A national risk analysis model (NRAM) for the assessment of COVID-19 epidemic.

COVID-19 has caused a critical health concern and severe economic crisis worldwide. With multiple variants, the epidemic has triggered waves of mass transmission for nearly 3 years. In order to coordinate epidemic control and economic development, it is important to support decision-making on precautions or prevention measures based on the risk analysis for different countries. This study proposes a national risk analysis model (NRAM) combining Bayesian network (BN) with other methods. The model is built and applied through three steps. (1) The key factors affecting the epidemic spreading are identified to form the nodes of BN. Then, each node can be assigned state values after data collection and analysis. (2) The model (NRAM) will be built through the determination of the structure and parameters of the network based on some integrated methods. (3) The model will be applied to scenario deduction and sensitivity analysis to support decision-making in the context of COVID-19. Through the comparison with other models, NRAM shows better performance in the assessment of spreading risk at different countries. Moreover, the model reveals that the higher education level and stricter government measures can achieve better epidemic prevention and control effects. This study provides a new insight into the prevention and control of COVID-19 at the national level.

Comparative Study of Government Response Measures and Epidemic Trends for COVID-19 Global Pandemic.

The ongoing novel coronavirus (COVID-19) epidemic has evolved into a full range of challenges that the world is facing. Health and economic threats caused governments to take preventive measures against the spread of the disease. This study aims to provide a correlation analysis of the response measures adopted by countries and epidemic trends since the COVID-19 outbreak. This analysis picks 13 countries for quantitative assessment. We select a trusted model to fit the epidemic trend curves in segments and catch the characteristics based on which we explore the key factors of COVID-19 spread. This review generates a score table of government response measures according to the Likert scale. We use the Delphi method to obtain expert judgments about the government response in the Likert scale. Furthermore, we find a significant negative correlation between the epidemic trend characteristics and the government response measure scores given by experts through correlation analysis. More stringent government response measures correlate with fewer infections and fewer waves in the infection curves. Stringent government response measures curb the spread of COVID-19, limit the number of total infectious cases, and reduce the time to peak of total cases. The clusters of the results categorize the countries into two specific groups. This study will improve our understanding of the prevention of COVID-19 spread and government response.

Ultrasound Imaging Findings of Acute Testicular Infection in Patients With Coronavirus Disease 2019: A Single-Center-Based Study in Wuhan, China.

OBJECTIVES: Coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic, raising widespread public health concerns. Our team treated hospitalized patients with COVID-19 in Wuhan, where the outbreak first began, and we suspected that SARS-CoV-2 may cause testicular infection in male patients. We conducted this study to explore that observation. METHODS: We enrolled male patients with a confirmed diagnosis of COVID-19 and performed a bedside ultrasound (US) examination of the scrotum, focused on findings of acute inflammation such as tunica albuginea thickening, enlargement and heterogeneous echogenicity of the testis, epididymis, or both, an abscess, scrotal wall edema, and hydrocele. Then we compared the proportions of observed epididymo-orchitis in patients from different age groups and COVID-19 severity groups. RESULTS: A total of 142 patients with COVID-19 were enrolled in our study, and 32 (22.5%) patients had acute orchitis, epididymitis, or epididymo-orchitis on scrotal US imaging, according to the diagnosis criteria. The observed risk of acute scrotal infection increased with age, with the incidence reaching 53.3% in men older than 80 years. We also observed that men with severe COVID-19 had a significantly higher possibility of epididymo-orchitis compared to the nonsevere COVID-19 group (P = .037). CONCLUSIONS: This study shows US imaging evidence that SARS-CoV-2 may cause infection of the testis or epididymis, and the risk is worthy of the attention of clinicians.

The Impact of Intolerance of Uncertainty on Test Anxiety: Student Athletes During the COVID-19 Pandemic.

Test anxiety caused by intolerance of uncertainty has a negative impact on the physical and mental health of student athletes, especially in the context of the coronavirus disease 2019 (COVID-19) pandemic. A total of 556 grade three high school student athletes in Chongqing, China, were investigated using the Test Anxiety Scale (TAS), Intolerance of Uncertainty Scale-12 (IUS-12), Perceived Social Support Scale, and Coping Style Scale for Middle School Students. Results reveal that more than half the student athletes experienced test anxiety, and the severity was above average during the COVID-19 pandemic. There was a significant correlation between intolerance of uncertainty, perceived social support, coping style, and test anxiety. A positive correlation was found between test anxiety, intolerance of uncertainty, and coping style toward emotions, and a negative correlation between test anxiety, perceived social support, and coping style toward problems. Intolerance of uncertainty has a direct predictive effect on test anxiety, and perceived social support and coping style play a chain mediator role between intolerance of uncertainty and test anxiety. By constructing the mediating effect model, we can, to some extent, reveal the mechanism of the influence of intolerance of uncertainty on test anxiety. This study has a certain reference value for the prevention of test anxiety in student athletes in the context of the COVID-19 pandemic.

Application of quantitative lung ultrasound instead of CT for monitoring COVID-19 pneumonia in pregnant women: a single-center retrospective study.

BACKGROUND: Computed tomography (CT) is the preferred imaging technique for the evaluation of COVID-19 pneumonia. However, it is not suitable as a monitoring tool for pregnant women because of the risk of ionizing radiation damage to the fetus as well as the possible infection of others. In this study, we explored the value of bedside lung ultrasound (LUS) as an alternative to CT for the detection and monitoring of lung involvement in pregnant women with COVID-19. METHODS: Clinical and LUS data of 39 pregnant women with COVID-19 were retrospectively reviewed. All LUS and CT images were analyzed to summarize the findings and calculate LUS scores and CT scores for each patient. LUS findings were compared with CT, and correlation between LUS scores and CT scores was evaluated. RESULTS: Among the 39 pregnant women, there were 6 mild-type cases, 29 common-type cases, 4 severe-type cases, and no critical-type cases. The most common LUS findings of COVID-19 pneumonia in pregnant women were various grades of multiple B-lines (84.6%), thickened and irregular pleural lines (71.8%), pleural effusion (61.5%) and small multifocal consolidation limited to the subpleural space (35.9%). The mean LUS score at admission was 0 points in mild-type cases, 10.6 points in common-type cases and 15.3 points in severe-type cases (P < 0.01). The correlation between LUS scores and CT was 0.793. All patients were clinically cured and each underwent an average of three LUS follow-ups during hospitalization. The mean LUS score at discharge was 5.6 points lower than that at admission. The consistency of LUS and chest CT during follow-up was 0.652. CONCLUSIONS: Quantitative LUS scoring can effectively instead of CT for detecting and monitoring of COVID-19 pneumonia in pregnant women and protect fetuses from the risk of ionizing radiation.

Semiquantitative lung ultrasound scores in the evaluation and follow-up of critically ill patients with COVID-19: a single-center study.

RATIONALE AND OBJECTIVES: Chest CT is not suitable for critically ill patients with COVID-19 and lung ultrasound (LUS) may play an important role for these patients. In this study, we summarized the findings of LUS and explore the value of semiquantitative LUS scores in evaluation and follow-up of COVID-19 pneumonia. MATERIALS AND METHODS: Retrospectively studied the LUS and chest CT imaging of 128 critically ill patients with COVID-19. The imaging data were reviewed to acquire the LUS and CT scores. The correlation between LUS scores and CT scores were made to evaluate the accuracy of LUS. A cut-off point of LUS score was calculated to distinguish critical-type patients from severe-type patients. LUS follow-up of 72 patients were compared with the gold standard chest CT. RESULTS: The most common LUS features of COVID-19 pneumonia were crowded or coalescent B-lines with multifocal small consolidations in multi-zone. The mean LUS score was 8.1 points in severe-type patients and 15.7 points in critical-type patients (P<0.05). The correlation between LUS scores and CT scores was high (r=0.891, p<0.01) and it was higher in critical-type patients than that in severe-type patients. The LUS score higher than 10.5 points had a 97.4% sensitivity and 75.0% specificity to distinguish critical-type patients. The consistency of LUS and chest CT in follow-up was 0.596, with higher consistency in diagnosis of lesion progression (Kappa values was 0.774). CONCLUSION: Our scoring system provides a more quantitative use of LUS findings and accurate evaluation of lung damage for critically ill patients with COVID-19.

Suspected myocardial injury in patients with COVID-19: Evidence from front-line clinical observation in Wuhan, China.

BACKGROUND: A novel coronavirus disease (COVID-19) in Wuhan has caused an outbreak and become a major public health issue in China and great concern from international community. Myocarditis and myocardial injury were suspected and may even be considered as one of the leading causes for death of COVID-19 patients. Therefore, we focused on the condition of the heart, and sought to provide firsthand evidence for whether myocarditis and myocardial injury were caused by COVID-19. METHODS: We enrolled patients with confirmed diagnosis of COVID-19 retrospectively and collected heart-related clinical data, mainly including cardiac imaging findings, laboratory results and clinical outcomes. Serial tests of cardiac markers were traced for the analysis of potential myocardial injury/myocarditis. RESULTS: 112 COVID-19 patients were enrolled in our study. There was evidence of myocardial injury in COVID-19 patients and 14 (12.5%) patients had presented abnormalities similar to myocarditis. Most of patients had normal levels of troponin at admission, that in 42 (37.5%) patients increased during hospitalization, especially in those that died. Troponin levels were significantly increased in the week preceding the death. 15 (13.4%) patients have presented signs of pulmonary hypertension. Typical signs of myocarditis were absent on echocardiography and electrocardiogram. CONCLUSIONS: The clinical evidence in our study suggested that myocardial injury is more likely related to systemic consequences rather than direct damage by the 2019 novel coronavirus. The elevation in cardiac markers was probably due to secondary and systemic consequences and can be considered as the warning sign for recent adverse clinical outcomes of the patients.

Forecasting of COVID-19 Spread with dynamic transmission rate

The COVID-19 was firstly reported in Wuhan, Hubei province, and it was brought to all over China by people travelling for Chinese New Year. The pandemic coronavirus with its catastrophic effects is now a global concern. Forecasting of COVID-19 spread has attracted a great attention for public health emergency. However, few researchers look into the relationship between dynamic transmission rate and preventable measures by authorities. In this paper, the SEIR (Susceptible Exposed Infectious Recovered) model is employed to investigate the spread of COVID-19. The epidemic spread is divided into two stages: before and after intervention. Before intervention, the transmission rate is assumed to be a constant since individual, community and government response has not taken into place. After intervention, the transmission rate is reduced dramatically due to the societal actions or measures to reduce and prevent the spread of disease. The transmission rate is assumed to follow an exponential function, and the removal rate is assumed to follow a power exponent function. The removal rate is increased with the evolution of the time. Using the real data, the model and parameters are optimized. The transmission rate without measure is calculated to be 0.033 and 0.030 for Hubei and outside Hubei province, respectively. After the model is established, the spread of COVID-19 in Hubei province, France and USA is predicted. From results, USA performs the worst according to the dynamic ratio. The model has provided a mathematical method to evaluate the effectiveness of the government response and can be used to forecast the spread of COVID-19 with better performance.