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

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

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has 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
Creator	Wang, Xin Wang, Kai He, Daihai Cao, Peihua Ran, Jinjun Zhao, Shi Yang, Guangpu Chong, Marc Musa, Salihu Tang, Xiujuan Wang, Maggie Zee, Benny Liang, Xue
topic	covid:d5ebec1e407d12d336e105f843b35977e0d3d8b2#this
Source	Medline; PMC
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.
has issue date	2020-06-17(xsd:dateTime)
bibo:doi	10.2147/idr.s258035
bibo:pmid	32606834
has license	cc-by-nc
sha1sum (hex)	d5ebec1e407d12d336e105f843b35977e0d3d8b2
schema:url	https://doi.org/10.2147/idr.s258035
resource representing a document's 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
has PubMed Central identifier	PMC7308762
has PubMed identifier	32606834
schema:publication	Infect Drug Resist
resource representing a document's body	covid:d5ebec1e407d12d336e105f843b35977e0d3d8b2#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/d5ebec1e407d12d336e105f843b35977e0d3d8b2
is schema:about of	named entity 'outbreak' named entity 'targeting' named entity 'hypothetical' named entity 'awareness' named entity '95% CI' named entity 'total' named entity 'predicted' named entity 'Outbreak' named entity 'EMERGENT' named entity 'HIGHLY CONTAGIOUS DISEASE' named entity 'REPORTING' named entity 'FOUND' named entity 'OCCURRED' named entity 'total' named entity 'burden' named entity 'measures' named entity 'Measles' named entity 'outbreak' named entity 'absent' named entity 'Conclusion' named entity 'level' named entity 'Methods' named entity 'program' named entity 'lags' named entity 'HKIA' named entity 'public enquiry' named entity 'highly contagious disease' named entity '95% CI' named entity 'March 23' named entity 'basic reproduction number' named entity 'Measles Outbreak' named entity 'Public Awareness' named entity 'Hong Kong International Airport' named entity '2019' named entity 'measles' named entity 'measles' named entity 'developing countries' named entity 'serial interval' named entity 'causality' named entity 'March 23' named entity 'vaccination program' named entity 'HKIA' named entity 'effective reproduction number' named entity 'coefficient of determination' named entity 'Centre for Health Protection' named entity 'March 23' named entity 'vaccination' named entity 'symptom' named entity 'vaccine' named entity 'prodrome' named entity 'effective reproduction number' named entity 'prodrome' named entity 'quarantine' named entity 'Hong Kong' named entity 'transmissibility' named entity 'regression model' named entity 'Infection' named entity 'April 1' named entity 'measles' named entity 'fever' named entity 'HKIA' named entity 'virus' named entity 'basic reproduction number' named entity 'Hong Kong' named entity 'SARS' named entity 'immunization' named entity 'time interval'

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