A Data Driven Study on the Variant of Covid-19 in Hong Kong
DOI:
https://doi.org/10.6000/1929-6029.2022.11.06Keywords:
Variant of COVID-19, ARIMA, Non-linear regression modelAbstract
The new wave of COVID-19 in Hong Kong, China was overwhelming again by “dynamic zero” strategy and non-pharmaceutical interventions (DZ-NPIs), which makes a time challenge to control the variant of this epidemic. We describe the variant of Covid-19 in Kong Hong to the infected proportion of the population, cumulative confirmed cases, cumulative deaths and current hospitalizations by age group via statistical measure firstly, then establish time series model for fitting the accumulative confirmed cases, further to predict the trend for searching out possible turning time-points. Non-linear regression model is created to feature the deaths series, then we figure out the parameters and educe the controlling condition for this epidemic. We expect our data-driven modeling process providing some insights to the controlling strategy for the new wave of the Covid-19 variant in Hong Kong, even in the mainland of China.
References
Fu G-E, Li J, Geng P-R, et al. Comparative study on COVID-19 prevention and control forces in typical cities of Guangdong-Hong Kong-Macao Greater Bay Area from the perspective of medical treatment [J]. Chinese Journal of Bioengineering 2021; 41(12): 16.
Ma A, Parry J. When Hong Kong’s “dynamic zero” covid-19 strategy met omicron, low vaccination rates sent deaths soaring. BMJ 2022; 377. https://doi.org/10.1136/bmj.o980 DOI: https://doi.org/10.1136/bmj.o980
The Government of the Hong Kong Special Administrative Region. Together, we fight the virus! Hong Kong, China: The Government of the Hong Kong Special Administrative Region; 2022. https://www.coronavirus.gov.hk/eng/index.html.
Taylor L. Covid-19: Hong Kong reports world’s highest death rate as zero covid strategy fails. BMJ 2022; 376: o707. https://doi.org/10.1136/bmj.o707 DOI: https://doi.org/10.1136/bmj.o707
Xie M, Dong N, Zhang X, He D. Exported cases were infected on the way: A conjecture derived from analysis on Hong Kong monthly exported COVID-19 cases. International Journal of Infectious Diseases 2022; 118: 62-4. https://doi.org/10.1016/j.ijid.2022.02.027 DOI: https://doi.org/10.1016/j.ijid.2022.02.027
Men YV, Yeung CY, Yip PSF. The association between unemployment and suicide among employed and unemployed people in Hong Kong: A time-series analysis. Journal of Affective Disorders 2022; 305: 240-243. https://doi.org/10.1016/j.jad.2022.03.013 DOI: https://doi.org/10.1016/j.jad.2022.03.013
Yuan HY, Blakemore C. The impact of multiple non-pharmaceutical interventions on controlling COVID-19 outbreak without lockdown in Hong Kong: A modelling study. The Lancet Regional Health-Western Pacific 2022; 20: 100343. https://doi.org/10.1016/j.lanwpc.2021.100343 DOI: https://doi.org/10.1016/j.lanwpc.2021.100343
Li J-B, Lau EYH, Chan DKC. Why do Hong Kong parents have low intention to vaccinate their children against COVID-19? testing health belief model and theory of planned behavior in a large-scale survey. Vaccine 2022; 40(19): 2772-2780. https://doi.org/10.1016/j.vaccine.2022.03.040 DOI: https://doi.org/10.1016/j.vaccine.2022.03.040
Koh K, Tang KC, Axhausen K. Loo BP. A metropolitan-scale, three-dimensional agent-based model to assess the effectiveness of the COVID-19 Omicron wave interventions in a hyperdense city: a case study of Hong Kong. International Journal of Infectious Diseases 2022. https://doi.org/10.1016/j.ijid.2022.06.042 DOI: https://doi.org/10.1016/j.ijid.2022.06.042
Huang R, Liu M, Ding Y. Spatial-temporal distribution of COVID-19 in China and its prediction: A data-driven modeling analysis. The Journal of Infection in Developing Countries 2020; 14(03): 246-53. https://doi.org/10.3855/jidc.12585 DOI: https://doi.org/10.3855/jidc.12585
Ding Y, Gao L. An evaluation of COVID-19 in Italy: A data-driven modeling analysis. Infectious Disease Modelling. 2020; 5: 495-501. https://doi.org/10.1016/j.idm.2020.06.007 DOI: https://doi.org/10.1016/j.idm.2020.06.007
Nealon J, Cowling BJ. Omicron severity: milder but not mild. The Lancet 2022; 399(10323): 412-413. https://doi.org/10.1016/S0140-6736(22)00056-3 DOI: https://doi.org/10.1016/S0140-6736(22)00056-3
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Policy for Journals/Articles with Open Access
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
Policy for Journals / Manuscript with Paid Access
Authors who publish with this journal agree to the following terms:
- Publisher retain copyright .
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .