Chong, Marc K C
Ran, Jinjun
Musa, Salihu S
Yang, Guangpu
Cao, Peihua
Wang, Kai
Zee, Benny C Y
Wang, Xin
He, Daihai
Wang, Maggie H
author_sort Zhao, Shi
collection PubMed
description BACKGROUND: Measles, a highly contagious disease, still poses a huge burden worldwide. Lately, a trend of resurgence threatened the developed countries. A measles outbreak occurred in the Hong Kong International Airport (HKIA) between March and April 2019, which infected 29 airport staff. During the outbreak, multiple measures were taken including daily situation updates, setting up a public enquiry platform on March 23, and an emergent vaccination program targeting unprotected staff. The outbreak was put out promptly. The effectiveness of these measures was unclear. METHODS: We quantified the transmissibility of outbreak in HKIA by the effective reproduction number, R(eff)(t), and basic reproduction number, R(0)(t). The reproduction number was modelled as a function of its determinants that were statistically examined, including lags in hospitalization, situation update, and level of public awareness. Then, we considered a hypothetical no-measure scenario when improvements in reporting and public enquiry were absent and calculated the number of infected airport staff. RESULTS: Our estimated average R(0) is 10.09 (95% CI: 1.73−36.50). We found that R(0)(t) was positively associated with lags in hospitalization and situation update, while negatively associated with the level of public awareness. The average predicted basic reproduction number, r(0), was 14.67 (95% CI: 9.01−45.32) under the no-measure scenario, which increased the average R(0) by 77.57% (95% CI: 1.71−111.15). The total number of infected staff would be 179 (IQR: 90−339, 95% CI: 23−821), namely the measure induced 8.42-fold (95% CI: 0.21−42.21) reduction in the total number of infected staff. CONCLUSION: Timely reporting on outbreak situation and public awareness measured by the number of public enquiries helped to control the outbreak.
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spelling pubmed-73087622020-06-29 Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness Zhao, Shi Tang, Xiujuan Liang, Xue Chong, Marc K C Ran, Jinjun Musa, Salihu S Yang, Guangpu Cao, Peihua Wang, Kai Zee, Benny C Y Wang, Xin He, Daihai Wang, Maggie H Infect Drug Resist Original Research BACKGROUND: Measles, a highly contagious disease, still poses a huge burden worldwide. Lately, a trend of resurgence threatened the developed countries. A measles outbreak occurred in the Hong Kong International Airport (HKIA) between March and April 2019, which infected 29 airport staff. During the outbreak, multiple measures were taken including daily situation updates, setting up a public enquiry platform on March 23, and an emergent vaccination program targeting unprotected staff. The outbreak was put out promptly. The effectiveness of these measures was unclear. METHODS: We quantified the transmissibility of outbreak in HKIA by the effective reproduction number, R(eff)(t), and basic reproduction number, R(0)(t). The reproduction number was modelled as a function of its determinants that were statistically examined, including lags in hospitalization, situation update, and level of public awareness. Then, we considered a hypothetical no-measure scenario when improvements in reporting and public enquiry were absent and calculated the number of infected airport staff. RESULTS: Our estimated average R(0) is 10.09 (95% CI: 1.73−36.50). We found that R(0)(t) was positively associated with lags in hospitalization and situation update, while negatively associated with the level of public awareness. The average predicted basic reproduction number, r(0), was 14.67 (95% CI: 9.01−45.32) under the no-measure scenario, which increased the average R(0) by 77.57% (95% CI: 1.71−111.15). The total number of infected staff would be 179 (IQR: 90−339, 95% CI: 23−821), namely the measure induced 8.42-fold (95% CI: 0.21−42.21) reduction in the total number of infected staff. CONCLUSION: Timely reporting on outbreak situation and public awareness measured by the number of public enquiries helped to control the outbreak. Dove 2020-06-17 /pmc/articles/PMC7308762/ /pubmed/32606834 http://dx.doi.org/10.2147/IDR.S258035 Text en © 2020 Zhao et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Zhao, Shi
Tang, Xiujuan
Liang, Xue
Chong, Marc K C
Ran, Jinjun
Musa, Salihu S
Yang, Guangpu
Cao, Peihua
Wang, Kai
Zee, Benny C Y
Wang, Xin
He, Daihai
Wang, Maggie H
Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title_full Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title_fullStr Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title_full_unstemmed Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title_short Modelling the Measles Outbreak at Hong Kong International Airport in 2019: A Data-Driven Analysis on the Effects of Timely Reporting and Public Awareness
title_sort modelling the measles outbreak at hong kong international airport in 2019: a data-driven analysis on the effects of timely reporting and public awareness
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308762/
https://www.ncbi.nlm.nih.gov/pubmed/32606834
http://dx.doi.org/10.2147/IDR.S258035
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