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Martín-Sánchez M, Wu P, Adam DC, Yang B, Lim WW, Lin Y, Lau EH, Sullivan SG, Leung GM, Cowling BJ. An observational study on imported COVID-19 cases in Hong Kong during mandatory on-arrival hotel quarantine. PUBLIC HEALTH IN PRACTICE 2024; 8:100525. [PMID: 39050010 PMCID: PMC11267049 DOI: 10.1016/j.puhip.2024.100525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 05/23/2024] [Accepted: 06/05/2024] [Indexed: 07/27/2024] Open
Abstract
Background Hong Kong enforced stringent travel restrictions during the COVID-19 pandemic. Understanding the characteristics of imported COVID-19 cases is important for establishing evidence-based control measures. Methods Retrospective cohort study summarising the characteristics of imported cases detected in Hong Kong between 13 November 2020 and 31 January 2022, when compulsory quarantine was implemented. Findings A total of 2269 imported COVID-19 cases aged 0-85 years were identified, of which 48.6 % detected on arrival. A shorter median delay from arrival to isolation was observed in Delta and Omicron cases (3 days) than in ancestral strain and other variants cases (12 days; p < 0.001). Lower Ct values at isolation were observed in Omicron cases than in ancestral strain or other variants cases. No Omicron cases were detected beyond 14 days after arrival. Cases detected after 14 days of quarantine (n=58, 2.6 %) were more likely asymptomatic at isolation and had higher Ct value during isolation, some of them indicating re-positivity or post-arrival infections. Conclusions Testing inbound travellers at arrival and during quarantine can detect imported cases early, but may not prevent all COVID-19 introductions into the community. Public health measures should be adapted in response to the emergence of SARS-CoV-2 variants based on evidence from ongoing surveillance.
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Affiliation(s)
- Mario Martín-Sánchez
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited (D4H), Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Dillon C. Adam
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Bingyi Yang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Wey Wen Lim
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yun Lin
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Eric H.Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited (D4H), Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Sheena G. Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, and Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Department of Epidemiology, University of California, Los Angeles, USA
| | - Gabriel M. Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited (D4H), Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited (D4H), Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
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Liu Y, Yin Y, Ward MP, Li K, Chen Y, Duan M, Wong PPY, Hong J, Huang J, Shi J, Zhou X, Chen X, Xu J, Yuan R, Kong L, Zhang Z. Optimization of Screening Strategies for COVID-19: Scoping Review. JMIR Public Health Surveill 2024; 10:e44349. [PMID: 38412011 PMCID: PMC10933748 DOI: 10.2196/44349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 06/29/2023] [Accepted: 11/21/2023] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND COVID-19 screening is an effective nonpharmaceutical intervention for identifying infected individuals and interrupting viral transmission. However, questions have been raised regarding its effectiveness in controlling the spread of novel variants and its high socioeconomic costs. Therefore, the optimization of COVID-19 screening strategies has attracted great attention. OBJECTIVE This review aims to summarize the evidence and provide a reference basis for the optimization of screening strategies for the prevention and control of COVID-19. METHODS We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. We conducted a scoping review of the present publications on the optimization of COVID-19 screening strategies. We searched the PubMed, Web of Science, and Elsevier ScienceDirect databases for publications up to December 31, 2022. English publications related to screening and testing strategies for COVID-19 were included. A data-charting form, jointly developed by 2 reviewers, was used for data extraction according to the optimization directions of the screening strategies. RESULTS A total of 2770 unique publications were retrieved from the database search, and 95 abstracts were retained for full-text review. There were 62 studies included in the final review. We summarized the results in 4 major aspects: the screening population (people at various risk conditions such as different regions and occupations; 12/62, 19%), the timing of screening (when the target population is tested before travel or during an outbreak; 12/62, 19%), the frequency of screening (appropriate frequencies for outbreak prevention, outbreak response, or community transmission control; 6/62, 10%), and the screening and detection procedure (the choice of individual or pooled detection and optimization of the pooling approach; 35/62, 56%). CONCLUSIONS This review reveals gaps in the optimization of COVID-19 screening strategies and suggests that a number of factors such as prevalence, screening accuracy, effective allocation of resources, and feasibility of strategies should be carefully considered in the development of future screening strategies.
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Affiliation(s)
- Yuanhua Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yun Yin
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Michael P Ward
- Sydney School of Veterinary Science, The University of Sydney, NSW, Australia
| | - Ke Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Mengwei Duan
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | | | - Jie Hong
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jiaqi Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jin Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xuan Zhou
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | - Xi Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jiayao Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Rui Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lingcai Kong
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | - Zhijie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
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Lou J, Lim NWH, Cai CGX, Dickens BSL, Huynh VA, Wee HL. Cost benefit analysis of alternative testing and quarantine policies for travelers for infection control: A case study of Singapore during the COVID-19 pandemic. Front Public Health 2023; 11:1101986. [PMID: 36908469 PMCID: PMC9996245 DOI: 10.3389/fpubh.2023.1101986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/23/2023] [Indexed: 02/25/2023] Open
Abstract
Background Border control mitigates local infections but bears a heavy economic cost, especially for tourism-reliant countries. While studies have supported the efficacy of border control in suppressing cross-border transmission, the trade-off between costs from imported and secondary cases and from lost economic activities has not been studied. This case study of Singapore during the COVID-19 pandemic aims to understand the impacts of varying quarantine length and testing strategies on the economy and health system. Additionally, we explored the impact of permitting unvaccinated travelers to address emerging equity concerns. We assumed that community transmission is stable and vaccination rates are high enough that inbound travelers are not dissuaded from traveling. Methods The number of travelers was predicted considering that longer quarantine reduces willingness to travel. A micro-simulation model predicted the number of COVID-19 cases among travelers, the resultant secondary cases, and the probability of being symptomatic in each group. The incremental net monetary benefit (INB) of Singapore was quantified under each border-opening policy compared to pre-opening status, based on tourism receipts, cost/profit from testing and quarantine, and cost and health loss due to COVID-19 cases. Results Compared to polymerase chain reaction (PCR), rapid antigen test (ART) detects fewer imported cases but results in fewer secondary cases. Longer quarantine results in fewer cases but lower INB due to reduced tourism receipts. Assuming the proportion of unvaccinated travelers is small (8% locally and 24% globally), allowing unvaccinated travelers will accrue higher INB without exceeding the intensive care unit (ICU) capacity. The highest monthly INB from all travelers is $2,236.24 m, with 46.69 ICU cases per month, achieved with ARTs at pre-departure and on arrival without quarantine. The optimal policy in terms of highest INB is robust under changes to various model assumptions. Among all cost-benefit components, the top driver for INB is tourism receipts. Conclusions With high vaccination rates locally and globally alongside stable community transmission, opening borders to travelers regardless of vaccination status will increase economic growth in the destination country. The caseloads remain manageable without exceeding ICU capacity, and costs of cases are offset by the economic value generated from travelers.
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Affiliation(s)
- Jing Lou
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Nigel Wei-Han Lim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | | | - Borame Sue Lee Dickens
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Vinh Anh Huynh
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Hwee-Lin Wee
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Singapore
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