Post-pandemic excess mortality of COVID-19 in Hong Kong: a retrospective study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: As the COVID-19 pandemic shifted into the post-pandemic period in early 2023, following the COVID-19 normalization with relaxation of stringent control measures and high vaccination coverage in Hong Kong, its long-term impact on mortality remains challenging with necessary needs of data-driven insights. This study examined the pattern of post-pandemic excess mortality in Hong Kong. Methods: We analyzed weekly inpatient death data from public hospitals from January 1, 2013, to June 1, 2024, using a mixed model with over-dispersed Poisson regression. Expected mortality was estimated as the difference between observed mortality and baseline derived from pre-pandemic data. Age-stratified analyses of overall and cause-specific mortality were conducted across the pre-Omicron pandemic, Omicron, and post-pandemic periods. Findings: In the post-pandemic period, the excess mortality declined but remained six-fold higher (37.66 [95% CI: 32.72-42.60] per 100,000) than pre-Omicron level, maintaining significance after adjusting for age (32.79 [95% CI: 28.13-37.46] per 100,000). The older population experienced sustained excess mortality, with crude estimates of 100.51 and 586.74 per 100,000 among those aged 65-79 years and ≥80 years, respectively, primarily due to respiratory diseases. Younger population showed near-zero overall excess mortality, whereas increased excess mortality among them occurred in heart disease, cerebrovascular disease, and injuries. Interpretation: Our findings highlight the lasting mortality impact of pandemic among vulnerable populations, specifically the older population, possibly due to the post-COVID conditions and circulating COVID-19, suggesting the need for targeted interventions for this group. Funding: Health and Medical Research Fund.
Institutions: Chinese University of Hong Kong, London School of Hygiene & Tropical Medicine, Laboratory of Data Discovery for Health, University of Hong Kong, UCL School of Pharmacy, University College London, Tianjin Medical University, University of Pittsburgh, Kwong Wah Hospital, Chinese University of Hong Kong, Shenzhen
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,250
Awards: Epidemic intelligence and a data informed risk assessment system to inform policy decisions critical for maintaining systems control of COVID-19 in strategies to enhance recovery, Investigation of Hong Kong’s early detection, assessment and response (S-EDAR) system to the new emerging infectious disease outbreak COVID-19, Innovations in surveillance to predict next influenza outbreak and epidemic severity
OpenAlex ID: W4409718382
