CoVSense: Ultrasensitive Nucleocapsid Antigen Immunosensor for Rapid Clinical Detection of Wildtype and Variant SARS-CoV-2.

The widespread accessibility of commercial/clinically-viable electrochemical diagnostic systems for rapid quantification of viral proteins demands translational/preclinical investigations. Here, Covid-Sense (CoVSense) antigen testing platform; an all-in-one electrochemical nano-immunosensor for sample-to-result, self-validated, and accurate quantification of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N)-proteins in clinical examinations is developed. The platform's sensing strips benefit from a highly-sensitive, nanostructured surface, created through the incorporation of carboxyl-functionalized graphene nanosheets, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) conductive polymers, enhancing the overall conductivity of the system. The nanoengineered surface chemistry allows for compatible direct assembly of bioreceptor molecules. CoVSense offers an inexpensive (<$2 kit) and fast/digital response (<10 min), measured using a customized hand-held reader (<$25), enabling data-driven outbreak management. The sensor shows 95% clinical sensitivity and 100% specificity (Ct<25), and overall sensitivity of 91% for combined symptomatic/asymptomatic cohort with wildtype SARS-CoV-2 or B.1.1.7 variant (N = 105, nasal/throat samples). The sensor correlates the N-protein levels to viral load, detecting high Ct values of ≈35, with no sample preparation steps, while outperforming the commercial rapid antigen tests. The current translational technology fills the gap in the workflow of rapid, point-of-care, and accurate diagnosis of COVID-19.

Mathematical Models Supporting Control of COVID-19.

Mathematical models have played an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic. The aim of this review is to describe the use of COVID-19 mathematical models, their classification, and the advantages and disadvantages of different types of models. We conducted subject heading searches of PubMed and China National Knowledge Infrastructure with the terms "COVID-19," "Mathematical Statistical Model," "Model," "Modeling," "Agent-based Model," and "Ordinary Differential Equation Model" and classified and analyzed the scientific literature retrieved in the search. We categorized the models as data-driven or mechanism-driven. Data-driven models are mainly used for predicting epidemics, and have the advantage of rapid assessment of disease instances. However, their ability to determine transmission mechanisms is limited. Mechanism-driven models include ordinary differential equation (ODE) and agent-based models. ODE models are used to estimate transmissibility and evaluate impact of interventions. Although ODE models are good at determining pathogen transmission characteristics, they are less suitable for simulation of early epidemic stages and rely heavily on availability of first-hand field data. Agent-based models consider influences of individual differences, but they require large amounts of data and can take a long time to develop fully. Many COVID-19 mathematical modeling studies have been conducted, and these have been used for predicting trends, evaluating interventions, and calculating pathogen transmissibility. Successful infectious disease modeling requires comprehensive considerations of data, applications, and purposes.

Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022

Background The epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control. Methods COVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P < 0.05 indicated that the difference was statistically significant. Results Mainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7;ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%;[IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant. Conclusion With the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.

Risk assessment of public health emergencies concerned in the mainland of China, June 2021

Objective: To assess the risk of public health emergencies, both the indigenous ones and the imported ones, which might occur in the mainland of China in June 2021. Methods: An internet based expert counsel was conducted to analyze the surveillance data of public health emergencies and priority communicable diseases in China reported through different channels, and the experts in all provincial centers for disease control and prevention attended this video conference. Results: Generally speaking, it is predicted that the incidence of public health emergencies would be similar in June with May. The risk of imported cases and secondary infections of COVID-19 would continue to exist, but would be controllable. It is the high incidence season of severe fever with thrombocytopenia syndrome and most cases would be sporadic, however, the risk of cluster exits especially in previous epidemic areas. The incidences of food poisoning caused by toxic animal or plant or poisonous mushroom would increase significantly, and the incidences of food poisoning caused by microbe would be high. The earthquake-stricken areas such as Yunnan and Qinghai should further strengthen post-disaster public health responses. The potential flood-stricken areas predicted by the meteorological department need to pay attention to the risks of water-borne, food-borne and vector-borne diseases that may increase after the disaster. Conclusion: Special attention should be paid to COVID-19, and general attention should be paid to severe fever with thrombocytopenia syndrome, food poisoning and natural disaster.

Differential diagnosis of the infection caused by wild-type or CD2v-deleted ASFV strains by quantum dots-based immunochromatographic assay.

African swine fever (ASF), a highly contagious and lethal disease, poses a tremendous threat and burden to the swine industry worldwide. Lack of available vaccines or treatments leaves rapid diagnosis as the key tool to control the disease. Quantum dots (QDs) are unique fluorescent semiconductor nanoparticles, highly versatile for biological applications. In this study, we developed a quantum dots-based fluorescent immunochromatographic assay (QDs-FICA) using CD2v as the diagnosis antigen to detect ASFV antibodies. The titre of the test strip was 1 : 5·12 × 105 . In addition, the strip was highly specific to anti-ASFV serum and had no cross-reaction with CSFV, PPV, PRRSV, PCV-2, PRV and FMDV. Moreover, a comparative test of 71 clinical samples showed that the coincidence rate was 85·92% between the test strip and the commercial ELISA kit (coated with p30, p62 and p72). The QDs-FICA can be used to detect ASFV antibodies, which is meaningful for the surveillance, control and purification of ASF.

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients.

Electrochemical immuno-biosensors are one of the most promising approaches for accurate, rapid, and quantitative detection of protein biomarkers. The two-working electrode strip is employed for creating a self-supporting system, as a tool for self-validating the acquired results for added reliability. However, the realization of multiplex electrochemical point-of-care testing (ME-POCT) requires advancement in portable, rapid reading, easy-to-use, and low-cost multichannel potentiostat readers. The combined multiplex biosensor strips and multichannel readers allow for suppressing the possible complex matrix effect or ultra-sensitive detection of different protein biomarkers. Herein, a handheld binary-sensing (BiSense) bi-potentiostat was developed to perform electrochemical impedance spectroscopy (EIS)-based signal acquisition from a custom-designed dual-working-electrode immuno-biosensor. BiSense employs a commercially available microcontroller and out-of-shelf components, offering the cheapest yet accurate and reliable time-domain impedance analyzer. A specific electrical board design was developed and customized for impedance signal analysis of SARS-CoV-2 nucleocapsid (N)-protein biosensor in spiked samples and alpha variant clinical nasopharyngeal (NP) swab samples. BiSense showed limit-of-detection (LoD) down to 56 fg/mL for working electrode 1 (WE1) and 68 fg/mL for WE2 and reported with a dynamic detection range of 1 pg/mL to 10 ng/mL for detection of N-protein in spiked samples. The dual biosensing of N-protein in this work was used as a self-validation of the biosensor. The low-cost (∼USD$40) BiSense bi-potentiostat combined with the immuno-biosensors successfully detected COVID-19 infected patients in less than 10 min, with the BiSense reading period shorter than 1.5 min, demonstrating its potential for the realization of ME-POCTs for rapid and hand-held diagnosis of infections.

Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins.

Multiplex electrochemical biosensors have been used for eliminating the matrix effect in complex bodily fluids or enabling the detection of two or more bioanalytes, overall resulting in more sensitive assays and accurate diagnostics. Many electrochemical biosensors lack reliable and low-cost multiplexing to meet the requirements of point-of-care detection due to either limited functional biosensors for multi-electrode detection or incompatible readout systems. We developed a new dual electrochemical biosensing unit accompanied by a customized potentiostat to address the unmet need for point-of-care multi-electrode electrochemical biosensing. The two-working electrode system was developed using screen-printing of a carboxyl-rich nanomaterial containing ink, with both working electrodes offering active sites for recognition of bioanalytes. The low-cost bi-potentiostat system (∼$80) was developed and customized specifically to the bi-electrode design and used for rapid, repeatable, and accurate measurement of electrochemical impedance spectroscopy signals from the dual biosensor. This binary electrochemical data acquisition (Bi-ECDAQ) system accurately and selectively detected SARS-CoV-2 Nucleocapsid protein (N-protein) in both spiked samples and clinical nasopharyngeal swab samples of COVID-19 patients within 30 min. The two working electrodes offered the limit of detection of 116 fg/mL and 150 fg/mL, respectively, with the dynamic detection range of 1-10,000 pg/mL and the sensitivity range of 2744-2936 Ω mL/pg.mm2 for the detection of N-protein. The potentiostat performed comparable or better than commercial Autolab potentiostats while it is significantly lower cost. The open-source Bi-ECDAQ presents a customizable and flexible approach towards addressing the need for rapid and accurate point-of-care electrochemical biosensors for the rapid detection of various diseases.

The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China.

BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.

Feasibility of Booster Vaccination in High-Risk Populations for Controlling Coronavirus Variants - China, 2021.

INTRODUCTION: Vaccination booster shots are completely necessary for controlling breakthrough infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China. The study aims to estimate effectiveness of booster vaccines for high-risk populations (HRPs). METHODS: A vaccinated Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model was developed to simulate scenarios of effective reproduction number (R eff ) from 4 to 6. Total number of infectious and asymptomatic cases were used to evaluated vaccination effectiveness. RESULTS: Our model showed that we could not prevent outbreaks when covering 80% of HRPs with booster unless R eff =4.0 or the booster vaccine had efficacy against infectivity and susceptibility of more than 90%. The results were consistent when the outcome index was confirmed cases or asymptomatic cases. CONCLUSIONS: An ideal coronavirus disease 2019 (COVID-19) booster vaccination strategy for HRPs would be expected to reach the initial goal to control the transmission of the Delta variant in China. Accordingly, the recommendation for the COVID-19 booster vaccine should be implemented in HRPs who are already vaccinated and could prevent transmission to other groups.

Containing the Transmission of COVID-19: A Modeling Study in 160 Countries.

Background: It is much valuable to evaluate the comparative effectiveness of the coronavirus disease 2019 (COVID-19) prevention and control in the non-pharmacological intervention phase of the pandemic across countries and identify useful experiences that could be generalized worldwide. Methods: In this study, we developed a susceptible-exposure-infectious-asymptomatic-removed (SEIAR) model to fit the daily reported COVID-19 cases in 160 countries. The time-varying reproduction number (R t ) that was estimated through fitting the mathematical model was adopted to quantify the transmissibility. We defined a synthetic index (I AC ) based on the value of R t to reflect the national capability to control COVID-19. Results: The goodness-of-fit tests showed that the SEIAR model fitted the data of the 160 countries well. At the beginning of the epidemic, the values of R t of countries in the European region were generally higher than those in other regions. Among the 160 countries included in the study, all European countries had the ability to control the COVID-19 epidemic. The Western Pacific Region did best in continuous control of the epidemic, with a total of 73.76% of countries that can continuously control the COVID-19 epidemic, while only 43.63% of the countries in the European Region continuously controlled the epidemic, followed by the Region of Americas with 52.53% of countries, the Southeast Asian Region with 48% of countries, the African Region with 46.81% of countries, and the Eastern Mediterranean Region with 40.48% of countries. Conclusion: Large variations in controlling the COVID-19 epidemic existed across countries. The world could benefit from the experience of some countries that demonstrated the highest containment capabilities.

Dense GAN and multi-layer attention based lesion segmentation method for COVID-19 CT images.

As the COVID-19 virus spreads around the world, testing and screening of patients have become a headache for governments. With the accumulation of clinical diagnostic data, the imaging big data features of COVID-19 are gradually clear, and CT imaging diagnosis results become more important. To obtain clear lesion information from the CT images of patients' lungs is helpful for doctors to adopt effective medical methods, and at the same time, is helpful to screen the patients with real infection. Deep learning image segmentation is widely used in the field of medical image segmentation. However, there are some challenges in using deep learning to segment the lung lesions of COVID-19 patients. Since image segmentation requires the labeling of lesion information on a pixel by pixel basis, most professional radiologists need to screen and diagnose patients on the front line, and they do not have enough energy to label a large amount of image data. In this paper, an improved Dense GAN to expand data set is developed, and a multi-layer attention mechanism method, combined with U-Net's COVID-19 pulmonary CT image segmentation, is proposed. The experimental results showed that the segmentation method proposed in this paper improved the segmentation accuracy of COVID-19 pulmonary medical CT image by comparing with other image segmentation methods.

The collaboration between infectious disease modeling and public health decision-making based on the COVID-19

Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future.

Control Measures During the COVID-19 Outbreak Reduced the Transmission of Hand, Foot, and Mouth Disease (preprint)

Background: Control measures during the coronavirus disease 2019 (COVID-19) outbreak may have limited the spread of infectious diseases. This study aimed to analyse the impact of COVID-19 on the spread of hand, foot, and mouth disease (HFMD) in China. Methods: A mathematical model was established to fit the reported data of HFMD in six selected cities in mainland China from 2015 to 2020. The absolute difference (AD) and relative difference (RD) between the reported incidence in 2020, and simulated maximum, minimum, or median incidence of HFMD in 2015-2019 were calculated. Findings: The incidence and Reff of HFMD have decreased in six selected cities since the outbreak of COVID-19, and in the second half of 2020, the incidence and R eff of HFMD have rebounded. The results show that the total attack rate (TAR) in 2020 was lower than the maximum, minimum, and median TAR fitted in previous years in six selected cities (except Changsha city). For the maximum, median, minimum fitted TAR, the range of RD (%) is 42·20-99·20%, 36·35-98·41% 48·35-96·23% (except Changsha city) respectively. Interpretation: Based on the incidence data of six cities from 2015 to 2019, the SEIAR model demonstrated a significant effect on the incidence of HFMD. During the period of COVID-19, the incidence and R eff of HFMD decreased, the prevention and control measures taken during the period of COVID-19, such as school suspension, home quarantine, closing all kinds of leisure places, wearing masks, advocating frequent hand washing, etc., have not only effectively suppressed the spread of COVID-19 epidemic, but also have significantly contributed to the containment of HFMD transmission.Funding Statement: This study was partly supported by the Bill & Melinda Gates Foundation (INV-005834).Declaration of Interests: The authors declare no conflicts of interests.

Post-COVID-19 Epidemic: Allostatic Load among Medical and Nonmedical Workers in China.

BACKGROUND: As the fight against the COVID-19 epidemic continues, medical workers may have allostatic load. OBJECTIVE: During the reopening of society, medical and nonmedical workers were compared in terms of allostatic load. METHODS: An online study was performed; 3,590 Chinese subjects were analyzed. Socio-demographic variables, allostatic load, stress, abnormal illness behavior, global well-being, mental status, and social support were assessed. RESULTS: There was no difference in allostatic load in medical workers compared to nonmedical workers (15.8 vs. 17.8%; p = 0.22). Multivariate conditional logistic regression revealed that anxiety (OR = 1.24; 95% CI 1.18-1.31; p < 0.01), depression (OR = 1.23; 95% CI 1.17-1.29; p < 0.01), somatization (OR = 1.20; 95% CI 1.14-1.25; p < 0.01), hostility (OR = 1.24; 95% CI 1.18-1.30; p < 0.01), and abnormal illness behavior (OR = 1.49; 95% CI 1.34-1.66; p < 0.01) were positively associated with allostatic load, while objective support (OR = 0.84; 95% CI 0.78-0.89; p < 0.01), subjective support (OR = 0.84; 95% CI 0.80-0.88; p < 0.01), utilization of support (OR = 0.80; 95% CI 0.72-0.88; p < 0.01), social support (OR = 0.90; 95% CI 0.87-0.93; p < 0.01), and global well-being (OR = 0.30; 95% CI 0.22-0.41; p < 0.01) were negatively associated. CONCLUSIONS: In the post-COVID-19 epidemic time, medical and nonmedical workers had similar allostatic load. Psychological distress and abnormal illness behavior were risk factors for it, while social support could relieve it.

Pediatric massage therapy for restoring pediatric lung function from COVID-19: A protocol for systematic review and meta-analysis.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has caused an international outbreak of a respiratory illness and grown to be a global public health emergency since patients were first detected in Wuhan, China. Given the rapidly growing pandemic and the overwhelmed medical system, there is an urgent need of alternative medicine to help children relieve symptoms during self-quarantine, and possibly to help increase their chances of survival and recovery from COVID-19. By using various manual techniques at specified locations on the surface of the body, pediatric massage manipulation can unblock meridians, promote the circulation of qi and blood and strengthen resistance to pathogens. METHODS: We will search the following electronic databases: Wanfang and Pubmed Database, CNKI, CENTRAL, CINAHL, EMBASE and MEDLINE. Each database will be searched from inception to June 2020. The entire process will include study selection, data extraction, risk of bias assessment and meta-analyses. RESULTS: This systematic review will evaluate the existing evidence of pediatric massage therapy for restoring pediatric lung function from COVID-19. The outcomes will include the improvement of pulmonary function and adverse effect. CONCLUSION: This proposed systematic review will evaluate the existing evidence and explore the potential role of pediatric massage therapy on the effectiveness and safety in pulmonary function of COVID-19 convalescent children. PROSPERO REGISTRATION NUMBER: CRD42020193396.