Modeling the co-circulation of influenza and COVID-19 in Hong Kong, China

After abandoning the zero-case strategy for COVID-19 in December 2022 in mainland China, the Hong Kong Special Administrative Region of China (HKSAR) has undergone an anticipated surge of the prevalence of COVID-19, as well as other influenzas, such as influenza A/H1N1, influenza A/H3N2, and influenza B as well. Noteworthy, people are usually concerned about the mutual influences between two families of respiratory viruses, like co-circulation or co-infection. We fitted a unified model to weekly reported severe COVID-19 cases and the confirmed influenza A laboratory cases in HKSAR, respectively, using the R package POMP to obtain the best fitting and parameter estimates. The reconstructed transmission rates of the COVID-19 (/influenza A) versus the weekly reported influenza A (/COVID-19) confirmations between April 2022 and April 2024 were also compared. Our numerical results suggest that influenza confirmations remained either at a very low level or were absent before 2023, while starting from 2023, the influenza epidemic re-emerged as expected because of the resumption of international travels and other social communications. Besides, the peak of influenza cases in April 2023 favored the form of the peak of COVID-19 between May–June, 2023. Additionally, during the sudden abolishment of the zero-case policy in mainland China (December 2022 to January 2023), we estimated that there were approximately 381 cases imported from mainland China into HKSAR. We estimated the potential number of imported COVID-19 severe cases from mainland China to Hong Kong and revealed some potential population-level interference between the two families of respiratory viruses.

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Publication Details

Journal
Advances in Continuous and Discrete Models
Published
2024-09-02
DOI
https://doi.org/10.1186/s13662-024-03830-7
Citations
2
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.79

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article

Modeling the co-circulation of influenza and COVID-19 in Hong Kong, China

Qiong Li, Zhihang Peng, Daihai He, Wen Li et al.
2 citations
Advances in Continuous and Discrete Models
COVID-19 epidemiological studies
0.79
article

Modeling the co-circulation of influenza and COVID-19 in Hong Kong, China

Qiong Li, Zhihang Peng, Daihai He, Wen Li, Yin Yi
article en
2 citations

Abstract

After abandoning the zero-case strategy for COVID-19 in December 2022 in mainland China, the Hong Kong Special Administrative Region of China (HKSAR) has undergone an anticipated surge of the prevalence of COVID-19, as well as other influenzas, such as influenza A/H1N1, influenza A/H3N2, and influenza B as well. Noteworthy, people are usually concerned about the mutual influences between two families of respiratory viruses, like co-circulation or co-infection. We fitted a unified model to weekly reported severe COVID-19 cases and the confirmed influenza A laboratory cases in HKSAR, respectively, using the R package POMP to obtain the best fitting and parameter estimates. The reconstructed transmission rates of the COVID-19 (/influenza A) versus the weekly reported influenza A (/COVID-19) confirmations between April 2022 and April 2024 were also compared. Our numerical results suggest that influenza confirmations remained either at a very low level or were absent before 2023, while starting from 2023, the influenza epidemic re-emerged as expected because of the resumption of international travels and other social communications. Besides, the peak of influenza cases in April 2023 favored the form of the peak of COVID-19 between May–June, 2023. Additionally, during the sudden abolishment of the zero-case policy in mainland China (December 2022 to January 2023), we estimated that there were approximately 381 cases imported from mainland China into HKSAR. We estimated the potential number of imported COVID-19 severe cases from mainland China to Hong Kong and revealed some potential population-level interference between the two families of respiratory viruses.

Advances in Continuous and Discrete ModelsVol. 2024(1)
Beijing Normal-Hong Kong Baptist University (CN), Hong Kong Baptist University (HK), Hong Kong Polytechnic University (HK), Chinese Center For Disease Control and Prevention (CN), Beijing Normal University (CN), Nanjing Medical University (CN)
National Science Foundation, National Natural Science Foundation of China, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 31%
COVID-19 epidemiological studies
0.79
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