Quantification of early nonpharmaceutical interventions 1 aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah) (preprint)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. To investigate the causes of this difference, we used a compartmental model accounting for distinct periods of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission) to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

Students' Perceptions of Online Learning in the Post-COVID Era: A Focused Case from the Universities of Applied Sciences in China

Currently, while most universities around the world have returned to offline teaching, most universities in China are still using online teaching. In the current educational context, Chinese universities switch between online and offline teaching modes at any time depending on the epidemic situation in their city. This paper discusses students' perceptions of online learning in the post-COVID era in China. Based on the data collected from student questionnaires, the teaching and learning situation in the post-COVID era and student preferences for online learning are discussed. In addition to this, the statistics program JMP was used to perform the data analysis. The correlations among study characteristics, socio-economic factors, organisational and didactic design, and the acceptance and use of online learning are analysed. The results show that students spend more time in university courses in the post-COVID era than in previous academic years. Students prefer to study alone and at individual times that are set by themselves. Study characteristics and the socio-economic situation of the students are not related to the acceptance and usage behaviour of online learning. The organisational and didactic design of online learning is correlated with its acceptance. In the end, the reflection on opportunities for online learning in the post-COVID era is concluded.

Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia.

Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this method is time-consuming, and it will interfere with the movement of the patient. In the recent outbreak of the coronavirus disease, the need for remote diagnosis and treatment of CD has become extremely urgent for clinical practice. To solve these problems, we propose a multi-view vision based CD severity scale scoring method, which detects the keypoint positions of the patient from the frontal and lateral images, and finally scores the severity scale by calculating head and neck motion angles. We compared the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) subscale scores calculated by our vision based method with the scores calculated by a neurologist trained in dyskinesia. An analysis of the correlation coefficient was then conducted. Intra-class correlation (ICC)(3,1) was used to measure absolute accuracy. Our multi-view vision based CD severity scale scoring method demonstrated sufficient validity and reliability. This low-cost and contactless method provides a new potential tool for remote diagnosis and treatment of CD.

Pilot Feasibility Study of a Multi-View Vision Based Scoring Method for Cervical Dystonia

Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to calculate the angle of the movement, but this method is time-consuming, and it will interfere with the movement of the patient. In the recent outbreak of the coronavirus disease, the need for remote diagnosis and treatment of CD has become extremely urgent for clinical practice. To solve these problems, we propose a multi-view vision based CD severity scale scoring method, which detects the keypoint positions of the patient from the frontal and lateral images, and finally scores the severity scale by calculating head and neck motion angles. We compared the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) subscale scores calculated by our vision based method with the scores calculated by a neurologist trained in dyskinesia. An analysis of the correlation coefficient was then conducted. Intra-class correlation (ICC)(3,1) was used to measure absolute accuracy. Our multi-view vision based CD severity scale scoring method demonstrated sufficient validity and reliability. This low-cost and contactless method provides a new potential tool for remote diagnosis and treatment of CD.

Construction and strategies of disease prevention and control system in the new era in Shanghai

After the epidemic of novel Coronavirus Disease 2019(COVID-19), construction of disease prevention and control has become a top priority. As a pioneer in the recovery of global economy and society, Shanghai should play a fundamental role in building a comprehensive system of public health and advanced disease prevention and control in the new era. In this article, we systematically categorize the requirements for the construction of disease prevention and control system in the new era, identify the weakness and challenges during and after the epidemic, and then make suggestions. It is proposed that we should utilize the important window period of the"14th Five-Year Plan", with the"Healthy China"strategy and municipal"20 Tasks for Public Health Construction"as the starting point, to make substantial contribution to the functional orientation, investment of resources, capacity building, operational mechanism and team building, which may provide scientific evidence for the reform and development of disease prevention and control system.

Study on curative effect of continuous positive psychological group intervention combined with Qingfei Paidu decoction on physical and mental health of front-line prevention of medical staff of COVID-19

Objective: To evaluate continuous positive psychological group intervention combined with Qingfei Paidu Decoction on psychological improvement and virus infection of front-line prevention medical staff of COVID-19.

Severe COVID-19-associated sepsis is different from classical sepsis induced by pulmonary infection with carbapenem-resistant klebsiella pneumonia (CrKP)

Purpose COVID-19 is also referred to as a typical viral septic pulmonary infection by 2019-nCoV. However, little is known regarding its characteristics in terms of systemic inflammation and organ injury, especially compared with classical bacterial sepsis. This article aims to learn the clinical characteristics and prognosis between COVID-19-associated sepsis and classic bacterial-induced sepsis. Methods In this retrospective cohort study, septic patients with COVID-19 in the intensive care unit (ICU) of a government-designed therapy center in Shenzhen, China between Jan 14, 2020 and Mar 10, 2020, and septic patients induced by carbapenem-resistant klebsiella pneumonia (CrKP) admitted at the ICU of the Second People’s Hospital of Shenzhen, China between Jan 1, 2014 and Oct 30, 2019, were enrolled. Demographic & clinical parameters including comorbidities, critical illness scores, treatment, and laboratory data, as well as prognosis were compared between the two groups. Risk factors for mortality and survival rate were analyzed using multivariable logistic regression and survival curve. Results A total of 107 patients with COVID-19 and 63 patients with CrKP were enrolled. A direct comparison between the two groups demonstrated more serious degrees of primary lung injury following 2019-nCoV infection (indicated by lower PaO2/FiO2) but milder systemic inflammatory response, lower sequential organ failure assessment (SOFA) score and better functions of the organs like heart, liver, kidney, coagulation, and circulation. However, the acquired immunosuppression presented in COVID-19 patients was more severe, which presented as lower lymphocyte counts. Moreover, the proportion of COVID-19 patients treated with corticosteroid therapy and extracorporeal membrane oxygenation was larger compared with CrKP patients who required less invasive mechanical ventilation. The incidence of hospitalized mortality and length of ICU stay and total hospital stay were also lower or shorter in viral sepsis. Similar results were obtained after being adjusted by age, gender, comorbidity and PaO2/FiO2. Lymphocytopenia and high acute physiology and chronic health evaluation II (APACH II) scores were common risk factors for in-hospital death. While the death cases of COVID-19 sepsis mostly occurred at the later stages of patients’ hospital stay. Conclusion Critical COVID-19 shares clinical characteristics with classical bacterial sepsis, but the degree of systemic inflammatory response, secondary organ damage and mortality rate are less severe. However, following 2019-nCoV infection, the level of immunosuppression may be increased and thus induce in more death at the later stage of patients’ hospital stay.

Impacts of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 variants Alpha and Delta on Coronavirus Disease 2019 transmission dynamics in the 15 most populous metropolitan statistical areas in the United States (preprint)

To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the 15 most populous metropolitan statistical areas (MSAs) in the United States (US) from January 2020 to September 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of social distancing by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to August 24, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeover times in each MSA. We find that 14-d ahead forecasts are reasonably accurate; these forecasts are being updated daily. Projections made on August 24, 2021 suggest that 5 of the 15 MSAs have already achieved herd immunity.

Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit (preprint)

Bayesian inference in biological modeling commonly relies on Markov chain Monte Carlo (MCMC) sampling of a multidimensional and non-Gaussian posterior distribution that is not analytically tractable. Here, we present the implementation of a practical MCMC method in the open-source software package PyBioNetFit (PyBNF), which is designed to support parameterization of mathematical models for biological systems. The new MCMC method, am, incorporates an adaptive move proposal distribution. For warm starts, sampling can be initiated at a specified location in parameter space and with a multivariate Gaussian proposal distribution defined initially by a specified covariance matrix. Multiple chains can be generated in parallel using a computer cluster. We demonstrate that am can be used to successfully solve real-world Bayesian inference problems, including forecasting of new Coronavirus Disease 2019 case detection with Bayesian quantification of forecast uncertainty. PyBNF version 1.1.9, the first stable release with am, is available at PyPI and can be installed using the pip package-management system on platforms that have a working installation of Python 3. PyBNF relies on libRoadRunner and BioNetGen for simulations (e.g., numerical integration of ordinary differential equations defined in SBML or BNGL files) and Dask.Distributed for task scheduling on Linux computer clusters.

Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States (preprint)

Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number [R]0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of [R]0 relates to a herd immunity threshold (HIT), which is given by 1 - 1/[R]0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level [R]0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. [R]0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21-January-2020 to 21-June-2020. Our [R]0 estimates characterize infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we find that no state has achieved herd immunity as of 20-September-2021. Significance StatementCOVID-19 will continue to threaten non-immune persons in the presence of ongoing disease transmission. We can estimate when sustained disease transmission will end by calculating the population-specific basic reproduction number [R]0, which relates to a herd immunity threshold (HIT), given by 1 - 1/[R]0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely. Here, we report state-level [R]0 estimates indicating that disease transmission varies considerably across states. Our [R]0 estimates can also be used to determine HITs for the Delta variant of COVID-19. On the basis of Delta-adjusted HITs, vaccination data, and serological survey results, we find that no state has yet achieved herd immunity.

Public practice, attitude and knowledge of coronavirus disease

Objective: To analyze the status of knowledge, attitude and practice of the coronavirus disease (COVID- 19) among the adults of 18-59 years Old in China, and to provide scientific basis for corresponding health education strategies.

Traditional Chinese Medicine Formulation Therapy in the Treatment of Coronavirus Disease 2019 (COVID-19).

This study aimed to investigate the efficacy of Traditional Chinese Medicine (TCM) decoction with different intervention timepoints in the treatment of coronavirus disease 2019 (COVID-19) patients. We retrospectively collected the medical records and evaluated the outcomes of COVID-19 patients that received TCM decoction treatment at different timepoints. A total of 234 COVID-19 patients were included in this study. Patients who received TCM decoction therapy within 3 days or 7 days after admission could achieve shorter hospitalization days and disease periods compared to those who received TCM decoction [Formula: see text] 7 days after admission (all [Formula: see text]). Patients who received TCM decoction therapy within 3 days had significantly fewer days to negative SARS-CoV-2 from nasopharyngeal/oral swab and days to negative SARS-CoV-2 from urine/stool/blood samples compared to those received TCM decoction [Formula: see text] days after admission (all [Formula: see text]). Patients who received TCM decoction therapy on the 3rd to 7th day after admission had a faster achievement of negative SARS-CoV-2 from urine/stool/blood samples compared to those who received TCM decoction [Formula: see text] days after admission ([Formula: see text]). Logistic models revealed that more days from TCM decoction to admission [Formula: see text] days might be a risk factor for long hospitalization days, disease period, and slower negative-conversion of SARS-CoV-2 (all [Formula: see text]). Conclusively, our results suggest that TCM decoction therapy should be considered at the early stage of COVID-19 patients.

ECMO application of patients with Critical Corona Virus Disease 2019 and fulminant myocarditis / 中华实验和临床病毒学杂志

Objective To evaluate the clinical experience of extracorporeal membrane oxygenation (ECMO) treatment on two cases of infection with the critical Corona Virus Disease 2019 (COVID-19) complicated by fulminant myocarditis (FM) . Methods This study selects two COVID-19 cases comorbid with fulminant myocarditis and had been treated with ECMO in Shenzhen Third People's Hospital from January 2020 to February 2020. We compare the index of inflammation, immunization, D-dimer and lactic acid before and after ECMO treatment in 24 and 96 hours, cardiopulmonary function before and after ECMO treatment in 24, 48, 72, 96 hours,. We also analyze the complications and clinical outcomes of the two cases during the ECMO treatment. Results Both patients were elderly obese men with chronic cardiopulmonary disease. Comparing the laboratory test results and imaging data of the two patients, the acute lung injury score, oxygenation index, albumin level, hypersensitive C-reactive protein, lactate and lactate dehydrogenase levels in 2 patients after ECMO treatment were improved as compared with those before ECMO treatment. Finally, case 1 died of multiple organ failure and his cardiac function continued to deteriorate, while, case 2 successfully withdrew and his cardiac function gradually improved. Conclusions For critical COVID-19 patients with fulminant myocarditis, ECMO treatment can improve pulmonary function in the short term, provide valuable time for rescuing COVID-19 patients with fulminant myocarditis.

Predictors for imaging progression on chest CT from coronavirus disease 2019 (COVID-19) patients.

OBJECTIVE: This study aimed to investigate the potential parameters associated with imaging progression on chest CT from coronavirus disease 19 (COVID-19) patients. RESULTS: The average age of 273 COVID-19 patients enrolled with imaging progression were older than those without imaging progression (p = 0.006). The white blood cells, platelets, neutrophils and acid glycoprotein were all decreased in imaging progression patients (all p < 0.05), and monocytes were increased (p = 0.025). The parameters including homocysteine, urea, creatinine and serum cystatin C were significantly higher in imaging progression patients (all p < 0.05), while eGFR decreased (p < 0.001). Monocyte-lymphocyte ratio (MLR) was significantly higher in imaging progression patients compared to that in imaging progression-free ones (p < 0.001). Logistic models revealed that age, MLR, homocysteine and period from onset to admission were factors for predicting imaging progression on chest CT at first week from COVID-19 patients (all p < 0.05). CONCLUSION: Age, MLR, homocysteine and period from onset to admission could predict imaging progression on chest CT from COVID-19 patients. METHODS: The primary outcome was imaging progression on chest CT. Baseline parameters were collected at the first day of admission. Imaging manifestations on chest CT were followed-up at (6±1) days.

Correlation between the migration scale index and the number of new confirmed Novel Coronavirus Pneumonia cases in China (preprint)

Background: In late December, 2019, patients of atypical pneumonia due to an unidentified microbial agent were reported in Wuhan, Hubei Province, China. Subsequently, a novel coronavirus was identified as the causative pathogen which was named 2019 novel coronavirus (2019-nCoV). As of Feb 12, 2020, more than 44,000 cases of 2019-nCoV infection have been confirmed in China and continue to expand. Provinces, municipalities and autonomous regions of China have launched first-level response to major public health emergencies one after another from Jan 23.2020, which means restricting movement of people among provinces, municipalities and autonomous regions. The aim of this study was to explore the correlation between the migration scale index and the number of confirmed Novel Coronavirus Pneumonia (NCP) cases and to depict the effect of restricting population movement. Methods: Excel 2010 was used to demonstrate the temporal distribution at the day level and SPSS 23.0 was used to analyze the correlation between the migration scale index and the number of confirmed NCP cases. Results: Since January 23, 2020, Wuhan migration scale index has dropped significantly and since January 26, 2020, Hubei province migration scale index has dropped significantly. New confirmed NCP cases per day in China except Wuhan gradually increased since January 24, 2020, and showed a downward trend from February 6, 2020. New confirmed NCP cases per day in China except Hubei province gradually increased since January 24, 2020, and maintained at a high level from January 24, 2020 to February 4, 2020, then showed a downward trend. Wuhan emigration scale index from January 9 to January 22, January 10 to January 23 and January 11 to January 24 was correlated with the number of new confirmed NCP cases per day in China except Wuhan from January 22 to February 4. Hubei province emigration scale index from January 10 to January 23 and January 11 to January 24 was correlated with the number of new confirmed NCP cases per day in China except Hubei province from January 22 to February 4.Conclusions: People who left Wuhan from January 9 to January 22 may lead to the outbreak in China except Wuhan and people who left Hubei province from January 10 to January 24 may lead to the outbreak in China except Hubei province. “Wuhan lockdown” and Hubei province launching first-level response to major public health emergencies may have had a good effect the control NCP epidemic. Because there were still new confirmed NCP cases in China except Wuhan and in China except Hubei province and this may indicate that the occurrence of second-generation cases.