SARS-CoV-2 Omicron variants: burden of disease, impact on vaccine effectiveness and need for variant-adapted vaccines.

The highly transmissible Omicron (B.1.1.529) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first detected in late 2021. Initial Omicron waves were primarily made up of sub-lineages BA.1 and/or BA.2, BA.4, and BA.5 subsequently became dominant in mid-2022, and several descendants of these sub-lineages have since emerged. Omicron infections have generally caused less severe disease on average than those caused by earlier variants of concern in healthy adult populations, at least, in part, due to increased population immunity. Nevertheless, healthcare systems in many countries, particularly those with low population immunity, have been overwhelmed by unprecedented surges in disease prevalence during Omicron waves. Pediatric admissions were also higher during Omicron waves compared with waves of previous variants of concern. All Omicron sub-lineages exhibit partial escape from wild-type (Wuhan-Hu 1) spike-based vaccine-elicited neutralizing antibodies, with sub-lineages with more enhanced immuno-evasive properties emerging over time. Evaluating vaccine effectiveness (VE) against Omicron sub-lineages has become challenging against a complex background of varying vaccine coverage, vaccine platforms, prior infection rates, and hybrid immunity. Original messenger RNA vaccine booster doses substantially improved VE against BA.1 or BA.2 symptomatic disease. However, protection against symptomatic disease waned, with reductions detected from 2 months after booster administration. While original vaccine-elicited CD8+ and CD4+ T-cell responses cross-recognize Omicron sub-lineages, thereby retaining protection against severe outcomes, variant-adapted vaccines are required to expand the breadth of B-cell responses and improve durability of protection. Variant-adapted vaccines were rolled out in late 2022 to increase overall protection against symptomatic and severe infections caused by Omicron sub-lineages and antigenically aligned variants with enhanced immune escape mechanisms.

Analysis of All-Cause Hospitalization and Death Among Nonhospitalized Patients With Type 2 Diabetes and SARS-CoV-2 Infection Treated With Molnupiravir or Nirmatrelvir-Ritonavir During the Omicron Wave in Hong Kong.

Importance: Diabetes and COVID-19 are both global pandemics, and type 2 diabetes is a common comorbidity in patients with acute COVID-19 and is proven to be a key determinant of COVID-19 prognosis. Molnupiravir and nirmatrelvir-ritonavir are oral antiviral medications recently approved for nonhospitalized patients with mild to moderate COVID-19, following demonstration of their efficacies in reducing adverse outcomes of the disease; it is crucial to clarify whether both oral antiviral medications are efficacious in a population consisting exclusively of patients with type 2 diabetes. Objective: To evaluate the effectiveness of molnupiravir and nirmatrelvir-ritonavir in a contemporary population-based cohort comprising exclusively nonhospitalized patients with type 2 diabetes and SARS-CoV-2 infection. Design, Setting, and Participants: This retrospective cohort study was performed using population-based electronic medical record data for patients in Hong Kong with type 2 diabetes and confirmed SARS-CoV-2 infection between February 26 and October 23, 2022. Each patient was followed up until death, outcome event, crossover of oral antiviral treatment, or end of the observational period (October 30, 2022), whichever came first. Outpatient oral antiviral users were divided into molnupiravir and nirmatrelvir-ritonavir treatment groups, respectively, and nontreated control participants were matched through 1:1 propensity score matching. Data analysis was performed on March 22, 2023. Exposures: Molnupiravir (800 mg twice daily for 5 days) or nirmatrelvir-ritonavir (300 mg nirmatrelvir and 100 mg ritonavir twice daily for 5 days, or 150 mg nirmatrelvir and 100 mg ritonavir for patients with an estimated glomerular filtration rate of 30-59 mL/min per 1.73 m2). Main Outcomes and Measures: The primary outcome was a composite of all-cause mortality and/or hospitalization. The secondary outcome was in-hospital disease progression. Hazard ratios (HRs) were estimated with Cox regression. Results: This study identified 22 098 patients with type 2 diabetes and COVID-19. A total of 3390 patients received molnupiravir and 2877 received nirmatrelvir-ritonavir in the community setting. After application of exclusion criteria followed by 1:1 propensity score matching, this study comprised 2 groups. One group included 921 molnupiravir users (487 men [52.9%]), with a mean (SD) age of 76.7 (10.8) years, and 921 control participants (482 men [52.3%]), with a mean (SD) age of 76.6 (11.7) years. The other group included 793 nirmatrelvir-ritonavir users (401 men [50.6%]), with a mean (SD) age of 71.7 (11.5) years, and 793 control participants (395 men [49.8%]), with a mean (SD) age of 71.9 (11.6) years. At a median follow-up of 102 days (IQR, 56-225 days), molnupiravir use was associated with a lower risk of all-cause mortality and/or hospitalization (HR, 0.71 [95% CI, 0.64-0.79]; P < .001) and in-hospital disease progression (HR, 0.49 [95% CI, 0.35-0.69]; P < .001) compared with nonuse. At a median follow-up of 85 days (IQR, 56-216 days), nirmatrelvir-ritonavir use was associated with a lower risk of all-cause mortality and/or hospitalization (HR, 0.71 [95% CI, 0.63-0.80]; P < .001) and a nonsignificantly lower risk of in-hospital disease progression (HR, 0.92 [95% CI, 0.59-1.44]; P = .73) compared with nonuse. Conclusions and Relevance: These findings suggest that both molnupiravir and nirmatrelvir-ritonavir oral antiviral medications were associated with a lower risk of all-cause mortality and hospitalization among patients with COVID-19 and type 2 diabetes. Further studies in specific populations, such as individuals in residential care homes and individuals with chronic kidney disease, are suggested.

Vaccine effectiveness of BNT162b2 and CoronaVac against SARS-CoV-2 omicron infection and related hospital admission among people with substance use disorder in Hong Kong: a matched case-control study.

BACKGROUND: People with substance use disorder have a high risk of SARS-CoV-2 infection and subsequent poor outcomes. Few studies have evaluated COVID-19 vaccine effectiveness among people with substance use disorder. We aimed to estimate the vaccine effectiveness of BNT162b2 (Fosun-BioNTech) and CoronaVac (Sinovac) against SARS-CoV-2 omicron (B.1.1.529) infection and related hospital admission in this population. METHODS: We did a matched case-control study using electronic health databases in Hong Kong. Individuals diagnosed with substance use disorder between Jan 1, 2016, and Jan 1, 2022, were identified. People aged 18 years and older with SARS-CoV-2 infection from Jan 1 to May 31, 2022, and people with COVID-19-related hospital admission from Feb 16 to May 31, 2022, were included as cases and were matched by age, sex, and previous clinical history with controls from all individuals diagnosed with substance use disorder who attended the Hospital Authority health services: up to three controls for SARS-CoV-2 infection and up to ten controls for hospital admission. Conditional logistical regression was used to evaluate the association between vaccination status (ie, one, two, or three doses of BNT162b2 or CoronaVac) and the risk of SARS-CoV-2 infection and COVID-19-related hospital admission, adjusted for baseline comorbidities and medication use. FINDINGS: Among 57 674 individuals with substance use disorder, 9523 people with SARS-CoV-2 infections (mean age 61·00 years, SD 14·90; 8075 [84·8%] males and 1448 [15·2%] females) were identified and matched to 28 217 controls (mean age 60·99 years, 14·67; 24 006 [85·1%] males and 4211 [14·9%] females), and 843 people with COVID-19-related hospital admissions (mean age 70·48 years, SD 14·68; 754 [89·4%] males and 89 [10·6%] females) were identified and matched to 7459 controls (mean age 70·24 years, 13·87; 6837 [91·7%] males and 622 [8·3%] females). Data on ethnicity were not available. We observed significant vaccine effectiveness against SARS-CoV-2 infection for two-dose BNT162b2 vaccination (20·7%, 95% CI 14·0-27·0, p<0·0001) and three-dose vaccination (all BNT162b2 41·5%, 34·4-47·8, p<0·0001; all CoronaVac 13·6%, 5·4-21·0, p=0·0015; BNT162b2 booster after two-dose CoronaVac 31·3%, 19·8-41·1, p<0·0001), but not for one dose of either vaccine or two doses of CoronaVac. Significant vaccine effectiveness against COVID-19-related hospital admission was detected after one dose of BNT162b2 vaccination (35·7%, 3·8-57·1, p=0·032), two-dose vaccination (both BNT162b2 73·3%, 64·3 to 80·0, p<0·0001; both CoronaVac 59·9%, 50·2-67·7, p<0·0001), and three-dose vaccination (all BNT162b2 86·3%, 75·6-92·3, p<0·0001; all CoronaVac 73·5% 61·0-81·9, p<0·0001; BNT162b2 booster after two-dose CoronaVac 83·7%, 64·6-92·5, p<0·0001), but not after one dose of CoronaVac. INTERPRETATION: For both BNT162b2 and CoronaVac, two-dose or three-dose vaccination was protective against COVID-19-related hospital admission and the booster dose provided protection against SARS-CoV-2 infection among people with substance use disorder. Our findings confirm the importance of booster doses in this population during the period dominated by the omicron variant. FUNDING: Health Bureau, the Government of the Hong Kong Special Administrative Region.

Treatment of COVID-19 symptoms with over the counter (OTC) medicines used for treatment of common cold and flu.

Persons suffering from acute upper respiratory tract viral infections (URTI) commonly use over the counter (OTC) medicines to relieve symptoms such as fever, muscle aches, cough, runny nose, sore throat and nasal congestion. At present OTC medicines are only licensed for treatment of common cold and flu symptoms and not for treatment of the same symptoms associated with COVID-19. The innate immune response responsible for the mechanisms of the symptoms of URTI is the same for all respiratory viruses including SARS-CoV-2 and these symptoms can be relieved by treatment with the same OTC medicines as available for treatment of colds and flu. This review provides scientific information that OTC treatments for common cold and flu-like illness caused by respiratory viruses are safe and effective treatments for the same symptoms associated with COVID-19.

Managing sources of error during pandemics.

The COVID-19 pandemic has highlighted important considerations for modeling future pandemics.

Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong.

Hong Kong experienced a surge of Omicron BA.2 infections in early 2022, resulting in one of the highest per-capita death rates of COVID-19. The outbreak occurred in a dense population with low immunity towards natural SARS-CoV-2 infection, high vaccine hesitancy in vulnerable populations, comprehensive disease surveillance and the capacity for stringent public health and social measures (PHSMs). By analyzing genome sequences and epidemiological data, we reconstructed the epidemic trajectory of BA.2 wave and found that the initial BA.2 community transmission emerged from cross-infection within hotel quarantine. The rapid implementation of PHSMs suppressed early epidemic growth but the effective reproduction number (Re) increased again during the Spring festival in early February and remained around 1 until early April. Independent estimates of point prevalence and incidence using phylodynamics also showed extensive superspreading at this time, which likely contributed to the rapid expansion of the epidemic. Discordant inferences based on genomic and epidemiological data underscore the need for research to improve near real-time epidemic growth estimates by combining multiple disparate data sources to better inform outbreak response policy.

Residential clustering of COVID-19 cases and efficiency of building-wide compulsory testing notices as a transmission control measure in Hong Kong.

We described the frequency of residential case clusters and the efficiency of compulsory testing in identifying cases using buildings targeted in compulsory testing and locally infected COVID-19 cases matched by residence in Hong Kong. Most of the buildings (4246/7688, 55.2%) with COVID-19 cases identified had only one reported case and 13% of the daily reported cases were detected through compulsory testing. Compulsory testing notices could be essential in attempting to eliminate infections ('zero covid') and impactful early in an epidemic but appears to be relatively inefficient in response to sustained community transmission.

Optimizing COVID-19 surveillance using historical electronic health records of influenza infections.

Targeting surveillance resources toward individuals at high risk of early infection can accelerate the detection of emerging outbreaks. However, it is unclear which individuals are at high risk without detailed data on interpersonal and physical contacts. We propose a data-driven COVID-19 surveillance strategy using Electronic Health Record (EHR) data that identifies the most vulnerable individuals who acquired the earliest infections during historical influenza seasons. Our simulations for all three networks demonstrate that the EHR-based strategy performs as well as the most-connected strategy. Compared to the random acquaintance surveillance, our EHR-based strategy detects the early warning signal and peak timing much earlier. On average, the EHR-based strategy has 9.8 days of early warning and 13.5 days of peak timings, respectively, before the whole population. For the urban network, the expected values of our method are better than the random acquaintance strategy (24% for early warning and 14% in-advance for peak time). For a scale-free network, the average performance of the EHR-based method is 75% of the early warning and 109% in-advance when compared with the random acquaintance strategy. If the contact structure is persistent enough, it will be reflected by their history of infection. Our proposed approach suggests that seasonal influenza infection records could be used to monitor new outbreaks of emerging epidemics, including COVID-19. This is a method that exploits the effect of contact structure without considering it explicitly.

Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach.

Identifying effective drug treatments for COVID-19 is essential to reduce morbidity and mortality. Although a number of existing drugs have been proposed as potential COVID-19 treatments, effective data platforms and algorithms to prioritize drug candidates for evaluation and application of knowledge graph for drug repurposing have not been adequately explored. A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments for COVID-19 by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported. The proposed drug candidates serve to generate hypotheses for future evaluation in clinical trials and observational studies.

Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities.

The two nearby Amazonian cities of Iquitos and Manaus endured explosive COVID-19 epidemics and may well have suffered the world's highest infection and death rates over 2020, the first year of the pandemic. State-of-the-art epidemiological and modeling studies estimated that the populations of both cities came close to attaining herd immunity (>70% infected) at the termination of the first wave and were thus protected. This makes it difficult to explain the more deadly second wave of COVID-19 that struck again in Manaus just months later, simultaneous with the appearance of a new P.1 variant of concern, creating a catastrophe for the unprepared population. It was suggested that the second wave was driven by reinfections, but the episode has become controversial and an enigma in the history of the pandemic. We present a data-driven model of epidemic dynamics in Iquitos, which we also use to explain and model events in Manaus. By reverse engineering the multiple epidemic waves over 2 y in these two cities, the partially observed Markov process model inferred that the first wave left Manaus with a highly susceptible and vulnerable population (≈40% infected) open to invasion by P.1, in contrast to Iquitos (≈72% infected). The model reconstructed the full epidemic outbreak dynamics from mortality data by fitting a flexible time-varying reproductive number [Formula: see text] while estimating reinfection and impulsive immune evasion. The approach is currently highly relevant given the lack of tools available to assess these factors as new SARS-CoV-2 virus variants appear with different degrees of immune evasion.

Rapid global spread of variants of concern of SARS-CoV-2.

Objectives: Variants of concern (VOCs) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), such as the Delta variant and the Omicron variant, have reached all countries/regions of the world and have had a tremendous impact. This study analyses the global spread of VOCs of SARS-CoV-2. Methods: Biweekly aggregated numbers of several VOCs were retrieved for 58 locations. The time interval for the proportion of VOC samples to exceed 60% (indicating dominance) among all samples sequenced in each location was calculated. The times taken for a VOC to become dominant in 12 (or 36) locations was defined in order to quantify the speed of spread. Results: It took 63, 56 and 28 days for the Alpha, Delta and Omicron variants to become dominant in 12 locations, respectively, and 133, 70 and 28 days for the Alpha, Delta and Omicron variants to become dominant in 36 locations. Conclusions: The Omicron variant has much higher transmission potential compared with the Delta variant, and the Delta variant has higher transmission potential compared with the pre-Delta VOCs.

Effectiveness of BNT162b2 and CoronaVac COVID-19 vaccination against asymptomatic and symptomatic infection of SARS-CoV-2 omicron BA.2 in Hong Kong: a prospective cohort study.

BACKGROUND: COVID-19 vaccines provide protection against symptomatic infection that might require medical attention and against severe outcomes; however, there is a paucity of evidence regarding the effectiveness of the BNT162b2 and CoronaVac vaccines and their booster regimens against asymptomatic or mild omicron infections in the community. We aimed to measure the effectiveness of BNT162b2 and CoronaVac vaccines against asymptomatic and symptomatic SARS-CoV-2 omicron infections, during a period of omicron BA.2 predominance in Hong Kong. METHODS: In this prospective cohort study in a population that was generally infection-naive before the large omicron BA.2 wave between January and late May, 2022, we established a public health surveillance platform to monitor the evolving activity of SARS-CoV-2 infections in the community. We recruited a cohort of individuals aged 5 years and older between March 1 and March 7, 2022, from the general population. Individuals were enrolled from all 18 districts of Hong Kong, according to a predefined age-stratified quota, primarily by random digit dialing (generating suitable eight-digit local telephone numbers by randomly picking sets of the first four digits from a sampling frame, and randomly generating the last four digits), and supplemented by our existing cohorts (which included cohorts for studying influenza vaccination from school-based vaccination programmes and cohorts for SARS-CoV-2 seroprevalence from the community), to ensure representativeness of the population in Hong Kong. Participants did weekly rapid antigen testing with a self-collected pooled nasal and throat swab, regardless of symptom and exposure status, from March 1 to April 15, 2022. Individuals reporting a history of SARS-CoV-2 infection confirmed by laboratory PCR testing before enrolment were excluded from the vaccine effectiveness analysis to avoid potential bias due to infection-induced immunity. The primary outcomes of the study were the incidence of SARS-CoV-2 infection, including asymptomatic and symptomatic infections, and the vaccine effectiveness of BNT162b2 and CoronaVac vaccines. The effectiveness of one, two, and three doses of vaccination was estimated with a Cox proportional hazards regression model with time-dependent covariates, allowing for changes in vaccination status over time, after adjustment for demographic factors and pre-existing medical conditions. FINDINGS: Of the 8636 individuals included in the analysis, 7233 (84%) received at least two doses of vaccine, 3993 (46%) received booster doses, and 903 (10%) reported SARS-CoV-2 infection. Among these infections 589 (65·2%) were symptomatic and 314 (34·8%) were asymptomatic at the time of testing. Statistically significant protection against asymptomatic and symptomatic SARS-CoV-2 omicron infection was found only for those who received a BNT162b2 or CoronaVac booster dose, with a vaccine effectiveness of 41·4% (23·2 to 55·2; p=0·0001) and 32·4% (9·0 to 49·8; p=0·0098), respectively. The vaccine effectiveness of BNT162b2 and CoronaVac boosters was further increased to 50·9% (95% CI 31·0-65·0; p<0·0001) and 41·6% (15·0-59·8; p=0·0049), respectively, for symptomatic omicron infections. A similar pattern of vaccine effectiveness (55·8%, 22·9-74·6; p=0·0040) was also conferred after receipt of a BNT162b2 booster by individuals who received a CoronaVac primary vaccination series. INTERPRETATION: Two doses of either vaccine did not provide significant protection against COVID-19 infection. However, receipt of a BNT162b2 booster or CoronaVac booster was associated with a significantly lower risk of omicron BA.2 infection and symptomatic infection. Our findings confirm the effectiveness of booster doses to protect against mild and asymptomatic infection. FUNDING: Henry Fok Foundation and Hong Kong Health Bureau.

Nonpharmaceutical interventions for managing SARS-CoV-2.

PURPOSE OF REVIEW: Initial response strategies to the COVID-19 pandemic were heavily reliant on nonpharmaceutical interventions (NPIs), a set of measures implemented to slow or even stop the spread of infection. Here, we reviewed key measures used during the COVID-19 pandemic. RECENT FINDINGS: Some NPIs were successful in reducing the transmission of SARS-CoV-2. Personal protective measures such as face masks were widely used, and likely had some effect on transmission. The development and production of rapid antigen tests allowed self-diagnosis in the community, informing isolation and quarantine measures. Community-wide measures such as school closures, workplace closures and complete stay-at-home orders were able to reduce contacts and prevent transmission. They were widely used in the pandemic and contributed to reduce transmission in the community; however, there were also negative unintended consequences in the society and economy. SUMMARY: NPIs slowed the spread of SARS-CoV-2 and are essential for pandemic preparedness and response. Understanding which measures are more effective at reducing transmission with lower costs is imperative.

Within-host dynamics of SARS-CoV-2 infection: A systematic review and meta-analysis.

Within-host model specified by viral dynamic parameters is a mainstream tool to understand SARS-CoV-2 replication cycle in infected patients. The parameter uncertainty further affects the output of the model, such as the efficacy of potential antiviral drugs. However, gathering empirical data on these parameters is challenging. Here, we aim to conduct a systematic review of viral dynamic parameters used in within-host models by calibrating the model to the viral load data measured from upper respiratory specimens. We searched the PubMed, Embase and Web of Science databases (between 1 December 2019 and 10 February 2022) for within-host modelling studies. We identified seven independent within-host models from the above nine studies, including Type I interferon, innate response, humoral immune response or cell-mediated immune response. From these models, we extracted and analyse seven widely used viral dynamic parameters including the viral load at the point of infection or symptom onset, the rate of viral particles infecting susceptible cells, the rate of infected cells releasing virus, the rate of virus particles cleared, the rate of infected cells cleared and the rate of cells in the eclipse phase can become productively infected. We identified seven independent within-host models from nine eligible studies. The viral load at symptom onset is 4.78 (95% CI:2.93, 6.62) log(copies/ml), and the viral load at the point of infection is -1.00 (95% CI:-1.94, -0.05) log(copies/ml). The rate of viral particles infecting susceptible cells and the rate of infected cells cleared have the pooled estimates as -6.96 (95% CI:-7.66, -6.25) log([copies/ml]-1 day-1 ) and 0.92 (95% CI:-0.09, 1.93) day-1 , respectively. We found that the rate of infected cells cleared was associated with the reported model in the meta-analysis by including the model type as a categorical variable (p < .01). Joint viral dynamic parameters estimates when parameterizing within-host models have been published for SARS-CoV-2. The reviewed viral dynamic parameters can be used in the same within-host model to understand SARS-CoV-2 replication cycle in infected patients and assess the impact of pharmaceutical interventions.

Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong.

Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines and mobile telephones from May 2020 to February 2021. We analyze the epidemiological impact of pandemic fatigue by using the large and detailed cross-sectional telephone surveys to quantify risk perception and self-reported protective behaviors and mathematical models to incorporate population protective behaviors. Our retrospective prediction suggests that an increase of 100 daily new reported cases would lead to 6.60% (95% CI: 4.03, 9.17) more people worrying about being infected, increase 3.77% (95% CI: 2.46, 5.09) more people to avoid social gatherings, and reduce the weekly mean reproduction number by 0.32 (95% CI: 0.20, 0.44). Accordingly, the fourth wave would have been 14% (95% CI%: -53%, 81%) smaller if not for pandemic fatigue. This indicates the important role of mitigating pandemic fatigue in maintaining population protective behaviors for controlling COVID-19.

Cost-effectiveness of fractional doses of COVID-19 vaccine boosters in India

Background Coronavirus disease 2019 (COVID-19) continues to be a major global public health crisis in 2022 that exacts significant human and economic costs. Booster vaccination of individuals can improve waning immunity and reduce the impact of community epidemics. Methods Using an epidemiological model that incorporates population-level SARS-CoV-2 transmission and waning of vaccine-derived immunity, we identify the hypothetical potential of mass vaccination with fractionated vaccine doses specific to ChAdOx1 nCoV-19 (AZD1222 [Covishield];AstraZeneca) as an optimal and cost-effective strategy in India's Omicron outbreak. Findings We find that the optimal strategy is 1/8 fractional dosing under mild (Re ∼ 1.2) and rapid (Re ∼ 5) transmission scenarios, leading to an estimated $6 (95% CI: -13, 26) billion and $2 (95% CI:-26, 30) billion in health-related net monetary benefit over 200 days, respectively. Rapid and broad use of fractional dosing for boosters, together with delivery costs divided by fractionation, could substantially gain more net monetary benefit by $11 (95% CI: -10, 33) and $2 (95% CI: -23, 28) billion, respectively, under the mild and rapid transmission scenarios. Conclusions Mass vaccination with fractional doses of COVID-19 vaccines to boost immunity in a vaccinated population could be a cost effective strategy for mitigating the public health costs of resurgences caused by vaccine-evasive variants and fractional dosing deserves further clinical and regulatory evaluation. Funding Financial support was provided by the AIR@InnoHK Programme from Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region. Graphical This analysis demonstrated that the use of fractional dose could offer greater net monetary benefit in both moderate and rapid transmission scenarios given the epidemiological and socioeconomic conditions in India in 2022. In the face of a vaccine shortage, fractional dosage of vaccinations would have additional beneficial public health benefits.

Viral burden rebound in hospitalised patients with COVID-19 receiving oral antivirals in Hong Kong: a population-wide retrospective cohort study.

BACKGROUND: Viral rebound after nirmatrelvir-ritonavir treatment has implications for the clinical management and isolation of patients with COVID-19. We evaluated an unselected, population-wide cohort to identify the incidence of viral burden rebound and associated risk factors and clinical outcomes. METHODS: We did a retrospective cohort study of hospitalised patients with a confirmed diagnosis of COVID-19 in Hong Kong, China, for an observation period from Feb 26 to July 3, 2022 (during the omicron BA.2.2 variant wave). Adult patients (age ≥18 years) admitted 3 days before or after a positive COVID-19 test were selected from medical records held by the Hospital Authority of Hong Kong. We included patients with non-oxygen-dependent COVID-19 at baseline receiving either molnupiravir (800 mg twice a day for 5 days), nirmatrelvir-ritonavir (nirmatrelvir 300 mg with ritonavir 100 mg twice a day for 5 days), or no oral antiviral treatment (control group). Viral burden rebound was defined as a reduction in cycle threshold (Ct) value (≥3) on quantitative RT-PCR test between two consecutive measurements, with such decrease sustained in an immediately subsequent Ct measurement (for those patients with ≥3 Ct measurements). Logistic regression models were used to identify prognostic factors for viral burden rebound, and to assess associations between viral burden rebound and a composite clinical outcome of mortality, intensive care unit admission, and invasive mechanical ventilation initiation, stratified by treatment group. FINDINGS: We included 4592 hospitalised patients with non-oxygen-dependent COVID-19 (1998 [43·5%] women and 2594 [56·5%] men). During the omicron BA.2.2 wave, viral burden rebound occurred in 16 of 242 patients (6·6% [95% CI 4·1-10·5]) receiving nirmatrelvir-ritonavir, 27 of 563 (4·8% [3·3-6·9]) receiving molnupiravir, and 170 of 3787 (4·5% [3·9-5·2]) in the control group. The incidence of viral burden rebound did not differ significantly across the three groups. Immunocompromised status was associated with increased odds of viral burden rebound, regardless of antiviral treatment (nirmatrelvir-ritonavir: odds ratio [OR] 7·37 [95% CI 2·56-21·26], p=0·0002; molnupiravir: 3·05 [1·28-7·25], p=0·012; control: 2·21 [1·50-3·27], p<0·0001). Among patients receiving nirmatrelvir-ritonavir, the odds of viral burden rebound were higher in those aged 18-65 years (vs >65 years; 3·09 [1·00-9·53], p=0·050), those with high comorbidity burden (score >6 on the Charlson Comorbidity Index; 6·02 [2·09-17·38], p=0·0009), and those concomitantly taking corticosteroids (7·51 [1·67-33·82], p=0·0086); whereas the odds were lower in those who were not fully vaccinated (0·16 [0·04-0·67], p=0·012). In patients receiving molnupiravir, those aged 18-65 years (2·68 [1·09-6·58], p=0·032) or on concomitant corticosteroids (3·11 [1·23-7·82], p=0·016) had increased odds of viral burden rebound. We found no association between viral burden rebound and occurrence of the composite clinical outcome from day 5 of follow-up (nirmatrelvir-ritonavir: adjusted OR 1·90 [0·48-7·59], p=0·36; molnupiravir: 1·05 [0·39-2·84], p=0·92; control: 1·27 [0·89-1·80], p=0·18). INTERPRETATION: Viral burden rebound rates are similar between patients with antiviral treatment and those without. Importantly, viral burden rebound was not associated with adverse clinical outcomes. FUNDING: Health and Medical Research Fund, Health Bureau, The Government of the Hong Kong Special Administrative Region, China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Characterizing Human Collective Behaviors During COVID-19 - Hong Kong SAR, China, 2020.

What is already known about this topic?: People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. What is added by this report?: This study offers a framework for evaluating interactions among individuals' emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model's output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. What are the implications for public health practice?: Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people's risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives.