Accurate quantification of DNA using on-site PCR (osPCR) by characterizing DNA amplification at single-molecule resolution.

Despite the need in various applications, accurate quantification of nucleic acids still remains a challenge. The widely-used qPCR has reduced accuracy at ultralow template concentration and is susceptible to nonspecific amplifications. The more recently developed dPCR is costly and cannot handle high-concentration samples. We combine the strengths of qPCR and dPCR by performing PCR in silicon-based microfluidic chips and demonstrate high quantification accuracy in a large concentration range. Importantly, at low template concentration, we observe on-site PCR (osPCR), where only certain sites of the channel show amplification. The sites have almost identical ct values, showing osPCR is a quasi-single molecule phenomenon. Using osPCR, we can measure both the ct values and the absolute concentration of templates in the same reaction. Additionally, osPCR enables identification of each template molecule, allowing removal of nonspecific amplification during quantification and greatly improving quantification accuracy. We develop sectioning algorithm that improves the signal amplitude and demonstrate improved detection of COVID in patient samples.

COVID-19 vaccination status, side effects, and perceptions among breast cancer survivors: a cross-sectional study in China.

Introduction: Breast cancer is the most prevalent malignancy in patients with coronavirus disease 2019 (COVID-19). However, vaccination data of this population are limited. Methods: A cross-sectional study of COVID-19 vaccination was conducted in China. Multivariate logistic regression models were used to assess factors associated with COVID-19 vaccination status. Results: Of 2,904 participants, 50.2% were vaccinated with acceptable side effects. Most of the participants received inactivated virus vaccines. The most common reason for vaccination was "fear of infection" (56.2%) and "workplace/government requirement" (33.1%). While the most common reason for nonvaccination was "worry that vaccines cause breast cancer progression or interfere with treatment" (72.9%) and "have concerns about side effects or safety" (39.6%). Patients who were employed (odds ratio, OR = 1.783, p = 0.015), had stage I disease at diagnosis (OR = 2.008, p = 0.019), thought vaccines could provide protection (OR = 1.774, p = 0.007), thought COVID-19 vaccines were safe, very safe, not safe, and very unsafe (OR = 2.074, p < 0.001; OR = 4.251, p < 0.001; OR = 2.075, p = 0.011; OR = 5.609, p = 0.003, respectively) were more likely to receive vaccination. Patients who were 1-3 years, 3-5 years, and more than 5 years after surgery (OR = 0.277, p < 0.001; OR = 0.277, p < 0.001, OR = 0.282, p < 0.001, respectively), had a history of food or drug allergies (OR = 0.579, p = 0.001), had recently undergone endocrine therapy (OR = 0.531, p < 0.001) were less likely to receive vaccination. Conclusion: COVID-19 vaccination gap exists in breast cancer survivors, which could be filled by raising awareness and increasing confidence in vaccine safety during cancer treatment, particularly for the unemployed individuals.

Assessment of Cardiac Adverse Events following COVID-19 Vaccination by Speckle Tracking Echocardiography (preprint)

Background: Cardiac discomfort has been reported periodically in COVID-19 vaccinated individuals. Thus, this study aimed to evaluate the role of myocardial strains in the early assessment of the clinical presentations after COVID-19 vaccination. Methods and Results: Totally, 121 subjects who received at least one dose of vaccine within 6 weeks underwent laboratory tests and echocardiogram. Two-dimensional speckle tracking echocardiography (2D-STE) was implemented to analyze changes in the left ventricular myocardium. After vaccination, 66 individuals (55.4 ± 17.4 years) developed cardiac discomfort, such as chest tightness, palpitations, dyspnea, and chest pain. All had normal serum levels of creatine phosphokinase, creatine kinase myocardial band, troponin, N-terminal pro b-type natriuretic peptide, platelets, and D-dimer. Left ventricular ejection fraction in the symptomatic group (71.41% ± 7.12%) and the control group (72.18% ± 5.11%) (p = 0.492) were normal. Use of 2D-STE presented global longitudinal strain (GLS) and global circumferential strain (GCS) were reduced in symptomatic group (17.86% ± 3.22% and 18.37% ± 5.22%) compared to control group (19.54% ± 2.18% and 20.73% ± 4.09%) (p = 0.001 and p = 0.028). Conclusion: COVID-19 vaccine-related cardiac adverse effects can be assessed early by 2D-STE. The prognostic implications of GLS and GCS enable evaluation of subtle changes in myocardial function after vaccination.

Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA Biochips

The micro-electrode-dot-array (MEDA) architecture provides precise droplet control and real-time sensing in digital microfluidic biochips. Previous work has shown that trapped charge under microelectrodes (MCs) leads to droplets being stuck and failures in fluidic operations. A recent approach utilizes real-time sensing of MC health status, and attempts to avoid degraded electrodes during droplet routing. However, the problem with this solution is that the computational complexity is unacceptable for MEDA biochips of realistic size. Consequently, in this work, we introduce a deep reinforcement learning (DRL)-based approach to bypass degraded electrodes and enhance the reliability of routing. The DRL model utilizes the information of health sensing in real time to proactively reduce the likelihood of charge trapping and avoid using degraded MCs. Simulation results show that our approach provides effective routing strategies for COVID-19 testing protocols. We also validate our DRL-based approach using fabricated prototype biochips. Experimental results show that the developed DRL model completed the routing tasks using a fewer number of clock cycles and shorter total execution time, compared with a baseline routing method. Moreover, our DRL-based approach provides reliable routing strategies even in the presence of degraded electrodes. Our experimental results show that the proposed DRL-based routing is robust to occurrences of electrode faults, as well as increases the lifetime and usability of microfluidic biochips compared to existing strategies.

Ultrafast Nucleic Acid Detection Equipment with Silicon-Based Microfluidic Chip.

Recently, infectious diseases, such as COVID-19, monkeypox, and Ebola, are plaguing human beings. Rapid and accurate diagnosis methods are required to preclude the spread of diseases. In this paper, an ultrafast polymerase chain reaction (PCR) equipment is designed to detect virus. The equipment consists of a silicon-based PCR chip, a thermocycling module, an optical detection module, and a control module. Silicon-based chip, with its thermal and fluid design, is used to improve detection efficiency. A thermoelectric cooler (TEC), together with a computer-controlled proportional-integral-derivative (PID) controller, is applied to accelerate the thermal cycle. A maximum of four samples can be tested simultaneously on the chip. Two kinds of fluorescent molecules can be detected by optical detection module. The equipment can detect viruses with 40 PCR amplification cycles in 5 min. The equipment is portable, easily operated, and low equipment cost, which shows great potential in epidemic prevention.

A Point-of-Care Biosensor for Rapid Detection and Differentiation of COVID-19 Virus (SARS-CoV-2) and Influenza Virus Using Subwavelength Grating Micro-ring Resonator (preprint)

In the context of continued spread of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 and the emergence of new variants, the demand for rapid, accurate, and frequent detection is increasing. Besides, the new predominant strain, Omicron variant, manifests more similar clinical features to those of other common respiratory infections. The concurrent detection of multiple potential pathogens helps distinguish SARS-CoV-2 infection from other diseases with overlapping symptoms, which is significant for patients to receive tailored treatment and containing the outbreak. Here, we report a lab-on-a-chip biosensing platform for SARS-CoV-2 detection based on subwavelength grating micro-ring resonator. The sensing surface is functionalized by specific antibody against SARS-CoV-2 spike protein, which could produce redshifts of resonant peaks by antigen-antibody combination, thus achieving quantitative detection. Additionally, the sensor chip is integrated with a microfluidic chip with an anti-backflow Y-shaped structure that enables the concurrent detection of two analytes. In this study, we realized the detection and differentiation of COVID-19 and influenza A H1N1. Experimental results show that the limit of detection of our device reaches 100 fg/mL (1.31 fM) within 15 min detecting time, and cross-reactivity tests manifest the specificity of the optical diagnostic assay. Further, the integrated packaging and streamlined workflow facilitate its use for clinical applications. Thus, the biosensing platform offers a promising solution to achieve ultrasensitive, selective, multiplexed, and quantitative point-of-care detection of COVID-19.

Case report: Vaccine-induced immune thrombotic thrombocytopenia complicated by acute cerebral venous thrombosis and hemorrhage after AstraZeneca vaccines followed by Moderna COVID-19 vaccine booster and surgery

Vaccine-induced thrombotic thrombocytopenia (VITT) is a well-known complication of adenoviral vector COVID-19 vaccines including ChAdOx1 nCoV-19 (AstraZeneca) and Ad26. COV2.S (Janssen, Johnson & Johnson). To date, only a few cases of mRNA COVID-19 vaccine such as mRNA-1273 (Moderna) or BNT162b2 (Pfizer-BioNTech)-induced VITT have been reported. We report a case of VITT with acute cerebral venous thrombosis and hemorrhage after a booster of mRNA-1273 (Moderna) vaccine in a patient previously vaccinated with two doses of the AstraZeneca vaccine. A 42-year-old woman presented with sudden onset of weakness of the right upper limb with focal seizure. She had received two doses of AstraZeneca vaccines and a booster with Moderna vaccine 32 days before presentation. She had also undergone a laparoscopic myomectomy 12 days previously. Laboratory examinations revealed anemia (9.5 g/dl), thrombocytopenia (31 × 103/μl), and markedly elevated d-dimer (>20.0 mg/L;reference value < 0.5 mg/L). The initial brain computed tomography (CT) was normal, but a repeated scan 10 h later revealed hemorrhage at the left cerebrum. Before the results of the blood smear were received, on suspicion of thrombotic microangiopathy with thrombocytopenia and thrombosis, plasmapheresis and pulse steroid therapy were initiated, followed by intravenous immunoglobulin (1 g/kg/day for two consecutive days) due to refractory thrombocytopenia. VITT was confirmed by positive anti-PF4 antibody and both heparin-induced and PF4-induced platelet activation testing. Clinicians should be aware that mRNA-1273 Moderna, an mRNA-based vaccine, may be associated with VITT with catastrophic complications. Additionally, prior exposure to the AstraZeneca vaccine and surgical procedure could also have precipitated or aggravated autoimmune heparin-induced thrombocytopenia/VITT-like presentation.

Determinants of coronavirus disease 2019 infection by artificial intelligence technology: A study of 28 countries.

OBJECTIVES: The coronavirus disease 2019 pandemic has affected countries around the world since 2020, and an increasing number of people are being infected. The purpose of this research was to use big data and artificial intelligence technology to find key factors associated with the coronavirus disease 2019 infection. The results can be used as a reference for disease prevention in practice. METHODS: This study obtained data from the "Imperial College London YouGov Covid-19 Behaviour Tracker Open Data Hub", covering a total of 291,780 questionnaire results from 28 countries (April 1~August 31, 2020). Data included basic characteristics, lifestyle habits, disease history, and symptoms of each subject. Four types of machine learning classification models were used, including logistic regression, random forest, support vector machine, and artificial neural network, to build prediction modules. The performance of each module is presented as the area under the receiver operating characteristics curve. Then, this study further processed important factors selected by each module to obtain an overall ranking of determinants. RESULTS: This study found that the area under the receiver operating characteristics curve of the prediction modules established by the four machine learning methods were all >0.95, and the RF had the highest performance (area under the receiver operating characteristics curve is 0.988). Top ten factors associated with the coronavirus disease 2019 infection were identified in order of importance: whether the family had been tested, having no symptoms, loss of smell, loss of taste, a history of epilepsy, acquired immune deficiency syndrome, cystic fibrosis, sleeping alone, country, and the number of times leaving home in a day. CONCLUSIONS: This study used big data from 28 countries and artificial intelligence methods to determine the predictors of the coronavirus disease 2019 infection. The findings provide important insights for the coronavirus disease 2019 infection prevention strategies.

The impact of COVID-19 epidemic on emergency department visits of older patients in Taiwan (preprint)

Background The number of emergency department (ED) visits has significantly declined since the COVID-19 pandemic. In Taiwan, an aging society, it is unknown whether older adults are accessing emergency care during the COVID-19 epidemic. Therefore, this study aimed to investigate the impact of COVID-19 on the ED visits and triage, admission, and intensive care unit (ICU) hospitalization of the geriatric population in a COVID-19-dedicated medical center throughout various periods of the epidemic.Methods A retrospective chart review of ED medical records from April 9 to August 31, 2021 were conducted, and demographic information was obtained from the hospital’s computer database. The period was divided into pre-, early-, peak-, late-, and post-epidemic stages. For statistical analysis, one-way analysis of variance followed by multiple comparison tests (Scheffe’s test) were used.Results A statistically significant decrease in the total number of patients attending the ED was noted during the peak-, late-, and post-epidemic stages. In the post- and pre-epidemic stage, the number of older patients visiting ED was consistent, indicating their earlier visit to ED than the general population. Regarding ICU admission, the total number of patients in late-epidemic stage was smaller than that in pre-epidemic stage; however, the number of older patients was steady, regardless of hospital or ICU admission.Conclusions During the peak of COVID-19 outbreak, the number of ED visits was significantly affected. However, it is noteworthy that as the epidemic was gradually controlled, the older patients resumed their ED visits earlier that the general population as indicated by the surge in their number. Additionally, in the patient group of triage 1 or 2, which represents a true emergency, the number did not show a drastic change.

Pilot Study: Nutritional and Preclinical Safety Investigation of Fermented Hispidin-Enriched Sanghuangporus sanghuang Mycelia: A Promising Functional Food Material to Improve Sleep

Sleep disturbances have been the hallmark of the recent coronavirus disease 2019 pandemic. Studies have shown that once sleep is disrupted, it can lead to psychological and physical health issues which can, in turn, disrupt circadian rhythm and induce further sleep disruption. As consumers are trying to establish healthy routines, nutritional and preclinical safety investigation of fermented hispidin-enriched Sanghuangporus sanghuang mycelia (GKSS) as a novel food material for spontaneous sleep in Sprague-Dawley rats is conducted for the first time. Results showed that the nutritional analysis of GKSS including moisture, ash, crude lipid, crude protein, carbohydrate, and energy were found to be 2.4 ± 0.3%, 8.0 ± 2.5%, 1.7 ± 0.3%, 22.9 ± 1.2%, 65.1 ± 3.1%, and 367.1 ± 10.2 kcal/100 g respectively. In the 28-day repeated-dose oral toxicity study, only Sprague-Dawley male rats receiving 5 g/kg showed a slight decrease in feed consumption at week 3, but no associated clinical signs of toxicity or significant weight loss were observed. Although a significant reduction of the platelet count was found in mid- and high-dose GKSS treated male groups, such changes were noted to be within the normal range and were not correlated with relative spleen weight changes. Hence, the no observed adverse effect level (NOAEL) of GKSS was identified to be higher than 5 g/kg in rats. After the safety of GKSS is confirmed, the sleep-promoting effect of GKSS ethanolic extract enriched with hispidin was further assessed. Despite 75 mg/kg of GKSS ethanolic extract does not affect wakefulness, rapid eye movement (REM) sleep and non-REM (NREM) sleep, GKSS ethanolic extract at 150 mg/kg significantly decreased wakefulness and enhanced NREM and REM sleep. Interestingly, such effects seem to be mediated through anti-inflammatory activities via NF-E2-related factor-2 (Nrf2) signaling pathway. Taken together, these findings provide the preliminary evidence to studies support the claims suggesting that GKSS contained useful phytochemical hispidin could be considered as and is safe to use as a functional food agent or nutraceutical for relieving sleep problems mediated by Nrf2 pathway, which the results are useful for future clinical pilot study.

The correlation between professional quality of life and mental health outcomes among hospital personnel during the Covid-19 pandemic in Taiwan

Purpose This study investigated the association between professional quality of life, working context, and mental health outcomes among hospital personnel in Taiwan during the worldwide upsurge in COVID-19 cases. Patients and Methods We recruited 503 hospital personnel to whom we administered online questionnaires containing items from the Professional Quality of Life (ProQoL) scale, which covers compassion satisfaction (CS), burnout (BO) and compassion fatigue (CF), the Depression, Anxiety and Stress Scale (DASS-21) and questions on work-related variables. Data were collected from 13 July to 19 August 2020. Results The participants generally reported moderate CS and BO and low CF. Overall prevalence of mild-to-extremely-severe stress, anxiety and depression was 24.5%, 39.6% and 31.2%, respectively. Multiple logistic regression revealed that moderate-to-high BO and CF correlated with increased risks of mild-to-extremely-severe stress (OR = 4.17 and 2.23, respectively), anxiety (OR = 4.86 and 2.81, respectively) and depression (OR = 5.83 and 3.01, respectively), while moderate-to-high CS correlated with reduced risks of stress (OR = 0.53) and depression (OR = 0.45) only. There were CS and BO differences in groups categorized by marital status and profession. Anxiety increased linearly by seniority <10, 10–19 and ≥20 years (p for trend <0.05). Conclusion In conclusion, the subscales of ProQOL, BO and CF appeared to be associated with increased risks of stress, anxiety and depression among hospital personnel during the COVID-19 epidemic. A long-term contingency program may be needed to adjust work context variables and support emotional well-being of these workers.

The occurrence of and risk factors for developing acute critical illness during quarantine as a response to the COVID-19 pandemic.

BACKGROUND/PURPOSE: Early detection and timely quarantine measures are necessary to control disease spread and prevent nosocomial outbreaks of Coronavirus disease 2019 (COVID-19). In this study, we aimed to investigate the impact of a quarantine strategy on patient safety and quality of care. METHODS: This retrospective cohort study enrolled patients admitted to the quarantine ward in a tertiary hospital in southern Taiwan. The incidence and causes of acute critical illness, including clinical deterioration and unexpected complications during the quarantine period, were reviewed. Further investigation was performed to identify risk factors for acute critical illness during quarantine. RESULTS: Of 320 patients admitted to the quarantine ward, more than two-thirds were elderly, and 37.8% were bedridden. During the quarantine period, 68 (21.2%) developed acute critical illness, which more commonly occurred among patients older than 80 years and with a bedridden status, nasogastric tube feeding, or dyspnea symptoms. Bedridden status was an independent predictor of acute critical illness. Through optimization of sampling for COVID-19 and laboratory schedules, both the duration of quarantine and the proportion of acute critical illness among bedridden patients during quarantine exhibited a decreasing trend. There was no COVID-19 nosocomial transmission during the study period. CONCLUSION: The quarantine ward is a key measure to prevent nosocomial transmission of COVID-19 but may carry a potential negative impact on patient care and safety. For patients with multiple comorbidities and a bedridden status, healthcare workers should remain alert to rapid deterioration and unexpected adverse events during quarantine.

Safety, tolerability, and immunogenicity of an aerosolised adenovirus type-5 vector-based COVID-19 vaccine (Ad5-nCoV) in adults: preliminary report of an open-label and randomised phase 1 clinical trial.

BACKGROUND: SARS-CoV-2 has caused millions of deaths, and, since Aug 11, 2020, 20 intramuscular COVID-19 vaccines have been approved for use. We aimed to evaluate the safety and immunogenicity of an aerosolised adenovirus type-5 vector-based COVID-19 vaccine (Ad5-nCoV) in adults without COVID-19 from China. METHOD: This was a randomised, single-centre, open-label, phase 1 trial done in Zhongnan Hospital (Wuhan, China), to evaluate the safety and immunogenicity of the Ad5-nCoV vaccine by aerosol inhalation in adults (≥18 years) seronegative for SARS-CoV-2. Breastfeeding or pregnant women and people with major chronic illnesses or history of allergies were excluded. Participants were enrolled and randomly assigned (1:1:1:1:1) into five groups to be vaccinated via intramuscular injection, aerosol inhalation, or both. Randomisation was stratified by sex and age (18-55 years or ≥56 years) using computer-generated randomisation sequences (block sizes of five). Only laboratory staff were masked to group assignment. The participants in the two aerosol groups received an initial high dose (2 × 1010 viral particles; HDmu group) or low dose (1 × 1010 viral particles; LDmu group) of Ad5-nCoV vaccine on day 0, followed by a booster on day 28. The mixed vaccination group received an initial intramuscular (5 × 1010 viral particles) vaccine on day 0, followed by an aerosolised booster (2 × 1010 viral particles) vaccine on day 28 (MIX group). The intramuscular groups received one dose (5 × 1010 viral particles; 1Dim group) or two doses (10 × 1010 viral particles; 2Dim group) of Ad5-nCoV on day 0. The primary safety outcome was adverse events 7 days after each vaccination, and the primary immunogenicity outcome was anti-SARS-CoV-2 spike receptor IgG antibody and SARS-CoV-2 neutralising antibody geometric mean titres at day 28 after last vaccination. This trial is registered with ClinicalTrials.gov, number NCT04552366. FINDINGS: Between Sept 28, 2020, and Sept 30, 2020, 230 individuals were screened for inclusion, of whom 130 (56%) participants were enrolled into the trial and randomly assigned into one of the five groups (26 participants per group). Within 7 days after vaccination, adverse events occurred in 18 (69%) in the HDmu group, 19 (73%) in the LDmu group, 19 (73%) in the MIX group, 19 (73%) in the 1Dim group, and 15 (58%) in the 2Dim group. The most common adverse events reported 7 days after the first or booster vaccine were fever (62 [48%] of 130 participants), fatigue (40 [31%] participants), and headache (46 [35%] participants). More adverse events were reported in participants who received intramuscular vaccination, including participants in the MIX group (49 [63%] of 78 participants), than those who received aerosol vaccine (13 [25%] of 52 participants) after the first vaccine vaccination. No serious adverse events were noted within 56 days after the first vaccine. At days 28 after last vaccination, geometric mean titres of SARS-CoV-2 neutralising antibody was 107 (95% CI 47-245) in the HDmu group, 105 (47-232) in the LDmu group, 396 (207-758) in the MIX group, 95 (61-147) in the 1Dim group, and 180 (113-288) in the 2Dim group. The geometric mean concentrations of receptor binding domain-binding IgG was 261 EU/mL (95% CI 121-563) in the HDmu group, 289 EU/mL (138-606) in the LDmu group, 2013 EU/mL (1180-3435) in the MIX group, 915 EU/mL (588-1423) in the 1Dim group, and 1190 EU/mL (776-1824) in the 2Dim group. INTERPRETATION: Aerosolised Ad5-nCoV is well tolerated, and two doses of aerosolised Ad5-nCoV elicited neutralising antibody responses, similar to one dose of intramuscular injection. An aerosolised booster vaccination at 28 days after first intramuscular injection induced strong IgG and neutralising antibody responses. The efficacy and cost-effectiveness of aerosol vaccination should be evaluated in future studies. FUNDING: National Key Research and Development Programme of China and National Science and Technology Major Project. TRANSLATION: For the Chinese translation of the Summary see Supplementary Material.

IMAL-Net: Interpretable multi-task attention learning network for invasive lung adenocarcinoma screening in CT images.

PURPOSE: Feature maps created from deep convolutional neural networks (DCNNs) have been widely used for visual explanation of DCNN-based classification tasks. However, many clinical applications such as benign-malignant classification of lung nodules normally require quantitative and objective interpretability, rather than just visualization. In this paper, we propose a novel interpretable multi-task attention learning network named IMAL-Net for early invasive adenocarcinoma screening in chest computed tomography images, which takes advantage of segmentation prior to assist interpretable classification. METHODS: Two sub-ResNets are firstly integrated together via a prior-attention mechanism for simultaneous nodule segmentation and invasiveness classification. Then, numerous radiomic features from the segmentation results are concatenated with high-level semantic features from the classification subnetwork by FC layers to achieve superior performance. Meanwhile, an end-to-end feature selection mechanism (named FSM) is designed to quantify crucial radiomic features greatly affecting the prediction of each sample, and thus it can provide clinically applicable interpretability to the prediction result. RESULTS: Nodule samples from a total of 1626 patients were collected from two grade-A hospitals for large-scale verification. Five-fold cross validation demonstrated that the proposed IMAL-Net can achieve an AUC score of 93.8% ± 1.1% and a recall score of 93.8% ± 2.8% for identification of invasive lung adenocarcinoma. CONCLUSIONS: It can be concluded that fusing semantic features and radiomic features can achieve obvious improvements in the invasiveness classification task. Moreover, by learning more fine-grained semantic features and highlighting the most important radiomics features, the proposed attention and FSM mechanisms not only can further improve the performance but also can be used for both visual explanations and objective analysis of the classification results.

Favipiravir Versus Arbidol for Clinical Recovery Rate in Moderate and Severe Adult COVID-19 Patients: A Prospective, Multicenter, Open-Label, Randomized Controlled Clinical Trial.

Background: In addition to supportive therapy, antiviral therapy is an effective treatment for coronavirus disease 2019 (COVID-19). Objective: To compare the efficacy and safety of favipiravir and umifenovir (Arbidol) to treat COVID-19 patients. Methods: We conducted a prospective, randomized, controlled, open-label multicenter trial involving adult patients with COVID-19. Enrolled patients with initial symptoms within 12 days were randomly assigned in a 1:1 ratio to receive conventional therapy plus Arbidol (200 mg*3/day) or favipiravir (1600 mg*2/first day followed by 600 mg*2/day) for 7 days. The primary outcome was the clinical recovery rate at day 7 of drug administration (relief for pyrexia and cough, respiratory frequency ≤24 times/min; oxygen saturation ≥98%). Latency to relief for pyrexia and cough and the rate of auxiliary oxygen therapy (AOT) or noninvasive mechanical ventilation (NMV)/mechanical ventilation (MV) were the secondary outcomes. Safety data were collected for 17 days. Results: A total of 240 enrolled COVID-19 patients underwent randomization; 120 patients were assigned to receive favipiravir (116 assessed), and 120 patients were assigned to receive Arbidol (120 assessed). The clinical recovery rate at day 7 of drug administration did not significantly differ between the favipiravir group (71/116) and Arbidol group (62/120) (p = 0.1396, difference in recovery rate: 0.0954; 95% CI: -0.0305∼0.2213). Favipiravir contributed to relief for both pyrexia (difference: 1.70 days, p < 0.0001) and cough (difference: 1.75 days, p < 0.0001). No difference was observed in the AOT or NMV/MV rate (both p > 0.05). The most frequently observed favipiravir-associated adverse event was increased serum uric acid (16/116, OR: 5.52, p = 0.0014). Conclusion: Among patients with COVID-19, favipiravir, compared to Arbidol, did not significantly improve the clinical recovery rate at day 7. Favipiravir significantly improved the latency to relieve pyrexia and cough. Adverse effects caused by favipiravir are mild and manageable.

iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients.

Most prior studies focused on developing models for the severity or mortality prediction of COVID-19 patients. However, effective models for recovery-time prediction are still lacking. Here, we present a deep learning solution named iCOVID that can successfully predict the recovery-time of COVID-19 patients based on predefined treatment schemes and heterogeneous multimodal patient information collected within 48 hours after admission. Meanwhile, an interpretable mechanism termed FSR is integrated into iCOVID to reveal the features greatly affecting the prediction of each patient. Data from a total of 3008 patients were collected from three hospitals in Wuhan, China, for large-scale verification. The experiments demonstrate that iCOVID can achieve a time-dependent concordance index of 74.9% (95% CI: 73.6-76.3%) and an average day error of 4.4 days (95% CI: 4.2-4.6 days). Our study reveals that treatment schemes, age, symptoms, comorbidities, and biomarkers are highly related to recovery-time predictions.

Public Compliance With Social Distancing Measures and SARS-CoV-2 Spread : A Quantitative Analysis of 5 States.

OBJECTIVE: We quantified the association between public compliance with social distancing measures and the spread of SARS-CoV-2 during the first wave of the epidemic (March-May 2020) in 5 states that accounted for half of the total number of COVID-19 cases in the United States. METHODS: We used data on mobility and number of COVID-19 cases to longitudinally estimate associations between public compliance, as measured by human mobility, and the daily reproduction number and daily growth rate during the first wave of the COVID-19 epidemic in California, Illinois, Massachusetts, New Jersey, and New York. RESULTS: The 5 states mandated social distancing directives during March 19-24, 2020, and public compliance with mandates started to decrease in mid-April 2020. As of May 31, 2020, the daily reproduction number decreased from 2.41-5.21 to 0.72-1.19, and the daily growth rate decreased from 0.22-0.77 to -0.04 to 0.05 in the 5 states. The level of public compliance, as measured by the social distancing index (SDI) and daily encounter-density change, was high at the early stage of implementation but decreased in the 5 states. The SDI was negatively associated with the daily reproduction number (regression coefficients range, -0.04 to -0.01) and the daily growth rate (from -0.009 to -0.01). The daily encounter-density change was positively associated with the daily reproduction number (regression coefficients range, 0.24 to 1.02) and the daily growth rate (from 0.05 to 0.26). CONCLUSIONS: Social distancing is an effective strategy to reduce the incidence of COVID-19 and illustrates the role of public compliance with social distancing measures to achieve public health benefits.