Global Seasonal Activities of Respiratory Syncytial Virus Before the Coronavirus Disease 2019 Pandemic: A Systematic Review

Varied seasonal patterns of respiratory syncytial virus (RSV) have been reported worldwide. We conducted a systematic review on articles identified in PubMed reporting RSV seasonality based on data collected before 1 January 2020. RSV seasonal patterns were examined by geographic location, calendar month, analytic method, and meteorological factors including temperature and absolute humidity. Correlation and regression analyses were conducted to explore the relationship between RSV seasonality and study methods and characteristics of study locations. RSV seasons were reported in 209 articles published in 1973-2023 for 317 locations in 77 countries. Regular RSV seasons were similarly reported in countries in temperate regions, with highly variable seasons identified in subtropical and tropical countries. Longer durations of RSV seasons were associated with a higher daily average mean temperature and daily average mean absolute humidity. The global seasonal patterns of RSV provided important information for optimizing interventions against RSV infection.

A retrospective cohort study of Paxlovid efficacy depending on treatment time in hospitalized COVID-19 patients

Paxlovid, a SARS-CoV-2 antiviral, not only prevents severe illness but also curtails viral shedding, lowering transmission risks from treated patients. By fitting a mathematical model of within-host Omicron viral dynamics to electronic health records data from 208 hospitalized patients in Hong Kong, we estimate that Paxlovid can inhibit over 90% of viral replication. However, its effectiveness critically depends on the timing of treatment. If treatment is initiated three days after symptoms first appear, we estimate a 17% chance of a post-treatment viral rebound and a 12% (95% CI: 0-16%) reduction in overall infectiousness for non-rebound cases. Earlier treatment significantly elevates the risk of rebound without further reducing infectiousness, whereas starting beyond five days reduces its efficacy in curbing peak viral shedding. Among the 104 patients who received Paxlovid, 62% began treatment within an optimal three-to-five-day day window after symptoms appeared. Our findings indicate that broader global access to Paxlovid, coupled with appropriately timed treatment, can mitigate the severity and transmission of SARS-Cov-2.

Clinical, imaging, and pathological characteristics of congenital infiltrating lipomatosis of the face

Congenital infiltrating lipomatosis of the face (CILF) is a rare congenital disease of the head and neck region. In this study, the cases of 20 patients diagnosed with CILF were reviewed retrospectively to analyse the characteristics of the disease. The symptoms, signs, and clinical progression were investigated. Radiological changes were analysed according to the distribution of the trigeminal nerve. The pathological features of the fatty facial lesions, jaw hyperplasia, and lingual lesions were further identified. All 20 patients demonstrated hemifacial hypertrophy at birth. None had a family history of the disease. Significant radiological features of CILF (prevalence ≥90%) included thickened buccal subcutaneous fat, palatal submucosal fat, and temporal subcutaneous fat, maxillary tuberosity heteroplasia, and fatty infiltration of the masseteric intermuscular space. With regard to the trigeminal nerve, the frontal branch region (CNV1) was rarely affected, while the maxillary (CNV2) and mandibular (CNV3) branch regions showed considerable changes. Pathologically, CILF was observed to be characterized by the infiltration of mature adipose tissue into the adjacent buccal soft tissue, osteal remodelling surrounded by sheets of mature lipocytes and supporting fibrovascular stroma, and lingual hamartoma. In summary, CILF exhibits distinct characteristics that are related to the regions controlled by the maxillary and mandibular branches of the trigeminal nerve, suggesting that CILF may be associated with early neural development.

Public Health Impact of Paxlovid as Treatment for COVID-19, United States

We evaluated the population-level benefits of expanding treatment with the antiviral drug Paxlovid (nirmatrelvir/ritonavir) in the United States for SARS-CoV-2 Omicron variant infections. Using a multiscale mathematical model, we found that treating 20% of symptomatic case-patients with Paxlovid over a period of 300 days beginning in January 2022 resulted in life and cost savings. In a low-transmission scenario (effective reproduction number of 1.2), this approach could avert 0.28 million (95% CI 0.03-0.59 million) hospitalizations and save US $56.95 billion (95% CI US $2.62-$122.63 billion). In a higher transmission scenario (effective reproduction number of 3), the benefits increase, potentially preventing 0.85 million (95% CI 0.36-1.38 million) hospitalizations and saving US $170.17 billion (95% CI US $60.49-$286.14 billion). Our findings suggest that timely and widespread use of Paxlovid could be an effective and economical approach to mitigate the effects of COVID-19.

Nowcasting and Forecasting Seasonal Influenza Epidemics - China, 2022-2023

Background

Seasonal influenza resurged in China in February 2023, causing a large number of hospitalizations. While influenza epidemics occurred across China during the coronavirus disease 2019 (COVID-19) pandemic, the relaxation of COVID-19 containment measures in December 2022 may have contributed to the spread of acute respiratory infections in winter 2022/2023.

Methods

Using a mathematical model incorporating influenza activity as measured by influenza-like illness (ILI) data for northern and southern regions of China, we reconstructed the seasonal influenza incidence from October 2015 to September 2019 before the COVID-19 pandemic. Using this trained model, we predicted influenza activities in northern and southern China from March to September 2023.

Results

We estimated the effective reproduction number R e as 1.08 [95% confidence interval ( CI): 0.51, 1.65] in northern China and 1.10 (95% CI: 0.55, 1.67) in southern China at the start of the 2022-2023 influenza season. We estimated the infection attack rate of this influenza wave as 18.51% (95% CI: 0.00%, 37.78%) in northern China and 28.30% (95% CI: 14.77%, 41.82%) in southern China.

Conclusions

The 2023 spring wave of seasonal influenza in China spread until July 2023 and infected a substantial number of people.

Mitigation of respiratory syncytial virus epidemics by RSVpreF vaccines after the COVID-19 pandemic in the UK: a modelling study

BACKGROUND

The RSVpreF vaccines have breakthrough progress. The respiratory syncytial virus (RSV) vaccine for older adults from GlaxoSmithKline was the first RSV vaccine approved by the US Food and Drug Administration (FDA) in early May 2023, followed by the subsequent FDA approval of Pfizer's RSV vaccines for older adults and pregnant women. We aimed to estimate the public health impact of the potential population-level administrations of the RSVpreF vaccine in the UK.

METHODS

In this modelling study, we used national census and contact survey data to construct an individual-based mathematical model, with interpersonal connections characterising household structure, social settings, and age-specific contact patterns. We considered both within-host viral-load dynamics and between-host RSV transmission. We modelled the coverages of RSV vaccines for older people (age ≥60 years) and pregnant women, using influenza vaccination data from the 2018-19 season. We explored a range of possible transmissibility and estimated the health burden averted by RSVpreF vaccine over a 300-day period as compared with the control scenario without vaccines.

FINDINGS

In a low-transmission scenario (Re=1·2), RSVpreF would avert a total population of 2·35 (95% credible interval [CrI] 1·24-3·77) million infections, 12.80 (95% CrI 8·60-17·06) thousand hospital admissions, and 0·93 (95% CrI 0·69-1·25) thousand deaths, with 1·82 (1·41-2·33) million infections, 12·44 (8·50-16·38) thousand hospital admissions, and 0·93 (0·67-1·23) thousand deaths averted for people aged 60 years and older. In a high-transmission scenario (Re=2·0), RSVpreF would avert 2·01 (1·37-2·68) million infections, 14·67 (10·05-18·33) thousand hospital admissions, and 1·12 (0·80-1·35) thousand deaths. The majority averted would still be among older adults.

INTERPRETATION

Our mathematical models will help improve the vaccine schedules of RSVpreF. Future work will address several limitations when data become available, including the incorporation of population immunity, potential vaccine hesitancy, and other factors affecting vaccine uptake and effectiveness.

FUNDING

Government of the Hong Kong Special Administrative Region, the European Research Council, and Ministry of Science and Technology of the People's Republic of China.

Identifying Phage Sequences From Metagenomic Data Using Deep Neural Network With Word Embedding and Attention Mechanism

Phages are the functional viruses that infect bacteria and they play important roles in microbial communities and ecosystems. Phage research has attracted great attention due to the wide applications of phage therapy in treating bacterial infection in recent years. Metagenomics sequencing technique can sequence microbial communities directly from an environmental sample. Identifying phage sequences from metagenomic data is a vital step in the downstream of phage analysis. However, the existing methods for phage identification suffer from some limitations in the utilization of the phage feature for prediction, and therefore their prediction performance still need to be improved further. In this article, we propose a novel deep neural network (called MetaPhaPred) for identifying phages from metagenomic data. In MetaPhaPred, we first use a word embedding technique to encode the metagenomic sequences into word vectors, extracting the latent feature vectors of DNA words. Then, we design a deep neural network with a convolutional neural network (CNN) to capture the feature maps in sequences, and with a bi-directional long short-term memory network (Bi-LSTM) to capture the long-term dependencies between features from both forward and backward directions. The feature map consists of a set of feature patterns, each of which is the weighted feature extracted by a convolution filter with convolution kernels in the CNN slide along the input feature vectors. Next, an attention mechanism is used to enhance contributions of important features. Experimental results on both simulated and real metagenomic data with different lengths demonstrate the superiority of the proposed MetaPhaPred over the state-of-the-art methods in identifying phage sequences.

Estimate of COVID-19 Deaths, China, December 2022-February 2023

China announced a slight easing of its zero-COVID rules on November 11, 2022, and then a major relaxation on December 7, 2022. We estimate that the ensuing wave of SARS-CoV-2 infections caused 1.41 million deaths in China during December 2022-February 2023, substantially higher than that reported through official channels.

Protocol for the automatic extraction of epidemiological information via a pre-trained language model

The lack of systems to automatically extract epidemiological fields from open-access COVID-19 cases restricts the timeliness of formulating prevention measures. Here we present a protocol for using CCIE, a COVID-19 Cases Information Extraction system based on the pre-trained language model.1 We describe steps for preparing supervised training data and executing python scripts for named entity recognition and text category classification. We then detail the use of machine evaluation and manual validation to illustrate the effectiveness of CCIE. For complete details on the use and execution of this protocol, please refer to Wang et al.2.

The public health impact of Paxlovid COVID-19 treatment in the United States

The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario R e ∼ 1.2 treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% CrI: 1.69, 71.15) thousand deaths averted, and US$52.16 (95% CrI: 2.62, 122.63) billion reduction in health- and treatment-related costs. Rapid and broad use of the antiviral Paxlovid could substantially reduce COVID-19 morbidity and mortality, while averting socioeconomic hardship.

Real-world effectiveness of monkeypox vaccines: a systematic review

A systematic review was conducted to investigate and understand the real-world effectiveness of smallpox vaccines against mpox during 2022 outbreaks. The effectiveness of MVA-BN was estimated to be 87% [95% confidence interval (CI): 84–90%] for one-dose and 89% (95% CI: 78–100%) for two-dose vaccination. The next-generation vaccines are recommended for future preparedness.

Reproduction number of SARS-CoV-2 Omicron variants, China, December 2022-January 2023

China adjusted the zero-COVID strategy in late 2022, triggering an unprecedented Omicron wave. We estimated the time-varying reproduction numbers of 32 provincial-level administrative divisions from December 2022 to January 2023. We found that the pooled estimate of initial reproduction numbers is 4.74 (95% confidence interval: 4.41, 5.07).

Genomic features of recombinant CHO clones arising from transposon-based and randomized integration

The use of transposase in cell line development (CLD) programs has experienced increased popularity over the past decade. However, few studies have described the mechanism of action and the genomic and phenotypic characteristics of clones derived from transposase. Additionally, how these traits impact long-term bioproduction is unknown. Here, we use chromosome painting, deep sequencing, and ddPCR to characterize the unique fingerprints associated with transposase-derived clones. Transposase reduces the cellular pool of transient vector as early as three days post transfection following transfection and expedites stable pool establishment by up to two weeks. Furthermore, recombinant DNA expression is significantly improved up to ∼3 fold along with a greater balance of antibody heavy and light chain transcripts, resulting in higher titers in transposase generated pools. Transposase derived pools contained an often innumerable number of integration sites, representing a vast increase in integration site diversity over randomly generated pools, which were bottlenecked at 1-3 integration sites per pool. These transposase mediated integrations typically occurred in clean singlets, free of genomic scars such as deletions, inversions, and other modifications associated with legacy transfection methods which exhibited higher copy numbers per integration site. Relative declines in gene expression occur with copy number increase in the randomly generated, but not the transposase derived clones. Furthermore, transposase-derived clones were more likely to exhibit enhanced a long term stability profile, including product quality attributes such as mannose-5. This improved stability may result from circumventing mechanisms associated with the silencing of tandem repeats. Thus, transposase-mediated approaches can provide multifaceted molecular and phenotypic advantages in cell line development when compared to legacy random-integration methods.

Multimodeling approach to evaluating the efficacy of layering pharmaceutical and nonpharmaceutical interventions for influenza pandemics

When an influenza pandemic emerges, temporary school closures and antiviral treatment may slow virus spread, reduce the overall disease burden, and provide time for vaccine development, distribution, and administration while keeping a larger portion of the general population infection free. The impact of such measures will depend on the transmissibility and severity of the virus and the timing and extent of their implementation. To provide robust assessments of layered pandemic intervention strategies, the Centers for Disease Control and Prevention (CDC) funded a network of academic groups to build a framework for the development and comparison of multiple pandemic influenza models. Research teams from Columbia University, Imperial College London/Princeton University, Northeastern University, the University of Texas at Austin/Yale University, and the University of Virginia independently modeled three prescribed sets of pandemic influenza scenarios developed collaboratively by the CDC and network members. Results provided by the groups were aggregated into a mean-based ensemble. The ensemble and most component models agreed on the ranking of the most and least effective intervention strategies by impact but not on the magnitude of those impacts. In the scenarios evaluated, vaccination alone, due to the time needed for development, approval, and deployment, would not be expected to substantially reduce the numbers of illnesses, hospitalizations, and deaths that would occur. Only strategies that included early implementation of school closure were found to substantially mitigate early spread and allow time for vaccines to be developed and administered, especially under a highly transmissible pandemic scenario.

Medical-Knowledge-Based Graph Neural Network for Medication Combination Prediction

Medication combination prediction (MCP) can provide assistance for experts in the more thorough comprehension of complex mechanisms behind health and disease. Many recent studies focus on the patient representation from the historical medical records, but neglect the value of the medical knowledge, such as the prior knowledge and the medication knowledge. This article develops a medical-knowledge-based graph neural network (MK-GNN) model which incorporates the representation of patients and the medical knowledge into the neural network. More specifically, the features of patients are extracted from their medical records in different feature subspaces. Then these features are concatenated to obtain the feature representation of patients. The prior knowledge, which is calculated according to the mapping relationship between medications and diagnoses, provides heuristic medication features according to the diagnosis results. Such medication features can help the MK-GNN model learn optimal parameters. Moreover, the medication relationship in prescriptions is formulated as a drug network to integrate the medication knowledge into medication representation vectors. The results reveal the superior performance of the MK-GNN model compared with the state-of-the-art baselines on different evaluation metrics. The case study manifests the application potential of the MK-GNN model.

Baicalin alleviates silica-induced lung inflammation and fibrosis by inhibiting TLR4/NF-?B pathway in rats

Silicosis is an occupational lung disease caused by inhaling silica dust. The disease is characterized by early lung inflammation and late irreversible pulmonary fibrosis. Here we report the effect of Baicalin, a main flavonoid compound from the roots of Chinese herbal medicine Huang Qin on silicosis in a rat model. Results showed Baicalin (50 or 100 mg/kg/day) can mitigate the silica-induced lung inflammation and reduce the harm of alveolar structure and the blue region of collagen fibers in rat lung at 28 days after administration. At the same time, Baicalin also diminished the level of interleukin-1beta (IL-1beta, interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha) and transforming growth factor-beta1 (TGF-beta1) in lung tissues. The protein expression of collagen I (Col-1), alpha-smooth muscle actin (alpha-SMA) and vimentin were down-regulated while E-cadherin (E-cad) was increased in Baicalin-treated rats. In addition, the Toll Like Receptor 4 (TLR4)/ nuclear factor kappaB (NF-kappaB) pathway was enabled at 28 days after silica infusion, and the treatment of Baicalin diminished the expression of TLR4 and NF-?B in the lungs of rat with silicosis. These results suggested that Baicalin inhibited the pulmonary inflammatory and fibrosis in a rat model of silicosis, which could be attributed to inhibition of the TLR4/NF-kappaB pathway.

Baicalin alleviates silica-induced lung inflammation and fibrosis by inhibiting TLR4/NF-?B pathway in rats

Silicosis is an occupational lung disease caused by inhaling silica dust. The disease is characterized by early lung inflammation and late irreversible pulmonary fibrosis. Here we report the effect of Baicalin, a main flavonoid compound from the roots of Chinese herbal medicine Huang Qin on silicosis in a rat model. Results showed Baicalin (50 or 100 mg/kg/day) can mitigate the silica-induced lung inflammation and reduce the harm of alveolar structure and the blue region of collagen fibers in rat lung at 28 days after administration. At the same time, Baicalin also diminished the level of interleukin-1beta (IL-1beta, interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha) and transforming growth factor-beta1 (TGF-beta1) in lung tissues. The protein expression of collagen I (Col-1), alpha-smooth muscle actin (alpha-SMA) and vimentin were down-regulated while E-cadherin (E-cad) was increased in Baicalin-treated rats. In addition, the Toll Like Receptor 4 (TLR4)/ nuclear factor kappaB (NF-kappaB) pathway was enabled at 28 days after silica infusion, and the treatment of Baicalin diminished the expression of TLR4 and NF-?B in the lungs of rat with silicosis. These results suggested that Baicalin inhibited the pulmonary inflammatory and fibrosis in a rat model of silicosis, which could be attributed to inhibition of the TLR4/NF-kappaB pathway.

Research on Ecological Land Expansion: A Case Study of Haixing County of China

As China’s natural resource governance has turned to high-quality management, establishing reasonable and ecological land-use patterns is an effective means of promoting natural resource utilization and improving the quality of the ecological environment. Therefore, this study used ecological land as the expansion source to construct an ecological land-use pattern with the minimum cumulative resistance model in Haixing County, China, based on regional food security, ecological security, and construction land expansion patterns. This work also involved designing ecological corridors, radiation channels, strategic nodes, and other ecological components. The results demonstrate that (1) the ecological land source is 7976.93 hm2, accounting for 9.19% of the total area. It is mainly distributed in the southeast of the county, mainly in the river system and woodland; (2) the food security situation of Haixing County can be divided into four zones, most of which are agricultural adjustment areas, indicating that the ecological security of cultivated land in this area needs to be improved; (3) the ecological security level of Haixing County is divided into four areas, and the ideal safety zone accounts for the smallest area, indicating that the regional ecological situation is very unstable; (4) construction land expansion zone is divided into four parts. A suitable construction zone occupies the largest area and is mainly distributed around the current construction land; (5) the expansion of the ecological land-use pattern of Haixing County includes four zones, 15 ecological corridors, 12 radiation channels, and 35 strategic nodes, which is conducive to optimal land allocation from an ecological security perspective. This paper puts forward some suggestions for ecological protection and intensive urban development.

The risk of SARS-CoV-2 Omicron variant emergence in low and middle-income countries (LMICs)

We estimated the probability of undetected emergence of the SARS-CoV-2 Omicron variant in 25 low and middle-income countries (LMICs) prior to December 5, 2021. In nine countries, the risk exceeds 50 %; in Turkey, Pakistan and the Philippines, it exceeds 99 %. Risks are generally lower in the Americas than Europe or Asia.

Impact of human mobility on COVID-19 transmission according to mobility distance, locations and demographic factors in the Greater Bay area of China：a population-based study

BACKGROUND

Mobility restriction is one of the primary measures used to restrain the spread of COVID-19 in the pandemic all over the world. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost three years, which caused severe adverse outcomes in health, society and economy.

OBJECTIVE

This study aims to quantify the impact of mobility reduction on COVID-19 transmission according to mobility distance, locations and demographic factors to identify hotspots of transmission and guide public health policies.

METHODS

Millions of the anonymized, aggregated mobile phone position data between Jan 1 and Feb 24, 2020 was collected for the nine mega cities Greater Bay Area (GBA), China. A generalized linear model (GLM) was established to test the association between mobility volume (number of trips) and COVID-19 transmission. Subgroups analysis was also performed for sex, age, travel locations and travel distance. The statistical interaction terms were included in a variety of models that express different relations between the involved variables.

RESULTS

The GLM analysis demonstrated a significant association between the COVID-19 growth rate ratio (GR) and mobility volume. A stratification analysis revealed a higher effect of mobility volume on the COVID-19 growth rate ratio (GR) among people aged 50-59 years (a decrease of 13.17% for GR per 10% reduction of mobility volume for persons 50-59 years, P <.001) than for other age groups (a decrease of 7.80%, 10.43%, 7.48%, 8.01%, 10.43% for age groups of ≤18, 19-29, 30-39, 40-49, ≥ 60 years, respectively, Pinteraction=.024). The impact of mobility reduction on COVID-19 transmission was higher in transit stations and shopping areas: a decrease of 0.67, 0.53, 0.30, 0.37, 0.44, 0.32 for instantaneous reproduction number R(t) per 10% reduction in mobility volume to transit stations, shopping, work, school, recreation, and other locations, separately (Pinteraction=.016). The association between reduction in mobility volume and COVID-19 transmission was lower with decreasing mobility distance as there was significant interaction between mobility volume and mobility distance on R(t) (Pinteraction<.001). Specifically, the R(t) reduced by 11.97% per 10% reduction of mobility volume when the mobility distance increased to 110% (Spring Festival), by 6.74% when distance remained unchanged and by 1.52% when the distance decreased to 90%.

CONCLUSIONS

The association between mobility reduction and COVID-19 transmission significantly varied by mobility distance, locations and age. The substantially higher impact of mobility volume on COVID-19 transmission in longer travel distance, certain age groups, and for specific travel destinations highlights the potential to optimize the effectiveness of mobility restriction strategies. The results from our study demonstrate the power of having a mobility network using mobile phone data for surveillance that monitor movement at a detailed level to measure the potential impacts of future pandemics.

CLINICALTRIAL

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.

Editorial: Infectious Disease Epidemiology and Transmission Dynamics

Infectious diseases, such as COVID-19 [...].

Impact of mass rapid antigen testing for SARS-CoV-2 to mitigate Omicron outbreaks in China

We analysed the effectiveness of various non-pharmaceutical interventions in containing the 2022 Omicron outbreak in China. The results show that the Rapid Antigen Test contributed to containing the outbreak, reducing the reproduction number by 0.788 (95% CI:−0.306, 1.880) in studied cities.

Reproduction number of monkeypox in the early stage of the 2022 multi-country outbreak

Monkeypox, a fast-spreading viral zoonosis outside of Africa in May 2022, has put scientists on alert. We estimated the reproduction number to be 1.39 (95% CrI: 1.37, 1.42) by aggregating all cases in 70 countries as of 22 July 2022.

Serial intervals and incubation periods of the monkeypox virus clades

Estimating serial interval (SI) and incubation period (IP) is necessary to interpret transmission trends and optimize contact tracing and isolation measures. We conducted a systematic review to synthesize the evidence for serial interval and incubation period of the monkeypox virus and further estimated the SI and IP of each clade.

Reproduction numbers of SARS-CoV-2 Omicron subvariants

Estimating the effective reproduction number of Omicron subvariants is crucial for evaluating the effectiveness of control measures, and adjusting control measures promptly. We conducted a systematic review to synthesize the evidence from estimates of the reproduction numbers for Omicron subvariants, and estimated their effective reproduction number.

Understanding the impact of rapid antigen tests on SARS-CoV-2 transmission in the fifth wave of COVID-19 in Hong Kong in early 2022

The fast-spreading Omicron variant of SARS-CoV-2 overwhelmed Hong Kong, causing the fifth wave of COVID-19. It remains to be determined what mitigation measures might have played a role in reversing the rising trend of confirmed cases in this major outbreak. The government of Hong Kong has launched the mass rapid antigen tests (RAT) in the population and the StayHomeSafe scheme since February 2022. In this study, we examined the impact of the mass RAT on disease transmission and the case fatality ratio. It was suggested that the implementation of RAT plausibly played a role in the steady decrease of the effective reproduction number, leading to diminished SARS-CoV-2 transmission. In addition, we projected the disease burden of the outbreak in a scenario analysis to highlight the necessity of the StayHomeSafe scheme in Hong Kong. The Omicron outbreak experience in Hong Kong may provide actionable insights for navigating the challenges of COVID-19 surges in other regions and countries.

Epidemiologic information discovery from open-access COVID-19 case reports via pretrained language model

Although open-access data are increasingly common and useful to epidemiological research, the curation of such datasets is resource-intensive and time-consuming. Despite the existence of a major source of COVID-19 data, the regularly disclosed case reports were often written in natural language with an unstructured format. Here, we propose a computational framework that can automatically extract epidemiological information from open-access COVID-19 case reports. We develop this framework by coupling a language model developed using deep neural networks with training samples compiled using an optimized data annotation strategy. When applied to the COVID-19 case reports collected from mainland China, our framework outperforms all other state-of-the-art deep learning models. The information extracted from our approach is highly consistent with that obtained from the gold-standard manual coding, with a matching rate of 80%. To disseminate our algorithm, we provide an open-access online platform that is able to estimate key epidemiological statistics in real time, with much less effort for data curation.

•

We propose a method to obtain epidemiological information from COVID-19 case reports

•

The extracted information has 80% matching rate with the gold-standard manual coding

•

We provide an online platform that can analyze epidemiological statistics in real time

Prediction of upcoming global infection burden of influenza seasons after relaxation of public health and social measures during the COVID-19 pandemic: a modelling study

BACKGROUND

The transmission dynamics of influenza were affected by public health and social measures (PHSMs) implemented globally since early 2020 to mitigate the COVID-19 pandemic. We aimed to assess the effect of COVID-19 PHSMs on the transmissibility of influenza viruses and to predict upcoming influenza epidemics.

METHODS

For this modelling study, we used surveillance data on influenza virus activity for 11 different locations and countries in 2017-22. We implemented a data-driven mechanistic predictive modelling framework to predict future influenza seasons on the basis of pre-COVID-19 dynamics and the effect of PHSMs during the COVID-19 pandemic. We simulated the potential excess burden of upcoming influenza epidemics in terms of fold rise in peak magnitude and epidemic size compared with pre-COVID-19 levels. We also examined how a proactive influenza vaccination programme could mitigate this effect.

FINDINGS

We estimated that COVID-19 PHSMs reduced influenza transmissibility by a maximum of 17·3% (95% CI 13·3-21·4) to 40·6% (35·2-45·9) and attack rate by 5·1% (1·5-7·2) to 24·8% (20·8-27·5) in the 2019-20 influenza season. We estimated a 10-60% increase in the population susceptibility for influenza, which might lead to a maximum of 1-5-fold rise in peak magnitude and 1-4-fold rise in epidemic size for the upcoming 2022-23 influenza season across locations, with a significantly higher fold rise in Singapore and Taiwan. The infection burden could be mitigated by additional proactive one-off influenza vaccination programmes.

INTERPRETATION

Our results suggest the potential for substantial increases in infection burden in upcoming influenza seasons across the globe. Strengthening influenza vaccination programmes is the best preventive measure to reduce the effect of influenza virus infections in the community.

FUNDING

Health and Medical Research Fund, Hong Kong.

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022

INTRODUCTION

Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the "Dynamic COVID-zero" strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures.

METHODS

Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.

RESULTS

Under the transmission scenario (R₀ =5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days.

CONCLUSIONS

Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 - especially when new variants emerge.

Risk assessment of imported COVID-19 in China: A modelling study in Sichuan Province

The importation of COVID-19 cases in China is due to the returning of Chinese citizens abroad, where the majority of cases stand. This study aimed to evaluate the risk of importing COVID-19 into the Sichuan Province of China and conduct a short-term risk prediction assessment and analysis. Data on COVID-19 cases in each country and Sichuan were collected, as well as visitors to Sichuan, population, area, and medical resources in each city in Sichuan province. According to different control strategies of entry aviation and quarantine control, we built models of epidemic transmission to estimate the risk for imported COVID-19 cases in 21 cities of Sichuan. Within 140 days of the policy change's implementation, the number of susceptible, infected, and recovered people in all cities followed the same pattern over time: (1) the number of susceptible people declined slowly at first, then accelerated to reach a stable value; (2) the number of infections gradually increased to a peak, then decreased; and (3) the number of recovered patients gradually increased to a stable value. Under the four different scenarios, there were no significant differences between the risk peaks because the social distance did not change. However, the peak time would be delayed due to the implementation of flight control and nucleic acid detection measures. The improvement of foreign epidemics (reduction of attenuation factors) all delayed the arrival of the peak risk value in Chengdu by about 20 days; however, the size of the peak value did not change significantly. The improvement of nucleic acid detection accuracy delayed the arrival of the peak risk value in Chengdu, but the size of the peak value did not change significantly. Therefore, flight control and the improvement of nucleic acid detection accuracy and overseas epidemic situations have positively affected the prevention and control of the epidemic in Sichuan.

International risk of SARS-CoV-2 Omicron variant importations originating in South Africa

Omicron, a fast-spreading SARS-CoV-2 variant of concern reported to the World Health Organization on 24 November 2021, has raised international alarm. We estimated there is at least 50% chance that Omicron had been introduced by travellers from South Africa into 11 of the 14 countries studied by 28 November 2021.

Shorter serial intervals and incubation periods in SARS-CoV-2 variants than the SARS-CoV-2 ancestral strain

The Delta and Omicron variants have the pooled estimates of serial interval as 3.4 days (95% CI: 3.0, 3.7) and 3.1 days (95% CI: 2.9, 3.2), respectively; incubation periods as 4.8 days (95% CI: 3.9, 5.6) and 3.6 days (95% CI: 2.3, 4.9), respectively.

The effectiveness of COVID-19 testing and contact tracing in a US city

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.

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.

Assessing the Dynamic Outcomes of Containment Strategies against COVID-19 under Different Public Health Governance Structures: A Comparison between Pakistan and Bangladesh

COVID-19 scenarios were run using an epidemiological mathematical model (system dynamics model) and counterfactual analysis to simulate the impacts of different control and containment measures on cumulative infections and deaths in Bangladesh and Pakistan. The simulations were based on national-level data concerning vaccination level, hospital capacity, and other factors, from the World Health Organization, the World Bank, and the Our World in Data web portal. These data were added to cumulative infections and death data from government agencies covering the period from 18 March 2020 to 28 February 2022. Baseline curves for Pakistan and Bangladesh were obtained using piecewise fitting with a consideration of different events against the reported data and allowing for less than 5% random errors in cumulative infections and deaths. The results indicate that Bangladesh could have achieved more reductions in each key outcome measure by shifting its initial lockdown at least five days backward, while Pakistan would have needed to extend its lockdown to achieve comparable improvements. Bangladesh’s second lockdown appears to have been better timed than Pakistan’s. There were potential benefits from starting the third lockdown two weeks earlier for Bangladesh and from combining this with the fourth lockdown or canceling the fourth lockdown altogether. Adding a two-week lockdown at the beginning of the upward slope of the second wave could have led to a more than 40 percent reduction in cumulative infections and a 35 percent reduction in cumulative deaths for both countries. However, Bangladesh’s reductions were more sensitive to the duration of the lockdown. Pakistan’s response was more constrained by medical resources, while Bangladesh’s outcomes were more sensitive to both vaccination timing and capacities. More benefits were lost when combining multiple scenarios for Bangladesh compared to the same combinations in Pakistan. Clearly, cumulative infections and deaths could have been highly impacted by adjusting the control and containment measures in both national settings. However, COVID-19 outcomes were more sensitive to adjustment interventions for the Bangladesh context. Disaggregated analyses, using a wider range of factors, may reveal several sub-national dynamics. Nonetheless, the current research demonstrates the relevance of lockdown timing adjustments and discrete adjustments to several other control and containment measures.

The Distribution, Seasonal Abundance, and Environmental Factors Contributing to the Presence of the Asian Longhorned Tick (Haemaphysalis longicornis, Acari: Ixodidae) in Central Appalachian Virginia

Over the past decade, Haemaphysalis longicornis, the Asian longhorned tick, has undergone a geographic range expansion in the United States, from its historical range in east Asia. This tick has been characterized by its frequent parasitism of livestock, an ability to reproduce through parthenogenesis, and its ability to transmit a variety of vector-borne pathogens to livestock, wildlife, and human hosts in its native geographic range. Thus far in the United States, 17 states have reported H. longicornis populations, including 38 counties in Virginia. These numbers come from presence-absence reports provided to the U.S. Department of Agriculture, but little has been reported about this ticks' seasonality in Virginia or its habitat preferences. Our current study detected H. longicornis populations in seven of the nine surveyed counties in Virginia. Haemaphysalis longicornis were observed in multiple habitat types including mixed hardwood forests and pastures, with abundant H. longicornis populations detected at one particular pasture site in Wythe County. This study also attempted to investigate environmental conditions that may be of importance in predicting tick presence likelihood. While sample size limited the scope of these efforts, habitat type and climatic metrics were found to be important indicators of H. longicornis collection success and abundance for both the nymphal and larval life stages. This current study reports useful surveillance data for monitoring these tick populations as they become established in the western half of Virginia and provides insight into their current distribution and maintenance over a large study region.

Systematic review and meta-analyses of superspreading of SARS-CoV-2 infections

Superspreading, or overdispersion in transmission, is a feature of SARS-CoV-2 transmission which results in surging epidemics and large clusters of infection. The dispersion parameter is a statistical parameter used to characterize and quantify heterogeneity. In the context of measuring transmissibility, it is analogous to measures of superspreading potential among populations by assuming that collective offspring distribution follows a negative-binomial distribution. We conducted a systematic review and meta-analysis on globally reported dispersion parameters of SARS-CoV-2 infection. All searches were carried out on 10 September 2021 in PubMed for articles published from 1 January 2020 to 10 September 2021. Multiple estimates of the dispersion parameter have been published for 17 studies, which could be related to where and when the data was obtained, in 8 countries (e.g., China, USA, India, Indonesia, Israel, Japan, New Zealand, and Singapore). High heterogeneity was reported among the included studies. The mean estimates of dispersion parameters range from 0.06 to 2.97 over eight countries, the pooled estimate was 0.55 (95% CI: 0.30, 0.79), with changing means over countries and decreasing slightly with the increasing reproduction number. The expected proportion of cases accounting for 80% of all transmissions is 19% (95% CrI: 7, 34) globally. The study location and method were found to be important drivers for diversity in estimates of dispersion parameters. While under high potential of superspreading, larger outbreaks could still occur with the import of the COVID-19 virus by traveling even when an epidemic seems to be under control. This article is protected by copyright. All rights reserved.

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.

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study

BACKGROUND

As SARS-CoV-2 vaccines are administered worldwide, the COVID-19 pandemic continues to exact significant human and economic costs. Mass testing of unvaccinated individuals followed by isolation of positive cases can substantially mitigate risks and be tailored to local epidemiological conditions to ensure cost effectiveness.

METHODS

Using a multi-scale model that incorporates population-level SARS-CoV-2 transmission and individual-level viral load kinetics, we identify the optimal frequency of proactive SARS-CoV-2 testing, depending on the local transmission rate and proportion immunized.

FINDINGS

Assuming a willingness-to-pay of US$100,000 per averted year of life lost (YLL) and a price of $10 per test, the optimal strategy under a rapid transmission scenario (Re ∼ 2.5) is daily testing until one third of the population is immunized and then weekly testing until half the population is immunized, combined with a 10-day isolation period of positive cases and their households. Under a low transmission scenario (Re ∼ 1.2), the optimal sequence is weekly testing until the population reaches 10% partial immunity, followed by monthly testing until 20% partial immunity, and no testing thereafter.

INTERPRETATION

Mass proactive testing and case isolation is a cost effective strategy for mitigating the COVID-19 pandemic in the initial stages of the global SARS-CoV-2 vaccination campaign and in response to resurgences of vaccine-evasive variants.

FUNDING

US National Institutes of Health, US Centers for Disease Control and Prevention, HK Innovation and Technology Commission, China National Natural Science Foundation, European Research Council, and EPSRC Impact Acceleration Grant.

Reproduction Numbers of SARS-CoV-2 Variants: A Systematic Review and Meta-analysis

The COVID-19 pandemic continues to pose substantial risks to public health, worsened by the emergence of SARS-CoV-2 variants which may have a higher transmissibility and reduce vaccine effectiveness. We conducted a systematic review and meta-analysis on reproduction numbers of SARS-CoV-2 variants and provided pooled estimates for each variant.

D-Galactose-Induced Accelerated Aging Model on Auditory Cortical Neurons by Regulating Oxidative Stress and Apoptosis in Vitro

OBJECTIVES

Age-related hearing loss (ARHL) is much more prevalent with age, affecting not only peripheral but central auditory system. We have previously established an aging model of peripheral auditory system in vitro using cultured cochlear basilar membrane. However, there is no ideal accelerated aging model on central auditory system in vitro. To establish the aging model, auditory cortical neurons (ACNs) were primary cultured and treated with either vehicle or different doses of D-galactose (D-gal). We studied the effect of D-gal on ACNs by evaluating the hallmarks of aging, including cell proliferation, oxidative stress, mitochondrial function, and neuronal apoptosis. Compared with the control group, cell viability was significantly inhibited in the D-gal-treated group in a dose-dependent manner. The production of reactive oxygen species was strongly increased in the D-gal-treated group. Meanwhile, the level of 8-hydroxy-2'-deoxyguanosine, which is a biomarker of DNA oxidative damage, was even higher in the D-gal-treated group than that in the control group. Conversely, the levels of ATP and mitochondrial membrane potential were notably decreased in the D-gal-treated group contrast to that in the control group. Furthermore, the number of neuronal apoptosis in the D-gal-treated group, compared with that in the control group, was dramatically increased in a dose-dependent approach. Together, our results demonstrate that ACNs treated with D-gal in vitro display senescence characteristics by regulating oxidative stress and apoptosis, indicating accelerated aging model on ACNs are successfully established. And the model provides a promising approach for exploring underlying mechanisms of the ARHL.

Effectiveness of International Travel Controls for Delaying Local Outbreaks of COVID-19

During the coronavirus disease pandemic, international travel controls have been widely adopted. To determine the effectiveness of these measures, we analyzed data from 165 countries and found that early implementation of international travel controls led to a mean delay of 5 weeks in the first epidemic peak of cases.

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020–2021 Season

Background. In mid-2020, there was significant concern that the overlapping 2020–2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Methods. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020–2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021. Results. Across all scenarios, we projected that the COVID-19 burden would dwarf that of influenza. In all but our lowest transmission scenarios, intensive care units were overwhelmed by COVID-19 patients, with the levels of influenza immunization having little impact on health care capacity needs. Consistent with our projections, sustained nonpharmaceutical interventions (NPIs) in Austin prevented COVID-19 from overwhelming health care systems and almost completely suppressed influenza during the 2020–2021 respiratory virus season. Limitations. The model assumed no cross-immunity between SARS-CoV-2 and influenza, which might reduce the burden or slow the transmission of 1 or both viruses. Conclusion. Before the widespread rollout of the SARS-CoV-2 vaccine, COVID-19 was projected to cause an order of magnitude more hospitalizations than seasonal influenza because of its higher transmissibility and severity. Consistent with predictions assuming strong NPIs, COVID-19 strained but did not overwhelm local health care systems in Austin, while the influenza burden was negligible. Implications. Nonspecific NPI efforts can dramatically reduce seasonal influenza burden and preserve health care capacity during respiratory virus season.

Pandemic fatigue and attenuated impact of avoidance behaviours against COVID-19 transmission in Hong Kong by cross-sectional telephone surveys

OBJECTIVES

This study aims to explore the attenuated impact of reported avoidance behaviours adherence on the transmission of COVID-19 through cross-sectional surveys in Hong Kong, in order to make up for the lack of research on avoidance behaviours fatigue.

DESIGN

40 cross-sectional telephone surveys.

SETTING

All districts in Hong Kong.

PARTICIPANTS

31 332 Cantonese or English-speaking participants at age of 18 years or above.

METHODS

We collected data on behaviours and estimated the average effective reproduction number ([Formula: see text]) among the Hong Kong adult population during the COVID-19 epidemic wave in November-December 2020 and compared with the preceding epidemic in June-July 2020.

RESULTS

We observed a reduction in adherence to voluntary avoidance behaviours due to pandemic fatigue, but continued adherence to regulated avoidance behaviours. The average [Formula: see text] during the post-work from home period was higher in November-December wave with estimated [Formula: see text] of 0.81 (95% CI: 0.75 to 0.87) compared with the June-July wave with an [Formula: see text] of 0.67 (95% CI: 0.60 to 0.75).

CONCLUSIONS

The declined effectiveness of social distancing interventions in reducing COVID-19 transmission was associated with fatigue with voluntary avoidance behaviours in Hong Kong population, implying a need for the government to reinvigorate the public to maintain effective pandemic control.

International risk of SARS-CoV-2 Omicron variant importations originating in South Africa

Omicron, a fast-spreading SARS-CoV-2 variant of concern reported to the World Health Organization on November 24, 2021, has raised international alarm. We estimated there is at least 50% chance that Omicron had been introduced by travelers from South Africa into all of the 30 countries studied by November 27, 2021.

Predictive value of GRACE score combined with BNP and glycosylated hemoglobin for in-hospital cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention

Purpose

To investigate the value of Global Registry of Acute Coronary Events (GRACE) score combined with B-type natriuretic peptide (BNP) and glycosylated hemoglobin (HbA1c) in predicting in-hospital major adverse cardiovascular events (MACE) in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI).

Methods

A total of consecutive 675 patients with acute coronary syndrome (ACS) admitted to our hospital from June 2019 to June 2020, and finally, 319 patients treated with the percutaneous coronary intervenion (PCI) were enrolled. Major adverse cardiovascular events (MACE) during hospitalization included cardiac death, cardiogenic shock, congestive heart failure, recurrent ischemic chest pain and malignant arrhythmia. The area under the curve (AUC) was used to evaluate the predictive value of MACE during hospitalization.

Results

Among 319 patients, during hospitalization, 26 patients (8.15%) experienced the MACE. Compared to that of non-MACE group, there were more patients with previous history of heart failure (P&lt;0.001), lower in-admission systolic and diastolic blood pressure (P all&lt;0.05), and higher heart rate, GRACE score, BNP, and HbA1c levels in the MACE group (P all&lt;0.05). Multivariate logistic regression analysis showed that history of heart failure (OR: 1.498, 95% CI: 1.144–2.249), GRACE score (OR: 1.040, 95% CI: 1.017–1.063), BNP (OR: 1.019, 95% CI: 1.012–1.026) and HbA1C (OR: 1.199, 95% CI: 1.043–1.378) were independent risk factors for MACE in patients with ACS after PCI (P all&lt;0.05). The AUC of GRACE score for predicting MACE in ACS patients after PCI was 0.758, while the AUC of BNP and HbA1C was 0.838 and 0.788, respectively. When GRACE score combined with BNP and HbA1c, the AUC was increased to 0.876, which was significantly higher than the GRACE score alone (Z=4.142, P&lt;0.001).

Conclusion

In this study, we reported for the first time, GRACE score combined with BNP and HbA1c significantly improved the predictive value of in-hospital MACE in ACS patients after PCI compared with traditional GRACE score, which can help clinicians identify high risk patients to improve their prognosis in the clinical practice.

Funding Acknowledgement

Type of funding sources: Public hospital(s). Main funding source(s): Young and middle-aged talents in the XPCC Science and Technology Project (2020CB012); Key Science and Technology Project of Shihezi (2019ZH09) ROC Curve