Household transmission of SARS-CoV-2 during the Omicron wave in Shanghai, China：a case-ascertained study (preprint)

Since late 2021, the highly transmissible SARS-CoV-2 Omicron variant has driven a new surge of infections across the world. We used a case-ascertained study to determine the features of household transmission of SARS-CoV-2 Omicron variant in Shanghai, China. We collected detailed information on 323 pediatric cases and their 951 household members, all received consecutively intensive RT-PCR testing. We estimated the transmission parameters. Both secondary infection attack rates (SARI) and secondary clinical attack rates (SARC) among adult household contacts were computed, through which the transmission heterogeneities in infectivity and susceptibility were characterized and the vaccine effectiveness were estimated. The mean incubation period and serial interval of Omicron variant were estimated to be 4.6±2.1 days and 3.9±3.7 days. The overall SARI and SARC among adult household contacts were 77.11% (95% confidence interval [CI]: 73.58%-80.63%) and 67.03% (63.09%-70.98%). We found higher household susceptibility in females, while infectivity was not significantly different in primary cases by age, sex, vaccination status and clinical severity. Full vaccination and booster vaccination of inactivated vaccines were 14.8% (5.8%-22.9%) and 18.9% (9.0%-27.7%) effective against Omicron infection and 21.5% (10.4%-31.2%) and 24.3% (12.3%-34.7%) effective against symptomatic disease. Overall, we found high household transmission during the Omicron wave in Shanghai due to asymptomatic and pre-symptomatic transmission in the context of city-wide lockdown, indicating the importance of early detection and timely isolation of SARS-CoV-2 infections and quarantine of close contacts. Marginal effectiveness of inactivated vaccines against Omicron infection poses great challenge for prevention and control of the SARS-CoV-2 Omicron variant.

Household transmission of SARS-CoV-2 during the Omicron wave in Shanghai, China:a case-ascertained study (preprint)

Background Since late 2021, the highly transmissible SARS-CoV-2 Omicron variant has driven a new surge of infections across the world. We used a case-ascertained study to determine the features of household transmission of SARS-CoV-2 Omicron variant in Shanghai, China. Methods We collected detailed information on 323 pediatric cases and their 951 household members in April 2022 during the Omicron outbreak. All household members received consecutively intensive RT-PCR testing for SARS-CoV-2 and routine symptom monitoring within 14 days after exposure to a confirmed case. We described the characteristics of study participants and estimated the transmission parameters. Both secondary infection attack rates (SAR I ) and secondary clinical attack rates (SAR C ) among adult household contacts were computed, through which the transmission heterogeneities in infectivity and susceptibility were characterized and the vaccine effectiveness were estimated. Results We estimated the mean incubation period of SARS-CoV-2 Omicron variant to be 4.6 (median: 4.4, IQR: 3.1-6.0) days and the mean serial interval to be 3.9 (median:4.0, IQR: 1.4-6.5) days. The overall SAR I and SAR C among adult household contacts were 77.11% (95% confidence interval [CI]: 73.58%-80.63%) and 67.03% (63.09%-70.98%). We found higher household susceptibility in females, while infectivity was not significantly different in primary cases by age, sex, vaccination status and clinical severity. The estimated VEs of full vaccination was 14.8% (95% CI: 5.8%-22.9%) against Omicron infection and 21.5% (95% CI: 10.4%-31.2%) against symptomatic disease. The booster vaccination was 18.9% (95% CI: 9.0%-27.7%) and 24.3% (95% CI: 12.3%-34.7%) effective against infection and symptomatic disease, respectively. Conclusions We found high household transmission during the Omicron wave in Shanghai due to asymptomatic and pre-symptomatic transmission in the context of city-wide lockdown, indicating the importance of early detection and timely isolation of SARS-CoV-2 infections and quarantine of close contacts. Marginal effectiveness of inactivated vaccines against Omicron infection poses great challenge for prevention and control of the SARS-CoV-2 Omicron variant.

Osteoporosis in Patients With Respiratory Diseases

Climate change, environmental pollution, and virus epidemics have sharply increased the number of patients suffering from respiratory diseases in recent years. Prolonged periods of illness and drug use increase the occurrence of complications in these patients. Osteoporosis is the common bone metabolism disease with respiratory disturbance, which affects prognosis and increases mortality of patients. The problem of osteoporosis in patients with respiratory diseases needs more attention. In this review, we concluded the characteristics of osteoporosis in some respiratory diseases including COPD, asthma, COVID-19, tuberculosis, and lung cancer. We revealed that hypoxia was the common pathogenesis of osteoporosis secondary to respiratory diseases, with malnutrition and corticosteroid abuse driving the progression of osteoporosis. Hypoxia-induced ROS accumulation and activated HIF-1α lead to attenuated osteogenesis and enhanced osteoclastogenesis in patients with respiratory diseases. Tuberculosis and cancer also invaded bone tissue and reduced bone strength by direct infiltration. For the treatment of osteoporosis in respiratory patients, oral-optimized bisphosphonates were the best treatment modality. Vitamin D was a necessary supplement, both for calcium absorption in osteogenesis and for improvement of respiratory lesions. Reasonable adjustment of the dose and course of corticosteroids according to the etiology and condition of patients is beneficial to prevent the occurrence and development of osteoporosis. Additionally, HIF-1α was a potential target for the treatment of osteoporosis in respiratory patients, which could be activated under hypoxia condition and involved in the process of bone remodeling.

COVIDFast™: A high-throughput and RNA extraction-free method for SARS-CoV-2 detection in swab (SwabFAST™) or saliva (SalivaFAST™) (preprint)

ABSTRACT There is an urgent need of having a rapid, high throughput, yet accurate SARS-COV-2 PCR testing to control the COVID19 pandemic. However, the RNA extraction step in conventional PCR creates a major bottle neck in the diagnostic process. In this paper we modified the CDC COVID-19 assay and developed an RNA-extraction free RT-qPCR assay for SARS-CoV-2, i.e. COVIDFast ™ . Depending on sample types, the assay is further divided into SwabFAST ™ , which uses anterior nares nasal swab, and SalivaFAST ™ , which uses saliva. By utilizing the proprietary buffer for either swab or saliva samples, the performance of SwabFAST or SalivaFAST is equivalent to RNA-extraction SARS-CoV-2 RT-qPCR in both contrived and clinical samples. The limit of detection of either assay is 4 copies/μL. We further developed a semi-automatic system, which is easy to adapt by clinical lab for implementation of a high-throughput SARS-CoV-2 test. Working together with the COVIDCheck Colorado, we have tested over 400,000 samples using COVIDFast (83.62% SwabFAST and 16.38% SalivaFAST) in less than a year, resulting in significant clinical contribution in the battle against COVID-19 during the pandemic.

SARS-CoV-2 viral load monitoring by extraction-free testing of saliva (preprint)

Real-time quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) remains the foundation of SARS-CoV-2 testing due to its accessibility, scalability, and superior assay performance. Variability in specimens and methods prevent standardization of RT-qPCR assays and reliable quantitative reporting to assess viral load. We developed an extraction-free RT-qPCR assay for detection of SARS-CoV-2 in saliva and monitored viral load until convalescence in COVID-19 patients. Comparison of 231 matched anterior nares swab and saliva specimens demonstrated that extraction-free testing of saliva has equivalent analytical and clinical assay performance compared to testing of RNA extracts from either anterior nares or saliva specimens. Analysis of specimen pairs revealed higher viral loads in the nasal cavity compared to the oral cavity, although this difference did not impact clinical sensitivity for COVID-19. Extraction-free testing of a combination specimen consisting of both nasal swab and saliva is also demonstrated. Assessment of viral load by RT-qPCR and parallel digital droplet PCR (ddPCR) revealed that cycle threshold (Ct) values less than approximately 30 correlated well with viral load, whereas Ct values greater than 30 correspond to low viral loads <10 copies/{micro}L. Therefore, extraction-free saliva testing maximizes testing efficiency without compromising assay performance and approximates viral loads >10 copies/{micro}L. This technology can facilitate high-throughput laboratory testing for SARS-CoV-2, monitor viral load in individual patients, and assess efficacy of therapies for COVID-19.

Reopening Borders in the Early Stage of COVID-19 Massive Vaccination: A Mathematic Model to Estimate the Optimal Length of Quarantine Period between Different Regions (preprint)

Background: Quarantine for cross-region traveling has slowed the transmission of SARS-CoV-2/coronavirus. However, it has had a negative impact on mental health and economic recovery. The study aimed to estimate a responsible and pragmatic quarantine period using a mathematic model. Method: We constructed a retrospective mathematical modeling using data from the World Health Organization coronavirus disease database. Four risk levels and 16 different cross-border scenarios were designed and analyzed. We then sought the optimal quarantine duration in different situations using a logarithmic regression analysis. Findings: The mean optimal quarantine days was found to be 1·4, 6·5, 10, and 14 days for the scenarios of traveling from very-high-risk countries to very-high-, high-, moderate- and low-risk countries, respectively. The mean optimal quarantine days regarding from high-risk countries to very-high-, high-, moderate- and low-risk countries were 0, 0·8, 7·2, and 14 days, respectively. The mean optimal quarantine days for from moderate-risk countries to very-high-, high-, moderate-, and low-risk countries were 0, 0·8, 2·6, and 10·4 days, respectively. The mean optimal quarantine days for from low-risk countries to very high-, high-, moderate-, and low-risk countries were 0, 0, 0, and 2 days, respectively. Correlations in logarithmic regression between the optimal quarantine days and the ratio of incidence rate between different countries performed well.Interpretation: The quarantine period for cross-region travelling could be adjusted based on the ratio of incidence rate between the two countries. We recommend a optimal quarantine period for travelers from a low-risk country entering a higher risk country in the early stage of COVID-19 massive vaccination. Funding: No external fundingDeclaration of Interest: None to declare

Co-Infection with Common Respiratory Pathogens and SARS-CoV-2 in Patients with COVID-19 Pneumonia and Laboratory Biochemistry Findings: A Retrospective Cross-Sectional Study of 78 Patients from a Single Center in China.

BACKGROUND This retrospective study aimed to investigate co-infections with common respiratory pathogens and SARS-CoV-2 and laboratory biochemistry findings in patients with COVID-19 in the Zhuzhou area of China, in order to provide a reference for the disease assessment and clinical treatment of COVID-19. MATERIAL AND METHODS The clinical data of COVID-19 patients admitted to the hospital of Zhuzhou City from January 28 to March 15, 2020, as well as laboratory test results for respiratory pathogens and biochemical indicators, were collected to conduct correlation analyses. All patients were diagnosed based on fluorescence-based PCR assay for SARS-CoV-2. RESULTS Eleven of the 78 patients (14.1%) were co-infected with other respiratory pathogens, among which Mycoplasma pneumoniae (n=5, 45.5%) and respiratory syncytial virus (n=4, 36.4%) were the most frequent. There were 8 patients co-infected with 1 other pathogen and 3 patients co-infected with 2 other pathogens. Compared with mono-infected COVID-19 patients, patients with co-infections had significantly higher levels of procalcitonin (P=0.002). CONCLUSIONS The findings showed that Mycoplasma pneumonia and respiratory syncytial virus were the most common co-infections in patients with COVID-19 pneumonia. Increased levels of PCT in patients with COVID-19 pneumonia were associated with co-infection.

A deep learning framework for high-throughput mechanism-driven phenotype compound screening (preprint)

ABSTRACT Target-based high-throughput compound screening dominates conventional one-drug-one-gene drug discovery process. However, the readout from the chemical modulation of a single protein is poorly correlated with phenotypic response of organism, leading to high failure rate in drug development. Chemical-induced gene expression profile provides an attractive solution to phenotype-based screening. However, the use of such data is currently limited by their sparseness, unreliability, and relatively low throughput. Several methods have been proposed to impute missing values for gene expression datasets. However, few existing methods can perform de novo chemical compound screening. In this study, we propose a mechanism-driven neural network-based method named DeepCE (Deep Chemical Expression) which utilizes graph convolutional neural network to learn chemical representation and multi-head attention mechanism to model chemical substructure-gene and gene-gene feature associations. In addition, we propose a novel data augmentation method which extracts useful information from unreliable experiments in L1000 dataset. The experimental results show that DeepCE achieves the superior performances not only in de novo chemical setting but also in traditional imputation setting compared to state-of-the-art baselines for the prediction of chemical-induced gene expression. We further verify the effectiveness of gene expression profiles generated from DeepCE by comparing them with gene expression profiles in L1000 dataset for downstream classification tasks including drug-target and disease predictions. To demonstrate the value of DeepCE, we apply it to patient-specific drug repurposing of COVID-19 for the first time, and generate novel lead compounds consistent with clinical evidences. Thus, DeepCE provides a potentially powerful framework for robust predictive modeling by utilizing noisy omics data as well as screening novel chemicals for the modulation of systemic response to disease.