Research protocol of Proportion, clinical sequelae, and risk factors of SARS-CoV-2 Omicron variant reinfection in Hong Kong children: a population-level observational study

doi:10.21203/rs.3.rs-4330714/v1

Background:

The rapid spread of the SARS-CoV-2 Omicron variant has led to significant public health concerns, particularly regarding reinfection rates among children. The Omicron subvariants BA.4 and BA.5 have shown differences in infection dynamics compared to earlier strains. Understanding the proportion of reinfections, associated clinical sequelae, and risk factors influencing disease severity in this vulnerable population is critical. This study addresses these concerns by analyzing population-level data from Hong Kong children.

Methods:

This retrospective cohort study will utilize electronic health records from the Hospital Authority and vaccination data from the Department of Health in Hong Kong. Participants will include children aged 0-18 years with confirmed SARS-CoV-2 infections. The study will identify reinfection cases and compare clinical outcomes between initial infections and reinfections. Data analysis will involve descriptive statistics, logistic regression models, and Kaplan-Meier survival analysis to assess the risk factors and clinical outcomes associated with reinfection.

Discussion:

The findings from this study are expected to provide essential insights into the burden of SARS-CoV-2 reinfections among children, mainly focusing on the Omicron BA.4 and BA.5 subvariants. Health authorities can better tailor public health interventions and vaccination strategies by understanding the frequency of reinfections and their clinical impacts. This study will contribute to the global understanding of COVID-19's evolving epidemiology and help mitigate the ongoing impacts of the pandemic on children’s health.

Trial registration: retrospectively registered.

Omicron variant

Reinfection

Risk factor

Clinical sequelae

Hong Kong children

This study provides new epidemiological data on the rate and severity of SARS-CoV-2 Omicron reinfections among Hong Kong children, a demographic less studied in previous COVID-19 research.
By suggesting the potential for a longitudinal follow-up, this research underscores the importance of understanding long-term health outcomes in children affected by COVID-19.
This work highlights challenges and solutions related to data integration and accuracy in health information systems, offering a methodological blueprint for similar epidemiological studies.

As of April 12, 2023, 762,791,152 confirmed cases of COVID-19, including 6,897,025 deaths, have been reported to the World Health Organization (WHO) globally ⁽¹⁾. The epidemic has caused a significant negative impact on healthcare systems and socio-economic activities around the world ⁽²⁾. SARS-CoV-2 is a mutation-prone RNA virus, so antibodies in recovered individuals do not ensure adequate protection against reinfection ⁽³⁾. In August 2020, the first confirmed SARS-Cov-2 reinfection case occurred in Hong Kong, 142 days after the initial infection ⁽⁴⁾. Since then, reinfection has steadily gained attention and been reported worldwide ⁽⁵⁾. The risk of reinfection with COVID-19 in children remains high because of the Omicron variant ⁽⁶⁾. Understanding Omicron variant reinfection’s proportion and clinical sequelae is crucial for guiding public health interventions and vaccination strategies, especially in vulnerable populations like children. The rapid spread of Omicron variants, especially BA.4 and BA.5, and their ability to cause reinfections even among previously infected or vaccinated individuals, underscore the need for this study.

1.1 Reinfection before Omicron variants

Most studies on COVID-19 reinfection predate Omicron. It appears that reinfections before Omicron are relatively rare. One systematic review included 11 studies showing that PCR-confirmed reinfection rates varied from 0–1.1% ⁽⁷⁾. Some studies indicated that the risk of death from SARS-CoV-2 reinfection is lower than from initial infection ⁽⁸⁾. Age, sex, and comorbidities are the main risk factors for disease severity following reinfection ^{(7, 8)}.

1.2 Omicron and reinfection

The Omicron variant has spread rapidly in many countries since 2021 ⁽⁹⁾. The Omicron variant of SARS-CoV-2 has raised concerns worldwide due to its high transmissibility and potential ability to evade immune responses ⁽¹⁰⁾.

1.2.1 Reinfection proportion

Studies of the early stages of Omicron (BA.1/2) suggested that the Omicron variant is linked to a high risk of reinfection ^{(11, 12)}. It has been found that the frequency of reinfection has increased sharply since the Omicron variant emerged and spread, which accounted for more than 4% of all confirmed COVID-19 cases at the end of February in France; by March 6 2022, the reinfection rate reached 6.8% ⁽¹³⁾. A British cohort study showed Omicron’s reinfection rate was more than ten times higher than Delta’s ⁽¹⁴⁾.

However, few relevant studies on children infected with Omicron BA.4/5 exist. The Omicron BA.5 subvariant appears to have a higher chance of reinfection than the Omicron BA.2 subvariant, regardless of vaccination status ⁽¹⁵⁾. There is no clear evidence on the reinfection rate in BA.4/ BA.5 subvariants. Determining the reinfection rates of the Omicron variant in Hong Kong children is essential to evaluate the effectiveness of natural immunity and the potential need for booster vaccinations. The study aims to comprehensively assess the proportion of reinfections among children and compare it with previous variants by analyzing population-level data.

1.2.2 Clinical Sequela

There is additional risk associated with reinfection beyond the initial infection, according to a preprinted study published on June 17 2022, ranging from hospitalization and lungs and extra-pulmonary organ sequelae, and these risks appear during both acute and post-acute infection phases, which is contrary to previous evidence from Omicron ^{(8, 16, 17)}. However, the study included data until April 4 2022 (mainly BA.1/BA.2) before BA.4/5 became popular in the US.

While reinfection rates are essential, it is equally crucial to investigate the clinical sequelae associated with Omicron variant reinfections in children. This method will help identify differences in disease severity, symptomatology, and complications compared to primary infections or infections with previous variants. It is not yet fully understood what health risks may result from reinfection. A detailed analysis of ICU admissions, hospitalizations, emergency department visits, and outpatient visits related to BA.4 or BA.5 needs to be included, as is information on the severity and sequelae of reinfections caused by these strains ⁽¹⁷⁾.

1.2.3 Risk Factors

1.2.3.1 Previous BA.1/BA.2 infection

Studies indicate that infection of the BA.1 subvariant induces a robust immune response but may not be completely protective against reinfection with the BA.2 subvariant ⁽¹⁸⁾. One preprint states that this kind of BA.2 reinfection shortly after BA.1 infection results in mild overall symptoms like the initial infection without hospitalization or death ⁽¹⁹⁾. Another preprint on BA.4 and BA.5 in Denmark released on July 18 estimated that a previous BA.2 infection was strongly protective against Ba.5 ⁽²⁰⁾.

1.2.3.2 Vaccination

Vaccination plays a crucial role in preventing SARS-CoV-2 infection and reducing the severity of the disease. Hybrid immunity, which involves the infection and vaccination of SARS-CoV-2, has attracted considerable attention and appears to provide more lasting protection ^{(21, 22)}. For BA.2 and BA.1, one preprint showed that people vaccinated twice and contracted BA.1 were well protected against subsequent BA.2 reinfection for a long time ⁽²³⁾. However, limited research has yet to be done on hybrid immunity to BA.4/5. The effectiveness of current vaccines against the Omicron variant and the impact of vaccination status on reinfection rates in children need further investigation. The continuous assessment of vaccine induction and reinfection may remain critical to real-time adjustment of vaccine schedules. This study will explore the association between vaccination status and the risk of reinfection with the Omicron variant in Hong Kong children.

1.3 The situation in Hong Kong

Hong Kong has experienced multiple COVID-19 outbreaks since 2020, and the Omicron variant has been detected in the community since 2022. The number of cases increased from about 5,000 per day in early August to 10,000 per day in early September and then stayed around 5,000 until late November 2023 ⁽²⁴⁾. After that, BA.5 dominated for a long time, reaching 40.8% on August 24 and 95.8% by October ^{(25, 26)}. As of 2024, Hong Kong has experienced multiple waves of COVID-19, with significant shifts in the pandemic’s landscape following the emergence of the Omicron variant. This highly transmissible variant has led to a substantial increase in infections, including among children. Despite high vaccination rates in the general population, the incidence of SARS-CoV-2 reinfections, particularly with the Omicron variant, has become a pressing concern for children. The health authorities have noted varying clinical sequelae associated with these reinfections, ranging from mild to severe symptoms, which has heightened the need for a focused investigation on this demographic. Current data suggest that while vaccination provides robust protection against severe disease, the risk factors associated with reinfection and the long-term health impacts on children remain insufficiently understood ⁽²⁷⁾. This situation underscores the importance of conducting comprehensive research to assess the proportion, clinical outcomes, and risk factors of Omicron reinfections among children in Hong Kong, aiding in formulating targeted public health strategies and interventions.

Although some studies have investigated Omicron reinfection, there is still limited evidence on clinical sequelae and risk factors for Omicron, especially BA.4/5. Moreover, there was no study on Omicron reinfection in Hong Kong children. Due to BA.4/5 becoming mainstream in Hong Kong, this study on reinfection related to BA.4/BA.5 presents favourable conditions.

1.4 Research Questions

This study aims to investigate the disease burden arising from SARS-COV-2 Omicron reinfection and to identify underlying risk factors for disease severity following reinfection, which include 1) the proportion of reinfections in Hong Kong children by Omicron (after January 2022), especially BA.4/5; 2) differences in clinical sequelae between initial infection and reinfection; 3) risk factors for Hong Kong children’s reinfection and severe reinfection. We can provide actionable insights for public health strategies tailored to mitigate the impacts of COVID-19 among these children.

2.1 Study Aim, Design, and Setting

This population-level observational study will start in Sep this year and end in June next year (Table 1), which aims to investigate the proportion of SARS-CoV-2 Omicron variant reinfections among children in Hong Kong, compare clinical sequelae between initial infections and reinfections and identify risk factors associated with disease severity following reinfection. To utilise a retrospective cohort design, the study will analyze electronic health records (EHRs) of children diagnosed with COVID-19, focusing on reinfections after October 2024, particularly with the Omicron BA.4 and BA.5 subvariants. This study will be conducted using data sourced from the Hospital Authority (HA) and the Department of Health (DH) in Hong Kong, which includes information on laboratory-confirmed SARS-CoV-2 Omicron cases among children ⁽²⁸⁾.

Table 1

Proposed timeline
Month	Activity
September	Study commencement, final protocol revisions
October	Data collection from HA and DH databases
November	Initial data cleaning and verification
December 2024	Data analysis: calculating reinfection rates
January 2025	Further analysis: clinical outcomes and risk factors
February	Drafting of interim report
March	Completion of main data analysis
April	Writing of the final report
May	Review and revisions of the final report
June	Submission of findings to a peer-reviewed journal

2.2 Participants

Participants will include all children aged 0 to 18 years who have tested positive for SARS-CoV-2, as recorded in the HA database from October 2024 through June 2025. These dates encompass the study’s data collection period, enabling us to track reinfections occurring after the initial infection during the defined time frame. Cases will be identified using a de-identified unique pseudo-ID, ensuring confidentiality. Reinfection cases will be defined as those with a positive SARS-CoV-2 result following a negative test, with at least 90 days between the positive tests to distinguish between persistent viral shedding and true reinfection. This period may allow us to capture data on the prevalence and outcomes of reinfections during a susceptible to infection season and beyond, providing seasonal and longitudinal insights.

2.2.1 Inclusion criteria

Participants will be included if they:

1) Are aged 0–18 years at the time of data collection.

2) Have a laboratory-confirmed positive test for SARS-CoV-2 recorded in the Hospital Authority’s database.

2.2.2 Exclusion criteria

Participants will be excluded if:

1) The initial positive test falls outside the defined cohort period from October 2024 to June 2025.

2) Infection status is ambiguous, such as having a positive test following another positive within 90 days without a confirming negative test in between, to avoid confusion with persistent viral shedding.

2.3 Data Sources and Collection

The primary data source will be HA’s Clinical Data Analysis and Reporting System (CDARS), which provides comprehensive information on laboratory-confirmed SARS-CoV-2 cases (Table 2). This source includes data on ICU admissions, inpatient admissions, emergency department visits, and outpatient consultations within 21 days of a positive test and between 22 and 180 days following a positive test. Population-based vaccination records will be sourced from DH, which administers the COVID-19 vaccination program. These records will be matched to health records using the unique pseudo-ID.

Table 2

Key resources
Resource Type	Description	Vendor/Manufacturer	Model/Catalog Number	Link
Database Access	Health records database Population-based vaccination records	Hong Kong Hospital Authority Department of Health	HA DH	Hospital Authority (ha.org.hk) Department of Health
Software	Statistical analysis software	SAS Institute Inc.	SAS/STAT	SAS/STAT
Software	Data cleaning and management	IBM	SPSS Statistics	SPSS Statistics
Equipment	Secure servers for data storage	Dell Technologies	PowerEdge	PowerEdge

2.4 Data Validation

1) Cross-Verification: Data entries will be cross-verified with different health records systems within the HA to confirm the consistency of patient test results and health outcomes.

2) Data Cleaning: Anomalies such as duplicate records, inconsistencies in date entries, and illogical data points (e.g., dates of reinfection before initial infection) will be identified and corrected.

3) Audit Trail: An audit trail will be maintained for all data handling and analysis activities, allowing for back-tracking and verifying data integrity throughout the study.

2.5 Interventions and Comparisons

The study will compare the clinical outcomes of initial infections and reinfections, focusing on the severity of symptoms, rate and duration of hospitalization, ICU admission, and long-term sequelae. We will also evaluate the impact of previous infection and vaccination status on the risk of reinfection. Vaccination data will be detailed, noting the number of doses and the interval since the last vaccination.

2.6 Outcome Measures

Clinical outcomes will be defined based on:

1) Hospitalization: Admission to a hospital following a reinfection.

2) ICU Admission: Admission to an intensive care unit due to severe manifestations of COVID-19.

3) Long-term Sequelae: Chronic conditions attributed to reinfection, documented up to six months post-recovery.

A severe case will be characterized by requiring ICU admission, mechanical ventilation, or resulting in death.

2.7 Statistical Analysis

Descriptive statistics will be used to summarize demographic characteristics, infection rates, and clinical outcomes. The proportion of reinfections will be calculated, and logistic regression models will be employed to assess the risk factors associated with reinfection and severe outcomes. Covariates will include age, sex, vaccination status (number of doses and time since last vaccination), comorbidities and previous SARS-CoV-2 infection status. Kaplan-Meier survival analysis will estimate the time to reinfection among the cohort, with censoring for the end of the study period or loss of follow-up. Hazard ratios will be adjusted for potential confounders including demographic characteristics and baseline health status. A power calculation will determine the sample size needed to achieve adequate power to detect significant differences in reinfection rates and clinical outcomes, aiming for a power of 80% and an alpha level of 0.05. Adjustments for multiple comparisons will be applied where necessary.

3.1 Expected outcomes

Large-scale population-level evidence of reinfection during the Omicron variant will be provided in this study using the available electronic health records from CDARDS and vaccination records from DH in Hong Kong. This study will report the proportion of reinfection under the Omicron variant, especially BA.4/5; And estimate the severity of reinfection compared to the first infection and the difference in clinical sequelae after 0-21 days in the acute phase and

after 22 days in the recovering phase, including the adjusted hazard ratios of excess risk for ICU admission, hospitalization, emergency department visits, and outpatient visits. Also, determine whether factors such as age, sex, and vaccination status are potential risk factors for reinfection and severe reinfection.

3.2 Clinical and Policy Implications

Reinfection is a continuing and increasingly troubling issue and a significant public health issue regarding the disease burden. The number of SARS-COV-2 infections and reinfections continues to rise with the rapid spread of the Omicron variant ⁽²⁹⁾. For the increasing number of initial infected population (i.e., those eligible for reinfection), the issue of whether being infected a second time poses an additional risk is essential. The assessment of clinical sequelae in the acute and recovering phases of reinfection in this study will contribute to evaluating whether ongoing vigilance is suitable in people who have already been infected once in terms of reducing overall health risk. The findings of this study will also offer clinicians a comprehensive understanding of the extent of the risk of common clinical sequelae of Omicron variant reinfection in Hong Kong children, which will help improve the diagnosis and therapy of COVID-19 infections.

Given that SARS-CoV-2 will likely remain a challenge for years, the comprehensive evidence presented in this study will inform potential policies for developing reinfection prevention strategies that can be publicly acceptable and implemented consistently over time to prevent reinfection. At the same time, it also provides some data to support the risk assessment of reinfection. Moreover, the study will examine the relationship between patients’ vaccination status and the risk and severity of reinfection, enabling key stakeholders to use an effective prevention algorithm to predict the magnitude of future health complications caused by COVID-19 reinfection and plan healthcare resources accordingly.

3.2.1 Direct Applications

1) Public Health Messaging: Emphasize the importance of maintaining up-to-date vaccinations and observing health precautions after recovering from an initial infection.

2) Vaccination Policy: If the study confirms significantly lower reinfection rates and severity in vaccinated children, advocate for targeted vaccination campaigns focusing on children susceptible to infection.

3.2.2 Broader Influence

1) Long-term Health Planning: Insights from the study could guide long-term health policies regarding paediatric health resources, especially in preparing for and managing school outbreaks.

2) Global Health Strategies: The findings could contribute to global recommendations on paediatric COVID-19 management, supporting efforts to reduce the global burden of the disease by identifying effective mitigation strategies for children.

3.3 Limitations

3.3.1 Potential Biases and Mitigation Strategies

Anticipated Biases and Countermeasures:

Selection Bias: There is a risk that the children included in the study might not represent the general population due to the study's retrospective nature.

Mitigation: Utilize stratified random sampling to ensure a representative cohort and adjust for known confounders like age, socioeconomic status, and comorbidities in the analysis.

Information Bias: Misclassification of reinfection status due to ambiguous testing data.

Mitigation: Implement stringent criteria for defining reinfection, including confirmed negative tests between positive results, and cross-verify with multiple data sources.

3.3.2 Technological Challenges

Data Management System Limitations:

The reliability of our findings hinges significantly on the accuracy and functionality of the data management systems used by the HA in Hong Kong. Potential technological issues include:

1) Data Integration: Different systems may have non-uniform data formats, leading to difficulties in merging and analyzing data comprehensively.

2) System Downtime: Unexpected outages or maintenance of hospital IT systems could delay data retrieval and affect the timeliness of follow-up data collection.

3) Data Accuracy: Inherent limitations in the electronic health record systems, such as input errors or outdated information, could introduce errors in our data set.

We will implement rigorous data cleaning protocols and verify critical data points through secondary sources where available to reduce these risks.

3.3.3 Longitudinal Follow-Up

Potential for Longitudinal Study Extension:

While this study primarily focuses on the immediate and medium-term impacts of SARS-CoV-2 Omicron reinfections over a defined period, extending it into a longitudinal follow-up could provide invaluable insights into the long-term effects of reinfections. Such an extension would allow us to:

1) Assess Long-term Outcomes: Understand the extended clinical consequences of reinfections, such as chronic respiratory or cardiovascular complications.

2) Monitor Immunity Durability: Evaluate how long immunity lasts post-reinfection, which could inform the timing of booster vaccinations.

3) Identify Delayed Sequelae: Detect any late-emerging effects in pediatric populations that might go unnoticed in shorter studies.

We hope to enhance the robustness and applicability of our research findings, providing a solid foundation for future studies and health policy decisions.

Ethics approval and consent to participate: The Hospital Authority Hong Kong West Cluster IRB Committee has waived this study’s ethics approval and consent.

Consent for publication: Not applicable.

Availability of data and materials: Not applicable.

Competing interests: The authors declare no conflict of interest.

Funding: This work was supported by the Health and Medical Research Fund [Grant Number COVID-1903010, Project 1].

Author contributions:

Chuhan Miao: Funding; Data collection; Writing-origin. Beilei Li: Data analysis. Jianxun He: Design; Writing-revision.

Acknowledgements: The authors thank all relevant departments who helped with this research.

Zaidi AK, Singh RB. Chapter Two - Epidemiology of COVID-19. In: Zaidi AK, editor. Progress in Molecular Biology and Translational Science. 202: Academic Press; 2024. p. 25-38.
Ramalho JP, Simões DG, Aguiar P. Impact of sociodemographic and economic determinants of health on COVID-19 infection: incidence variation between reference periods. Public Health. 2023;225:305-10.
Brouqui P, Colson P, Melenotte C, Houhamdi L, Bedotto M, Devaux C, et al. COVID-19 re-infection. Eur J Clin Invest. 2021;51(5):e13537.
To KK, Hung IF, Ip JD, Chu AW, Chan WM, Tam AR, et al. Coronavirus Disease 2019 (COVID-19) Re-infection by a Phylogenetically Distinct Severe Acute Respiratory Syndrome Coronavirus 2 Strain Confirmed by Whole Genome Sequencing. Clin Infect Dis. 2021;73(9):e2946-e51.
Wang J, Kaperak C, Sato T, Sakuraba A. COVID-19 reinfection: a rapid systematic review of case reports and case series. Journal of investigative medicine. 2021;69(6):1253-5.
New Influenza Findings from Chinese University of Hong Kong Reported (Virological response to peramivir treatment in adults hospitalised for influenza-associated lower respiratory tract infections). Obesity, fitness, & wellness week. 2016:3328.
O Murchu E, Byrne P, Carty PG, De Gascun C, Keogan M, O’Neill M, et al. Quantifying the risk of SARS‐CoV‐2 reinfection over time. Reviews in medical virology. 2022;32(1):e2260-n/a.
Mensah AA, Lacy J, Stowe J, Seghezzo G, Sachdeva R, Simmons R, et al. Disease severity during SARS-COV-2 reinfection: a nationwide study. The Journal of infection. 2022;84(4):542-50.
Pulliam JRC, van Schalkwyk C, Govender N, von Gottberg A, Cohen C, Groome MJ, et al. Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa. Science (American Association for the Advancement of Science). 2022;376(6593):eabn4947-eabn.
Yadav PD, Sapkal GN, Sahay RR, Potdar VA, Deshpande GR, Patil DY, et al. Substantial immune response in Omicron infected breakthrough and unvaccinated individuals against SARS-CoV-2 variants of concern. The Journal of infection. 2022;84(5):e80-e1.
Araf Y, Akter F, Tang Yd, Fatemi R, Parvez MSA, Zheng C, et al. Omicron variant of SARS‐CoV‐2: Genomics, transmissibility, and responses to current COVID‐19 vaccines. Journal of medical virology. 2022;94(5):1825-32.
Nguyen NN, Houhamdi L, Hoang VT, Stoupan D, Fournier P-E, Raoult D, et al. High rate of reinfection with the SARS-CoV-2 Omicron variant. The Journal of infection. 2022;85(2):174-211.
Bastard J, Taisne B, Figoni J, Mailles A, Durand J, Fayad M, et al. Impact of the Omicron variant on SARS-CoV-2 reinfections in France, March 2021 to February 2022. Euro surveillance : bulletin européen sur les maladies transmissibles. 2022;27(13).
Hall VJ, Insalata F, Foulkes S, Kirwan P, Sparkes D, Atti A, et al. Effectiveness of BNT162b2 mRNA vaccine third doses and previous infection in protecting against SARS-CoV-2 infections during the Delta and Omicron variant waves; the UK SIREN cohort study September 2021 to February 2022. The Journal of infection. 2024;88(1):30-40.
Kislaya I, Casaca P, Borges V, Sousa C, Ferreira BI, Fonte A, et al. Comparative Effectiveness of COVID-19 Vaccines in Preventing Infections and Disease Progression from SARS-CoV-2 Omicron BA.5 and BA.2, Portugal. Emerging infectious diseases. 2023;29(3):569-75.
Bowe B, Xie Y, Al-Aly Z. Acute and postacute sequelae associated with SARS-CoV-2 reinfection. Nature medicine. 2022;28(11):2398-405.
Dhawan M, Saied AA, Emran TB, Choudhary OP. Emergence of omicron variant’s sublineages BA.4 and BA.5: risks assessment and possible countermeasures. New microbes and new infections. 2022;48:100997-.
Chemaitelly H, Ayoub HH, Coyle P, Tang P, Yassine HM, Al-Khatib HA, et al. Protection of Omicron sub-lineage infection against reinfection with another Omicron sub-lineage. Nature communications. 2022;13(1):4675-.
Occurrence and significance of Omicron BA.1 infection followed by BA.2 reinfection. Medical Letter on the CDC & FDA. 2022:127.
Hansen CH, Friis NU, Bager P, Stegger M, Fonager J, Fomsgaard A, et al. Risk of reinfection, vaccine protection, and severity of infection with the BA.5 omicron subvariant: a nation-wide population-based study in Denmark. The Lancet infectious diseases. 2023;23(2):167-76.
Suryawanshi R, Ott M. SARS-CoV-2 hybrid immunity: silver bullet or silver lining? Nature reviews Immunology. 2022;22(10):591-2.
Pilz S, Theiler-Schwetz V, Trummer C, Krause R, Ioannidis JPA. SARS-CoV-2 reinfections: Overview of efficacy and duration of natural and hybrid immunity. Environmental research. 2022;209:112911-.
Protection against Omicron BA.2 reinfection conferred by primary Omicron or pre-Omicron infection with and without mRNA vaccination. Vaccine Weekly. 2022:115.
Zhao S, Mok CKP, Tang YS, Chen C, Sun Y, Chong KC, et al. Inferring Incidence of Unreported SARS-CoV-2 Infections Using Seroprevalence of Open Reading Frame 8 Antigen, Hong Kong. Emerging infectious diseases. 2024;30(2):325-8.
Findings on COVID-19 Discussed by Investigators at University of Hong Kong (Divergent Trajectory of Replication and Intrinsic Pathogenicity of Sars-cov-2 Omicron Post-ba.2/5 Subvariants In the Upper and Lower Tract). Medical Letter on the CDC & FDA. 2024:130.
Brüssow H. COVID‐19: Omicron – the latest, the least virulent, but probably not the last variant of concern of SARS‐CoV‐2. Microbial biotechnology. 2022;15(7):1927-39.
Lam MCY, Lam DSY. The Omicron variant of COVID-19 and its association with croup in children: a single-centre study in Hong Kong. Hong Kong medical journal = Xianggang yi xue za zhi. 2024;30(1):44-55.
Wong CKH, Lau KTK, Au ICH, Lau EHY, Poon LLM, Hung IFN, et al. Viral burden rebound in hospitalised patients with COVID-19 receiving oral antivirals in Hong Kong: a population-wide retrospective cohort study. The Lancet infectious diseases. 2023;23(6):683-95.
Callaway E. What Omicron's BA.4 and BA.5 variants mean for the pandemic. Nature (London). 2022;606(7916):848-9.

No competing interests reported.