Semisupervised score based matching algorithm to evaluate the effect of public health interventions (preprint)

Multivariate matching algorithms "pair" similar study units in an observational study to remove potential bias and confounding effects caused by the absence of randomizations. In one-to-one multivariate matching algorithms, a large number of "pairs" to be matched could mean both the information from a large sample and a large number of tasks, and therefore, to best match the pairs, such a matching algorithm with efficiency and comparatively limited auxiliary matching knowledge provided through a "training" set of paired units by domain experts, is practically intriguing. We proposed a novel one-to-one matching algorithm based on a quadratic score function $S_{\beta}(x_i,x_j)= \beta^T (x_i-x_j)(x_i-x_j)^T \beta$. The weights $\beta$, which can be interpreted as a variable importance measure, are designed to minimize the score difference between paired training units while maximizing the score difference between unpaired training units. Further, in the typical but intricate case where the training set is much smaller than the unpaired set, we propose a \underline{s}emisupervised \underline{c}ompanion \underline{o}ne-\underline{t}o-\underline{o}ne \underline{m}atching \underline{a}lgorithm (SCOTOMA) that makes the best use of the unpaired units. The proposed weight estimator is proved to be consistent when the truth matching criterion is indeed the quadratic score function. When the model assumptions are violated, we demonstrate that the proposed algorithm still outperforms some popular competing matching algorithms through a series of simulations. We applied the proposed algorithm to a real-world study to investigate the effect of in-person schooling on community Covid-19 transmission rate for policy making purpose.

Time-Since-Infection Model for Hospitalization and Incidence Data (preprint)

The Time Since Infection (TSI) models, which use disease surveillance data to model infectious diseases, have become increasingly popular recently due to their flexibility and capacity to address complex disease control questions. However, a notable limitation of TSI models is their primary reliance on incidence data. Even when hospitalization data are available, existing TSI models have not been crafted to estimate disease transmission or predict disease-related hospitalizations - metrics crucial for understanding a pandemic and planning hospital resources. Moreover, their dependence on reported infection data makes them vulnerable to variations in data quality. In this study, we advance TSI models by integrating hospitalization data, marking a significant step forward in modeling with TSI models. Our improvements enable the estimation of key infectious disease parameters without relying on contact tracing data, reduce bias in incidence data, and provide a foundation to connect TSI models with other infectious disease models. We introduce hospitalization propensity parameters to jointly model incidence and hospitalization data. We use a composite likelihood function to accommodate complex data structure and an MCEM algorithm to estimate model parameters. We apply our method to COVID-19 data to estimate disease transmission, assess risk factor impacts, and calculate hospitalization propensity.

Simultaneous Detection of SARS-CoV-2 and Six Other Human Coronaviruses by Multiplex PCR and MALDI-TOF MS (preprint)

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is challenging the health systems worldwide, and large population testing is a vital step to control this pandemic. Here, we developed a new method (named HCoV-MS), which combines multiplex PCR with matrix-assisted laser desorption/ionization-time of flight mass spectrometry to simultaneously detect and differentiate seven human coronaviruses (HCoVs). The HCoV-MS method had good specificity and sensitivity, with a detection limit of 1-5 copies/reaction. To validate the HCoV-MS method, we tested 151 clinical samples, and the results showed good concordance with real-time PCR. In addition, 41 D614G variants were identified, which were consistent with the sequencing results. This method was also used in EQAE-SARS-COV in 2020, and all the samples were accurately identified. Taken together, HCoV-MS could be used as an effective method for large-scale detection. It was also capable of detecting key single nucleotide polymorphism about variants.

Resistance mechanisms of SARS-CoV-2 3CLpro to the non-covalent inhibitor WU-04 (preprint)

Drug resistance poses a significant challenge in the development of effective therapies against SARS-CoV-2. Here, we identified two double mutations, M49K/M165V and M49K/S301P, in the 3C-like protease (3CLpro) that confer resistance to a novel non-covalent inhibitor, WU-04. Crystallographic analysis indicates that the M49K mutation destabilizes the WU-04 binding pocket, impacting the binding of WU-04 more significantly than the binding of 3CLpro substrates. The M165V mutation directly interferes with WU-04 binding. The S301P mutation, which is far from the WU-04 binding pocket, indirectly affects WU-04 binding by restricting the rotation of 3CLpros C-terminal tail and impeding 3CLpro dimerization. We further explored 3CLpro mutations that confer resistance to two clinically used inhibitors: ensitrelvir and nirmatrelvir, and revealed a trade-off between the catalytic activity, thermostability, and drug resistance of 3CLpro. We found that mutations at the same residue (M49) can have distinct effects on the 3CLpro inhibitors, highlighting the importance of developing multiple antiviral agents with different skeletons for fighting SARS-CoV-2. These findings enhance our understanding of SARS-CoV-2 resistance mechanisms and inform the development of effective therapeutics.

Estimating the Instantaneous Reproduction Number With Imperfect Data: A Method to Account for Case-Reporting Variation and Serial Interval Uncertainty (preprint)

During an infectious disease outbreak, public health decision-makers require real-time monitoring of disease transmission to respond quickly and intelligently. In these settings, a key measure of transmission is the instantaneous time-varying reproduction number, $R_t$. Estimation of this number using a Time-Since-Infection model relies on case-notification data and the distribution of the serial interval on the target population. However, in practice, case-notification data may contain measurement error due to variation in case reporting while available serial interval estimates may come from studies on non-representative populations. We propose a new data-driven method that accounts for particular forms of case-reporting measurement error and can incorporate multiple partially representative serial interval estimates into the transmission estimation process. In addition, we provide practical tools for automatically identifying measurement error patterns and determining when measurement error may not be adequately accounted for. We illustrate the potential bias undertaken by methods that ignore these practical concerns through a variety of simulated outbreaks. We then demonstrate the use of our method on data from the COVID-19 pandemic to estimate transmission and explore the relationships between social distancing, temperature, and transmission.

Explaining customer satisfaction via hotel reviews: A comparison between pre- and post-COVID-19 reviews

This study aims to examine whether and how COVID-19 has changed the effects of consumer evaluations of hotel attributes on customer satisfaction. We extracted positive and negative evaluations of hotel attributes from online reviews both pre- and post-COVID-19 and examined their effects on customer satisfaction. Using a sample of 1,947,391 reviews of 35,022 Chinese hotels collected from ctrip.com, we conducted a fine-grained sentiment analysis based on sentiment triples to identify important positive and negative evaluations of hotel attributes. Subsequently, we applied regression analyses to examine how these evaluations of hotel attributes influenced customer satisfaction. The results revealed that positive and negative evaluations of hotel attributes had differentiated effects on customer satisfaction. We classified these attributes into basic, excitement, and performance attributes, from which management implications can be derived.

MERS-CoV e protein induces autophagy in 293T cells

Objective: To investigate the molecular mechanism of the action by which the MERS-CoV E proxein induces autophagy in 293T cells.

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro (preprint)

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC 50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence Summary A oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

Integrated bioinformatics analysis to determine the impact of SARS-CoV-2 infections to Heart Failure patients (preprint)

Background: COVID-19, the highly contagious respiratory disease, has become a major threat to humanity, and its extrapulmonary effects were also evident. Heart failure (HF) may be the result of myocardial damage associated with COVID-19. Methods: : To understand the relationship between SARS-COV-2 and HF, we used bioinformatics analysis to identify common pathways and molecular biomarkers for HF and COVID-19. In this study, two datasets (GSE152418, GSE57338) from Gene Expression Omnibus (GEO) were used to identify differentially expressed genes (DEGs) of SARS-COV-2 infection in HF patients to find common pathways and drug candidates. Results: : A total of 123 common DEGs were identified in the two datasets. Using a variety of bioinformatics tools, we first constructed protein-protein interactions (PPI) and then identified hub genes that could be served as potential biomarkers or novel therapeutic strategies. In addition, some common associations between HF and the progression of COVID-19 infection were found by using functional under ontological terms and pathway analysis. Through the datasets, we also identified transcription factor-gene interactions, protein-drug interactions, and co-regulatory network of DEGs-miRNAs with common DEGs. We built gene-disease association network to represent diseases associated with mutual DEGs. Conclusions: : Our study has identified the candidate hub genes and drugs that might become a new therapeutic target for novel coronavirus vaccine development and treatment in COVID-19 and HF.

Economic Value of Vaccines to Address the COVID-19 Pandemic in Hong Kong: A Cost-Effectiveness Analysis

Objective The coronavirus disease 2019 (COVID-19) pandemic has imposed significant costs on economies. Safe and effective vaccines are a key tool to control the pandemic;however, vaccination programs can be costly. Are the benefits they bestow worth the costs they incur? The relative value of COVID-19 vaccines has not been widely assessed. In this study, a cost-effectiveness analysis was performed to provide evidence of the economic value of vaccines in Hong Kong. Method We developed a Markov model of COVID-19 infections using a susceptible–infected–recovered structure over a 1-year time horizon from a Hong Kong healthcare sector perspective to measure resource utilization, economic burden, and disease outcomes. The model consisted of two arms: do nothing and implement a vaccination program. We assessed effectiveness using units of quality-adjusted life years (QALYs) to measure the incremental cost-effectiveness at a HKD 1,000,000/QALY threshold. Results The vaccination program, which has reached approximately 72% of the population of Hong Kong with two vaccine doses, was found to have a cost of HKD 22,339,700 per QALY gained from February 2021 to February 2022. At a willingness-to-pay threshold, the vaccination program was not cost-effective in the context of the low prevalence of COVID-19 cases before the Omicron wave. However, the cost-effectiveness of a COVID-19 vaccine is sensitive to the infection rate. Hong Kong is now experiencing the fifth wave of the Omicron. It is estimated that the ICER of the vaccination program from February 2022 to February 2023 was HKD 310,094. The vaccination program in Hong Kong was cost-effective in the context of the Omicron. Conclusions Vaccination programs incur a large economic burden, and we therefore need to acknowledge their limitations in the short term. This will help relevant departments implement vaccination programs. From a longer-term perspective, the vaccination program will show great cost-effectiveness once infection rates are high in a regional outbreak. Compared with other age groups, it is suggested that the elderly population should be prioritized to improve the vaccine coverage rate.

Emergency management strategy for prevention and control of novel coronavirus pneuminia-Tenth people's hospital pf Tongi University

To explore scientifically configure medical equipment, standardize distribution of protective materials and manage safely, efficiently in prevention and control of novel coronavirus pneumonia, which comprehensively ensure medical personnel safety and provide support for battle against epidemic. The medical equipment division actively implemented relevant national requirements and coordinated hospital internal, information unblocked and data accuracy. Combined with epidemic character-istics. the needs of key departments were guaranteed based on existing medical equipment and protective materials, and re-fined medical equipment management in emergency situations. The real-time department transfer and scientific management of hospital could effectively respond to risks caused by sudden novel coronavirus pneumonia. In condition of shortage of supplies, hospital was prevented clinical cross-infection and ensured normal operation of medical equipment. which provided reliable and effective medical equipment guarantee. After emergency management during epidemic, summarize effective management and control medical equipment department in special period to ensure overall safe and stable operation at hospital, which has strong practicability and repeatability.

Clinical characteristics of 134 convalescent patients with COVID-19 in Guizhou, China (preprint)

Background: Previous studies have focused on the clinical characteristics of hospitalized patients with the novel 2019 coronavirus disease (COVID-19). Limited data are available for convalescent patients. This study aimed to evaluate the clinical characteristics of discharged COVID-19 patients. Methods: : In this retrospective study, we extracted data for 134 convalescent patients with COVID-19 in Guizhou Provincial Staff Hospital from February 15 to March 31, 2020. Cases were analyzed on the basis of demographic, clinical, and laboratory data as well as radiological features. Results: : Of 134 convalescent patients with COVID-19, 19 (14.2%) were severe cases, while 115 (85.8%) were non-severe cases. The median patient age was 33 years (IQR, 21.8 to 46.3), and the cohort included 69 men and 65 women. Compared with non-severe cases, severe patients were older and had more chronic comorbidities, especially hypertension, diabetes, and thyroid disease (P<0.05). Leukopenia was present in 32.1% of the convalescent patients and lymphocytopenia was present in 6.7%, both of which were more common in severe patients. 48 (35.8%) of discharged patients had elevated levels of alanine aminotransferase, which was more common in adults than in children (40.2% vs 13.6%, P=0.018). A normal chest CT was found in 61 (45.5%) patients during rehabilitation. Severe patients had more ground-glass opacity, bilateral patchy shadowing, and fibrosis. No significant differences were observed in the positive rate of IgG and/or IgM antibodies between severe and non-severe patients. Conclusion: Leukopenia, lymphopenia, ground-glass opacity, and fibrosis are common in discharged severe COVID-19 patients, and liver injury is common in discharged adult patients. We suggest physicians develop follow-up treatment plans based on the different clinical characteristics of convalescent patients.

Higher pharyngeal epithelial gene expression of Angiotensin-Converting Enzyme-2 in upper respiratory infection patients (preprint)

We analyzed the expression of ACE2 in pharyngeal epithelium and examined its relationship with clinical features and serological parameters in the upper respiratory infection (URI) patients. The expression of ACE2 were significantly higher in URI patients than in healthy controls individuals, and positively correlated with age and body temperature.

AXL Promotes SARS-CoV-2 Infection of Pulmonary and Bronchial Epithelial Cells (preprint)

The current coronavirus disease 2019 (COVID-19) pandemic presents a global public health challenge. The viral pathogen responsible, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), binds to a host receptor ACE2 through its spike (S) glycoprotein, which mediates membrane fusion and virus entry. Although the role of ACE2 as a receptor for SARS-CoV-2 is clear, studies have shown that ACE2 expression across different human tissues is extremely low, especially in pulmonary and bronchial cells. Thus, other host receptors and/or co-receptors that promote the entry of SARS-CoV-2 into cells of the respiratory system might exist. In this study, we have identified tyrosine-protein kinase receptor UFO (AXL), specifically interacts with SARS-CoV-2 S on the host cell membrane. When overexpressed in cells that do not highly express either AXL or ACE2, AXL promotes virus entry as efficiently as ACE2. Strikingly, deleting AXL, but not ACE2, significantly reduces infection of pulmonary cells by the SARS-CoV-2 virus pseudotype. Soluble human recombinant AXL, but not ACE2, blocks SARS-CoV-2 virus pseudotype infection in pulmonary cells. Taken together, our findings suggest AXL may play an important role in promoting SARS-CoV-2 infection of the human respiratory system and is a potential target in future clinical intervention strategies.

Sample Pooling as a Strategy of SARS-COV-2 Nucleic Acid Screening Increases the False-negative Rate (preprint)

Background Identification of less costly and accurate methods for monitoring novel coronavirus disease 2019 (CoViD-19) transmission has attracted much interest in recent times. Here, we evaluated a pooling method to determine if this could improve screening efficiency and reduce costs while maintaining accuracy in Guangzhou, China. Methods We evaluated 8097 throat swap samples collected from individuals who came for a health check-up or fever clinic in The Third Affiliated Hospital, Southern Medical University between March 4, 2020 and April 26, 2020. Samples were screened for CoViD-19 infection using the WHO-approved quantitative reverse transcription PCR (RT-qPCR) primers. The positive samples were classified into two groups (high or low) based on viral load in accordance with the CT value of COVID-19 RT-qPCR results. Each positive RNA samples were mixed with COVID-19 negative RNA or ddH2O to form RNA pools. Findings Samples with high viral load could be detected in pool negative samples (up to 1/1000 dilution fold). In contrast, the detection of RNA sample from positive patients with low viral load in a pool was difficult and not repeatable. Interpretation Our results show that the COVID-19 viral load significantly influences in pooling efficacy. COVID-19 has distinct viral load profile which depends on the timeline of infection. Thus, application of pooling for infection surveillance may lead to false negatives and hamper infection control efforts. Funding National Natural Science Foundation of China; Hong Kong Scholars Program, Natural Science Foundation of Guangdong Province; Science and Technology Program of Guangzhou, China.

The Association of Social Distancing, Population Density, and Temperature with the SARS-CoV-2 Instantaneous Reproduction Number in Counties Across the United States (preprint)

ImportanceThe Covid-19 pandemic has been marked by considerable heterogeneity in outbreaks across the United States. Local factors that may be associated with variation in SARS-CoV-2 transmission have not been well studied. ObjectiveTo examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time. DesignObservational study Setting211 counties in 46 states and the District of Columbia between February 25, 2020 and April 23, 2020. ParticipantsResidents within the counties (55% of the US population) ExposuresSocial distancing as measured by percent change in visits to non-essential businesses, population density, lagged daily wet bulb temperatures. Main Outcomes and MeasuresThe instantaneous reproduction number (Rt) which is the estimated number of cases generated by one case at a given time during the pandemic. ResultsMedian case incidence was 1185 cases and fatality rate was 43.7 deaths per 100,000 people for the top decile of 21 counties, nearly ten times the incidence and fatality rate in the lowest density quartile. Average Rt in the first two weeks was 5.7 (SD 2.5) in the top decile, compared to 3.1 (SD 1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to non-essential businesses was associated with a 57% decrease in Rt (95% confidence interval, 56% to 58%). Cumulative temperature effects over 4 to 10 days prior to case incidence were nonlinear; relative Rt decreased as temperatures warmed above 32{degrees}F to 53{degrees}F, which was the point of minimum Rt, then increased between 53{degrees}F and 66{degrees}F, at which point Rt began to decrease. At 55{degrees}F, and with a 70% reduction in visits to non-essential business, 96% of counties were estimated to fall below a threshold Rt of 1.0, including 86% of counties among the top density decile and 98% of counties in the lowest density quartile. Conclusions and RelevanceSocial distancing, lower population density, and temperate weather change were associated with a decreased SARS-Co-V-2 Rt in counties across the United States. These relationships can inform selective public policy planning in communities during the SARS-CoV-2 pandemic. Key PointsO_ST_ABSQuestionC_ST_ABSHow is the instantaneous reproduction number (Rt) of SARS-CoV-2 influenced by local area effects of social distancing, wet bulb temperature, and population density in counties across the United States? FindingsSocial distancing, temperate weather, and lower population density were associated with a decrease in Rt. Of these county-specific factors, social distancing appeared to be the most significant in reducing SARS-CoV-2 transmission. MeaningRt varies significantly across counties. The relationship between Rt and county-specific factors can inform policies to reduce SARS-CoV-2 transmission in selective and heterogeneous communities.