Changes in all-cause and cause-specific excess mortality before and after the Omicron outbreak of COVID-19 in Hong Kong.

Background: While coronavirus 2019 (COVID-19) deaths were generally underestimated in many countries, Hong Kong may show a different trend of excess mortality due to stringent measures, especially for deaths related to respiratory diseases. Nevertheless, the Omicron outbreak in Hong Kong evolved into a territory-wide transmission, similar to other settings such as Singapore, South Korea, and recently, mainland China. We hypothesized that the excess mortality would differ substantially before and after the Omicron outbreak. Methods: We conducted a time-series analysis of daily deaths stratified by age, reported causes, and epidemic wave. We determined the excess mortality from the difference between observed and expected mortality from 23 January 2020 to 1 June 2022 by fitting mortality data from 2013 to 2019. Results: During the early phase of the pandemic, the estimated excess mortality was -19.92 (95% confidence interval (CI) = -29.09, -10.75) and -115.57 (95% CI = -161.34, -69.79) per 100 000 population overall and for the elderly, respectively. However, the overall excess mortality rate was 234.08 (95% CI = 224.66, 243.50) per 100 000 population overall and as high as 928.09 (95% CI = 885.14, 971.04) per 100 000 population for the elderly during the Omicron epidemic. We generally observed negative excess mortality rates of non-COVID-19 respiratory diseases before and after the Omicron outbreak. In contrast, increases in excess mortality were generally reported in non-respiratory diseases after the Omicron outbreak. Conclusions: Our results highlighted the averted mortality before 2022 among the elderly and patients with non-COVID-19 respiratory diseases, due to indirect benefits from stringent non-pharmaceutical interventions. The high excess mortality during the Omicron epidemic demonstrated a significant impact from the surge of COVID-19 infections in a SARS-CoV-2 infection-naive population, particularly evident in the elderly group.

Relationship between antidepressants and severity of SARS-CoV-2 Omicron infection: a retrospective cohort study using real-world data

Background Few studies have used real-world data to evaluate the impact of antidepressant use on the risk of developing severe outcomes after SARS-CoV-2 Omicron infection. Methods This is a retrospective cohort study using propensity-score matching to examine the relationship between antidepressant use and COVID-19 severity. Inpatient and medication records of all adult COVID-19 patients in Hong Kong during the Omicron-predominated period were obtained. Severe clinical outcomes including intensive care unit admission and inpatient death after the first positive results of reverse transcription polymerase chain reaction as well as a composite outcome of both were studied. Cox proportional hazard models were applied to estimate the crude and adjusted hazard ratios (HR). Findings Of 60,903 hospitalised COVID-19 patients admitted, 40,459 were included for matching, among which 3821 (9.4%) were prescribed antidepressants. The rates of intensive care unit admission, inpatient death, and the composite event were 3.9%, 25.5%, and 28.3% respectively in the unexposed group, 1.3%, 20.0%, and 21.1% respectively in the exposed group, with adjusted HR equal to 0.332 (95% CI, 0.245–0.449), 0.868 (95% CI, 0.800–0.942), and 0.786 (95% CI, 0.727–0.850) respectively. The result was generally consistent when stratified by selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs. Antidepressants with functional inhibition of acid sphingomyelinase activity, specifically fluoxetine, were also negatively associated with the outcomes. The effect of antidepressants was more apparent in female and fully vaccinated COVID-19 patients. Interpretation Antidepressant use was associated with a lower risk of severe COVID-19. The findings support the continuation of antidepressants in patients with COVID-19, and provide evidence for the treatment potential of antidepressants for severe COVID-19. Funding This research was supported by Health and Medical Research Fund [grant numbers COVID190105, COVID19F03, INF-CUHK-1], Collaborative Research Fund of University Grants Committee [grant numbers C4139-20G], 10.13039/501100001809National Natural Science Foundation of China (NSFC) [71974165], and Group Research Scheme from The 10.13039/501100004853Chinese University of Hong Kong.

Comparing the incubation period, serial interval, and infectiousness profile between SARS-CoV-2 Omicron and Delta variants.

In January 2022, the SARS-CoV-2 Omicron variants initiated major outbreaks and dominated the transmissions in Hong Kong, displacing an earlier outbreak seeded by the Delta variants. To provide insight into the transmission potential of the emerging variants, we aimed to compare the epidemiological characteristics of the Omicron and Delta variants. We analyzed the line-list clinical and contact tracing data of the SARS-CoV-2 confirmed cases in Hong Kong. Transmission pairs were constructed based on the individual contact history. We fitted bias-controlled models to the data to estimate the serial interval, incubation period and infectiousness profile of the two variants. Viral load data were extracted and fitted to the random effect models to investigate the potential risk modifiers for the clinical viral shedding course. Totally 14 401 confirmed cases were reported between January 1 and February 15, 2022. The estimated mean serial interval (4.4 days vs. 5.8 days) and incubation period (3.4 days vs. 3.8 days) were shorter for the Omicron than the Delta variants. A larger proportion of presymptomatic transmission was observed for the Omicron (62%) compared to the Delta variants (48%). The Omicron cases had higher mean viral load over an infection course than the Delta cases, with the elder cases appearing more infectious than the younger cases for both variants. The epidemiological features of Omicron variants were likely an obstacle to contact tracing measures, imposed as a major intervention in settings like Hong Kong. Continuously monitoring the epidemiological feature for any emerging SARS-CoV-2 variants in the future is needed to assist officials in planning measures for COVID-19 control.

Estimating the serial intervals of SARS-CoV-2 Omicron BA.4, BA.5, and BA.2.12.1 variants in Hong Kong.

Empirical evidence on the epidemiological characteristics of the emerged SARS-CoV-2 variants could shed light on the transmission potential of the virus and strategic outbreak control planning. In this study, by using contact tracing data collected during an Omicron-predominant epidemic phase in Hong Kong, we estimated the mean serial interval of SARS-CoV-2 Omicron BA.4, BA.5, and BA.2.12.1 variants at 2.8 days (95% credible interval [CrI]: 1.5, 6.7), 2.7 days (95% CrI: 2.1, 3.6), and 4.4 days (95% CrI: 2.6, 7.5), respectively, with adjustment for right truncation and sampling bias. The short serial interval for the current circulating variant indicated that outbreak mitigations through contact tracing and case isolation would be quite challenging.

Dining-Out Behavior as a Proxy for the Superspreading Potential of SARS-CoV-2 Infections: Modeling Analysis.

BACKGROUND: While many studies evaluated the reliability of digital mobility metrics as a proxy of SARS-CoV-2 transmission potential, none examined the relationship between dining-out behavior and the superspreading potential of COVID-19. OBJECTIVE: We employed the mobility proxy of dining out in eateries to examine this association in Hong Kong with COVID-19 outbreaks highly characterized by superspreading events. METHODS: We retrieved the illness onset date and contact-tracing history of all laboratory-confirmed cases of COVID-19 from February 16, 2020, to April 30, 2021. We estimated the time-varying reproduction number (Rt) and dispersion parameter (k), a measure of superspreading potential, and related them to the mobility proxy of dining out in eateries. We compared the relative contribution to the superspreading potential with other common proxies derived by Google LLC and Apple Inc. RESULTS: A total of 6391 clusters involving 8375 cases were used in the estimation. A high correlation between dining-out mobility and superspreading potential was observed. Compared to other mobility proxies derived by Google and Apple, the mobility of dining-out behavior explained the highest variability of k (ΔR-sq=9.7%, 95% credible interval: 5.7% to 13.2%) and Rt (ΔR-sq=15.7%, 95% credible interval: 13.6% to 17.7%). CONCLUSIONS: We demonstrated that there was a strong link between dining-out behaviors and the superspreading potential of COVID-19. The methodological innovation suggests a further development using digital mobility proxies of dining-out patterns to generate early warnings of superspreading events.

Relationship between antidepressants and severity of SARS-CoV-2 Omicron infection: a retrospective cohort study using real-world data.

Background: Few studies have used real-world data to evaluate the impact of antidepressant use on the risk of developing severe outcomes after SARS-CoV-2 Omicron infection. Methods: This is a retrospective cohort study using propensity-score matching to examine the relationship between antidepressant use and COVID-19 severity. Inpatient and medication records of all adult COVID-19 patients in Hong Kong during the Omicron-predominated period were obtained. Severe clinical outcomes including intensive care unit admission and inpatient death after the first positive results of reverse transcription polymerase chain reaction as well as a composite outcome of both were studied. Cox proportional hazard models were applied to estimate the crude and adjusted hazard ratios (HR). Findings: Of 60,903 hospitalised COVID-19 patients admitted, 40,459 were included for matching, among which 3821 (9.4%) were prescribed antidepressants. The rates of intensive care unit admission, inpatient death, and the composite event were 3.9%, 25.5%, and 28.3% respectively in the unexposed group, 1.3%, 20.0%, and 21.1% respectively in the exposed group, with adjusted HR equal to 0.332 (95% CI, 0.245-0.449), 0.868 (95% CI, 0.800-0.942), and 0.786 (95% CI, 0.727-0.850) respectively. The result was generally consistent when stratified by selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs. Antidepressants with functional inhibition of acid sphingomyelinase activity, specifically fluoxetine, were also negatively associated with the outcomes. The effect of antidepressants was more apparent in female and fully vaccinated COVID-19 patients. Interpretation: Antidepressant use was associated with a lower risk of severe COVID-19. The findings support the continuation of antidepressants in patients with COVID-19, and provide evidence for the treatment potential of antidepressants for severe COVID-19. Funding: This research was supported by Health and Medical Research Fund [grant numbers COVID190105, COVID19F03, INF-CUHK-1], Collaborative Research Fund of University Grants Committee [grant numbers C4139-20G], National Natural Science Foundation of China (NSFC) [71974165], and Group Research Scheme from The Chinese University of Hong Kong.

Estimation of Vaccine Effectiveness of CoronaVac and BNT162b2 Against Severe Outcomes Over Time Among Patients With SARS-CoV-2 Omicron.

Importance: Few studies have evaluated the waning of vaccine effectiveness against severe outcomes caused by SARS-CoV-2 Omicron infection. Hong Kong is providing inactivated and mRNA vaccines, but the population had limited protection from natural infections before the Omicron variant emerged. Objective: To examine the change in vaccine effectiveness against hospitalization and mortality due to the Omicron variant over time. Design, Setting, and Participants: This case-control study included adults with SARS-CoV-2 Omicron variant infection who died or were hospitalized in Hong Kong from January 1 to June 5, 2022 (ie, case participants), and adults with SARS-CoV-2 Omicron, sampled from the public health registry during the study period (ie, control participants), who were matched to case participants by propensity score. Exposures: Vaccination status of the individuals. Main Outcomes and Measures: Estimated vaccine effectiveness against death, death or hospitalization, and death among hospitalized patients. Vaccine effectiveness was calculated as 1 - adjusted odds ratio obtained by conditional logistic regression adjusted with covariates for each period following vaccination. Results: There were 32 823 case participants (25 546 [77.8%] ≥65 years; 16 930 [47.4%] female) and 131 328 control participants (100 041 [76.2%] ≥65 years; 66 625 [46.6%] female) in the sample analyzed for the death or hospitalization outcome. Vaccine effectiveness against death or hospitalization was maintained for at least 6 months after the second dose of both CoronaVac (74.0%; 95% CI, 71.8%-75.8%) and BNT162b2 (77.4%; 95% CI, 75.5%-79.0%) vaccines. Vaccine effectiveness against death in those aged 18 to 49 years was 86.4% (95% CI, 85.8%-87.0%) and 92.9% (95% CI, 92.6%-93.2%) for those receiving 2 doses of CoronaVac and BNT162b2, respectively, while for patients aged 80 years or older, it dropped to 61.4% (95% CI, 59.8%-63.2%) and 52.7% (95% CI, 50.2%-55.6%) for CoronaVac and BNT162b2, respectively. Nevertheless, overall vaccine effectiveness against death at 4 to 6 months after the third dose was greater than 90% for CoronaVac, BNT162b2, and the mixed vaccine schedule (eg, mixed vaccines: vaccine effectiveness, 92.2%; 95% CI, 89.2%-95.1%). Conclusions and Relevance: While vaccines were generally estimated to be effective against severe outcomes caused by SARS-CoV-2 Omicron infection, this analysis found that protection in older patients was more likely to wane 6 months after the second dose. Hence, a booster dose is recommended for older patients to restore immunity. This is especially critical in a setting like Hong Kong, where third-dose coverage is still insufficient among older residents.

A statistical framework for tracking the time-varying superspreading potential of COVID-19 epidemic.

Timely detection of an evolving event of an infectious disease with superspreading potential is imperative for territory-wide disease control as well as preventing future outbreaks. While the reproduction number (R) is a commonly-adopted metric for disease transmissibility, the transmission heterogeneity quantified by dispersion parameter k, a metric for superspreading potential is seldom tracked. In this study, we developed an estimation framework to track the time-varying risk of superspreading events (SSEs) and demonstrated the method using the three epidemic waves of COVID-19 in Hong Kong. Epidemiological contact tracing data of the confirmed COVID-19 cases from 23 January 2020 to 30 September 2021 were obtained. By applying branching process models, we jointly estimated the time-varying R and k. Individual-based outbreak simulations were conducted to compare the time-varying assessment of the superspreading potential with the typical non-time-varying estimate of k over a period of time. We found that the COVID-19 transmission in Hong Kong exhibited substantial superspreading during the initial phase of the epidemics, with only 1 % (95 % Credible interval [CrI]: 0.6-2 %), 5 % (95 % CrI: 3-7 %) and 10 % (95 % CrI: 8-14 %) of the most infectious cases generated 80 % of all transmission for the first, second and third epidemic waves, respectively. After implementing local public health interventions, R estimates dropped gradually and k estimates increased thereby reducing the risk of SSEs to approaching zero. Outbreak simulations indicated that the non-time-varying estimate of k may overlook the possibility of large outbreaks. Hence, an estimation of the time-varying k as a compliment of R as a monitoring of both disease transmissibility and superspreading potential, particularly when public health interventions were relaxed is crucial for minimizing the risk of future outbreaks.

Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data.

BACKGROUND: Contact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing ("unlinked cases") or described their potential roles in seeding community outbreaks. OBJECTIVE: For this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings. METHODS: We obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution. RESULTS: Time interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings. CONCLUSIONS: The unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size-implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies.

Assessing the impact of non-pharmaceutical interventions on the transmissibility and severity of COVID-19 during the first five months in the Western Pacific Region.

While most countries in the Western Pacific Region (WPR) had similar trajectories of COVID-19 from January to May, their implementations of non-pharmaceutical interventions (NPIs) differed by transmission stages. To offer a better understanding for an implementation of multidisciplinary policies in COVID-19 control, we compared the impact of NPIs by assessing the transmissibility and severity of COVID-19 in different phases of the epidemic during the first five months in WPR. In this study, we estimated the piecewise instantaneous reproduction number (R t ) and the reporting delay-adjusted case-fatality ratio (dCFR) of COVID-19 in seven WPR jurisdictions: Hong Kong Special Administrative Region, Japan, Malaysia, Shanghai, Singapore, South Korea, and Taiwan. According to the results, implementing NPIs was associated with an apparent reduction of the piecewise R t in two epidemic waves in general. However, large cluster outbreaks raised the piecewise R t to a high level. We also observed relaxing the NPIs could result in an increase of R t . The estimated dCFR ranged from 0.09% to 1.59% among the jurisdictions, except in Japan where an estimate of 5.31% might be due to low testing efforts. To conclude, in conjunction with border control measures to reduce influx of imported cases which might cause local outbreaks, other NPIs including social distancing measures along with case finding by rapid tests are also necessary to prevent potential large cluster outbreaks and transmissions from undetected cases. A comparatively lower CFR may reflect the health system capacity of these jurisdictions. In order to keep track of sustained disease transmission due to resumption of economic activities, a close monitoring of disease transmissibility is recommended in the relaxation phase. The report of transmission of SARS CoV-2 to pets in Hong Kong and to mink in farm outbreaks highlight for the control of COVID-19 and emerging infectious disease, the One Health approach is critical in understanding and accounting for how human, animals and environment health are intricately connected.