Electrochemical Detection of a Few Copies of Unamplified SARS-CoV-2 Nucleic Acids by a Self-Actuated Molecular System.

The existing electrochemical biosensors lack controllable and intelligent merit to modulate the sensing process upon external stimulus, leading to challenges in analyzing a few copies of biomarkers in unamplified samples. Here, we present a self-actuated molecular-electrochemical system that consists of a tentacle and a trunk modification on a graphene microelectrode. The tentacle that contains a probe and an electrochemical label keeps an upright orientation, which increases recognition efficiency while decreasing the pseudosignal. Once the nucleic acids are recognized, the tentacles nearby along with the labels are spontaneously actuated downward, generating electrochemical responses under square wave voltammetry. Thus, it detects unamplified SARS-CoV-2 RNAs within 1 min down to 4 copies in 80 µL, 2-6 orders of magnitude lower than those of other electrochemical assays. Double-blind testing and 10-in-1 pooled testing of nasopharyngeal samples yield high overall agreement with reverse transcription-polymerase chain reaction results. We fabricate a portable prototype based on this system, showing great potential for future applications.

Ultraprecise Antigen 10-in-1 Pool Testing by Multiantibodies Transistor Assay.

Effective screening of infectious diseases requires a fast, cheap, and population-scale testing. Antigen pool testing can increase the test rate and shorten the screening time, thus being a valuable approach for epidemic prevention and control. However, the overall percent agreement (OPA) with polymerase chain reaction (PCR) is one-half to three-quarters, hampering it from being a comprehensive method, especially pool testing, beyond the gold-standard PCR. Here, a multiantibodies transistor assay is developed for sensitive and highly precise antigen pool testing. The multiantibodies capture SARS-CoV-2 spike S1 proteins with different configurations, resulting in an antigen-binding affinity down to 0.34 fM. The limit of detection reaches 3.5 × 10-17 g mL-1SARS-CoV-2 spike S1 protein in artificial saliva, 4-5 orders of magnitude lower than existing transistor sensors. The testing of 60 nasopharyngeal swabs exhibits ∼100% OPA with PCR within an average diagnoses time of 38.9 s. Owing to its highly precise feature, a portable integrated platform is fabricated, which achieves 10-in-1 pooled screening for high testing throughput. This work solves the long-standing problem of antigen pool testing, enabling it to be a valuable tool in precise diagnoses and population-wide screening of COVID-19 or other epidemics in the future.

Factors influencing nurses' behavioral intention toward caring for COVID-19 patients on mechanical ventilation: A cross-sectional study.

OBJECTIVES: To investigate nurses' behavioral intention toward caring for COVID-19 patients on mechanical ventilation, as well as the factors affecting their intention. BACKGROUND: COVID-19 patients undergoing mechanical ventilation have many care needs and pose more challenges for nurses, which might adversely affect nurses' intention toward caring behavior. METHODS: A cross-sectional study was conducted by using simple random sampling to recruit 598 nurses from five tertiary hospitals in Sichuan Province, China. The participants responded to an online questionnaire that included questions on demographic characteristics; the Attitude, Subjective Norms, and Behavioral Intention of Nurses toward Mechanically Ventilated Patients (ASIMP) questionnaire; the Nursing Professional Identity Scale (NPIS); and the Compassion Fatigue-Short Scale (CF-Short Scale). ANOVA, Spearman correlation analysis, and multiple linear regression were performed to analyze the data. RESULTS: The mean total behavioral intention score was 179.46 (± 14.83) out of a total score of 189.00, which represented a high level of intention toward caring for patients on mechanical ventilation. Multiple linear regression revealed that subjective norms (ß = 0.390, P<0.001), perceived behavioral control (ß = 0.149, P<0.001), professional identity (ß = 0.101, P = 0.009), and compassion fatigue (ß = 0.088 P = 0.024) were significant predictors of nurses' behavioral intention. CONCLUSIONS: Most nurses have a positive behavioral intention to care for COVID-19 patients undergoing mechanical ventilation. The findings in this study provide some insight for developing effective and tailored strategies to promote nurses' behavioral intention toward caring for ventilated patients under the pandemic situation.

Ultrasensitive Detection of SARS-CoV-2 Antibody by Graphene Field-Effect Transistors.

The fast spread of SARS-CoV-2 has severely threatened the public health. Establishing a sensitive method for SARS-CoV-2 detection is of great significance to contain the worldwide pandemic. Here, we develop a graphene field-effect transistor (g-FET) biosensor and realize ultrasensitive SARS-CoV-2 antibody detection with a limit of detection (LoD) down to 10-18 M (equivalent to 10-16 g mL-1) level. The g-FETs are modified with spike S1 proteins, and the SARS-CoV-2 antibody biorecognition events occur in the vicinity of the graphene surface, yielding an LoD of ∼150 antibodies in 100 µL full serum, which is the lowest LoD value of antibody detection. The diagnoses time is down to 2 min for detecting clinical serum samples. As such, the g-FETs leverage rapid and precise SARS-CoV-2 screening and also hold great promise in prevention and control of other epidemic outbreaks in the future.

A Bayes Decision Rule to Assist Policymakers during a Pandemic.

A new decision rule based on net benefit per capita is proposed and exemplified with the aim of assisting policymakers in deciding whether to lockdown or reopen an economy-fully or partially-amidst a pandemic. Bayesian econometric models using Markov chain Monte Carlo algorithms are used to quantify this rule, which is illustrated via several sensitivity analyses. While we use COVID-19 data from the United States to demonstrate the ideas, our approach is invariant to the choice of pandemic and/or country. The actions suggested by our decision rule are consistent with the closing and reopening of the economies made by policymakers in Florida, Texas, and New York; these states were selected to exemplify the methodology since they capture the broad spectrum of COVID-19 outcomes in the U.S.

Covid-19’s adverse effects on a stock market index

We perform a panel data analysis of 14 daily stock market indices during 01/21/2020–06/30/2020 to document a stock market index’s negative responsiveness to Covid-19’s spread variations. We find that a stock market index’s elasticity estimate is −0.028 (p-value <0.01) for local cumulative confirmed cases. As a stock market index tends to move with Covid-19’s local and non-local spreads, international efforts of containment are expected to pare stock market losses.