Depressive symptoms faced by non-native international medical students in China during COVID-19

This study examines depressive symptoms faced by non-native international medical students studying in China during the COVID-19 pandemic. The targeted population for this cross-sectional study included non-native medical students studying in Chinese universities. This study used convenience sampling. An online, self-administered questionnaire was distributed to international medical students studying in Chinese universities from February 2020 to June 2021. The questionnaire collected demographic data, information regarding struggles faced, and used the CES-D-10 Likert scale to assess both the challenges and depression symptoms, respectively. By analyzing the 1,207 students’ responses, the study found that students with poor Chinese language were two times more likely to suffer from depressive symptoms (OR = 2.67;value of p 0.00). Moreover, female students were found more prone (76.35%) than their male counterparts (44.96%). The study found that food adaptability, health issues, accommodation issues, and financial issues were related factors contributing to depressive symptoms among non-native international medical students during the COVID-19 pandemic. The study tried to highlight the factors that resulted in depressive symptoms among non-native international medical students, and the findings may help diplomatic representatives take necessary actions to help their citizens during this difficult time.

COVID-19 Propagation Prediction Model Using Improved Grey Wolf Optimization Algorithms in Combination with XGBoost and Bagging-Integrated Learning

Toward solving the slow convergence and low prediction accuracy problems associated with XGBoost in COVID-19-based transmission prediction, a novel algorithm based on guided aggregation is presented to optimize the XGBoost prediction model. In this study, we collect the early COVID-19 propagation data using web crawling techniques and use the Lasso algorithm to select the important attributes to simplify the attribute set. Moreover, to improve the global exploration and local mining capability of the grey wolf optimization (GWO) algorithm, a backward learning strategy has been introduced, and a chaotic search operator has been designed to improve GWO. In the end, the hyperparameters of XGBoost are continuously optimized using COLGWO in an iterative process, and Bagging is employed as a method of integrating the prediction effect of the COLGWO-XGBoost model optimization. The experiments, firstly, compared the search means and standard deviations of four search algorithms for eight standard test functions, and then, they compared and analyzed the prediction effects of fourteen models based on the COVID-19 web search data collected in China. Results show that the improved grey wolf algorithm has excellent performance benefits and that the combined model with integrated learning has good prediction ability. It demonstrates that the use of network search data in the early spread of COVID-19 can complement the historical information, and the combined model can be further extended to be applied to other prevention and control early warning tasks of public emergencies. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Potential Novel COVID-19 Vaccine With RBD-HR1/HR2 Hexamer Structure (preprint)

The COVID-19 pandemic and the continued spreading of the SARS-CoV-2 variants have brought a grave public health consequence and severely devastated the global economy with recessions. Vaccination is considered as one of the most promising and efficient methods to end the COVID-19 pandemic and mitigate the disease conditions if infected. Although a few vaccines have been developed with an unprecedented speed, scientists around the world are continuing pursuing the best possible vaccines with innovations. Comparing to the expensive mRNA vaccines and attenuated/inactivated SARS-CoV-2 vaccines, recombinant protein vaccines have certain advantages, including their safety (non-virus components), potential stronger immunogenicity, broader protection, ease of scaling-up production, reduced cost, etc. In this study, we reported a novel COVID-19 vaccine generated with RBD-HR1/HR2 hexamer that was creatively fused with the RBD domain and heptad repeat 1 (HR1) or heptad repeat 2 (HR2) to form a dumbbell-shaped hexamer to target the spike S1 subunit. The novel hexamer COVID-19 vaccine induced high titers of neutralizing antibody in mouse studies (>100,000), and further experiments also showed that the vaccine also induced an alternative antibody to the HR1 region, which probably alleviated the drop of immunogenicity from the frequent mutations of SARS-CoV-2.

Bayesian Estimation of the Seroprevalence of Antibodies to SARS-CoV-2 (preprint)

Accurately estimating the seroprevalence of antibodies to SARS-CoV-2 requires the use of appropriate methods. Bayesian statistics provides a natural framework for considering the variabilities of specificity and sensitivity of the antibody tests, as well as for incorporating prior knowledge of viral infection prevalence. We present a full Bayesian approach for this purpose, and we demonstrate the utility of our approach using a recently published large-scale dataset from the U.S. CDC.

A Bayesian Framework for Estimating the Risk Ratio of Hospitalization for People with Comorbidity Infected by the SARS-CoV-2 Virus (preprint)

Estimating the hospitalization risk for people with certain comorbidities infected by the SARS-CoV-2 virus is important for developing public health policies and guidance based on risk stratification. Traditional biostatistical methods require knowing both the number of infected people who were hospitalized and the number of infected people who were not hospitalized. However, the latter may be undercounted, as it is limited to only those who were tested for viral infection. In addition, comorbidity information for people not hospitalized may not always be readily available for traditional biostatistical analyses. To overcome these limitations, we developed a Bayesian approach that only requires the observed frequency of comorbidities in COVID-19 patients in hospitals and the prevalence of comorbidities in the general population. By applying our approach to two different large-scale datasets in the U.S., our results consistently indicated that cardiovascular diseases carried the highest hospitalization risk for COVID-19 patients, followed by diabetes, chronic respiratory disease, hypertension, and obesity, respectively. Significance StatementWe developed a novel Bayesian approach to estimate the hospitalization risk for people with comorbidities infected with the SARS-CoV-2 virus. Our results indicated that cardiovascular diseases carried the highest hospitalization risk for COVID-19 patients, followed by diabetes, chronic respiratory disease, hypertension, and obesity, respectively.

A Logistic Model for Age-Specific COVID-19 Case-Fatality Rates (preprint)

Objectives To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Materials and Method Based on two large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. Results and Discussion We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a predicted theoretical upper limit for males (32%), females (21%), and the general population (23%). Conclusion Our logistic model provided quantitative insight on the dynamics of CFR.

Corporate Pandemic Bonds (preprint)

We examine corporate pandemic bonds whose proceeds are committed to COVID-19 containing activities. We find an average cumulative abnormal stock return of 1.33–1.71% during the five trading days surrounding their issuance announcement. Also, their yield spread is 8.9–18 basis points lower than that of otherwise similar non-pandemic bonds. Additional evidence suggests that these findings are due to the government’s supports for pandemic bond issuances rather than the prosocial clienteles of financial investors.

Vaginal delivery after 37 days of a convalescent pregnant woman with COVID-19: a case report / 中华围产医学杂志

We present a case report of a healthy neonate born by vaginal delivery to a woman who had recovered from COVID-19 after 37 days of discharge. The pregnant woman had fever, cough, and chills at 33 +1 gestational weeks and was diagnosed with COVID-19 by coronavirus nucleic acid test one day later. She recovered and was discharged after a series of treatment, and the 2019 novel coronavirus nucleic acid test and pulmonary CT were negative at the 2nd and 4th weeks after being discharged. The patient was admitted in early labor at 38 +4 gestational weeks and delivered a healthy newborn vaginally at that day. Both the mother and the baby were in good condition. All the maternal or neonatal specimens taken immediately after birth in the delivery room for 2019 novel coronavirus nucleic acid tests were negative, including the maternal pharynx, rectal and cervical secretions, amniotic fluid, an neonatal pharynx and rectal swabs. The qualitative examination of 2019 novel coronavirus antibodies in the maternal venous blood test showed that both IgG and IgM were positive. While the same test for neonatal cord blood and femoral vein blood showed negative results. No inflammatory reaction was found in the placenta and immunohistochemistry detection of novel coronavirus N protein was negative. The mother and newborn were observed postnatally and treated in the same ward, neither of them had fever, cough or fatigue, and were discharged three days after delivery. The qualitative examination of 2019 novel coronavirus antibodies (IgM and IgG) in the femoral vein blood of the nenonate 27 days old showed negative results.

Impacts and strategies for the construction of the disease control and prevention system in the COVID-19 outbreak / 上海预防医学

The outbreak of COVID-19 has exposed many shortcomings in disease control and prevention system (DCPS) of China. Resolving the problems and strengthening the DCPS became the top priority in China’s public policy agenda. This paper revealed the problems of the system regarding policy-making, regulations, operation mechanism and staff, and proposed several strategies from three aspects of legal construction, management system, and operation mechanism, including: 'Prevention first' should be incorporated into the national legal system, all the departments should be engaged in 'Healthy China 2030' initiative, laws and regulations should be amended, new disease prevention and control management institutions should be set up, a high-quality professional team should be retained, the regional health information exchange channels should be strengthened, the coordinated mechanism for disease prevention and control should be normalized, the long-term investment mechanism should be established, and the equipment renewal and reserve system should be improved.