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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.
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.
Afiliación
  • Zhao S; Division of Biostatistics, JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, People's Republic of China.
  • Tang X; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, People's Republic of China.
  • Liang X; Shenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
  • Chong MKC; Department of Hematology, The 989th Hospital of the Joint Logistics Support Force of Chinese PLA, Luoyang 471031, People's Republic of China.
  • Ran J; Division of Biostatistics, JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, People's Republic of China.
  • Musa SS; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, People's Republic of China.
  • Yang G; School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, People's Republic of China.
  • Cao P; Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
  • Wang K; Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong, People's Republic of China.
  • Zee BCY; Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
  • Wang X; Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, People's Republic of China.
  • He D; Division of Biostatistics, JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, People's Republic of China.
  • Wang MH; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, People's Republic of China.
Infect Drug Resist ; 13: 1851-1861, 2020.
Article en En | MEDLINE | ID: mdl-32606834
ABSTRACT

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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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Infect Drug Resist Año: 2020 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Infect Drug Resist Año: 2020 Tipo del documento: Article