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Reaction to the COVID-19 pandemic in Seoul with biostatistics

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Authors

Jung, Seungpil; Hwang, Seung-Sik; Kim, Kyoung-Nam; Lee, Woojoo

Issue Date
2022-09
Publisher
Elsevier
Citation
Infectious Disease Modelling, Vol.7 No.3, pp.419-429
Abstract
This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic. First, we focus on short-term fore-casting for the number of new confirmed cases and severe cases. Second, we focus on understanding how much of the current infections has been affected by external influx from neighborhood areas or internal transmission within the area. This understanding may be important because it is linked to the government policy determining non-pharmaceutical interventions. To obtain the decomposition of the effect, districts of Seoul should be considered simultaneously, and multivariate time series models are used. Third, we focus on predicting the number of new weekly confirmed cases for each district in Seoul. This detailed prediction may be important to the government policy on resource allocation. We consider an ensemble method to overcome poor prediction performance of simple models. This paper presents the methodological details and analysis results of the study.(c) 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
ISSN
2468-0427
URI
https://hdl.handle.net/10371/185071
DOI
https://doi.org/10.1016/j.idm.2022.06.009
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