Indirect Effects of the COVID-19 Pandemic on Routine Childhood Vaccination in Low-Income Countries: A Systematic Review to Set the Scope for Future Pandemics (preprint)

The COVID-19 pandemic halted progress in global vaccine coverage and disrupted routine childhood vaccination practices worldwide. While there is ample evidence of vaccination declines experienced during the pandemic, it is less clear how low-income countries were affected. We executed a systematic review to synthesize the current literature on impacts to routine childhood vaccinations in low-income countries from January 1, 2020 to February 8, 2023. We collected data using an extraction form on Covidence and assessed the quality of studies included in the review using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Effect estimates for changes in vaccination during the pandemic were reported and summarized. Factors that influenced changes were grouped into descriptive themes. Thirteen studies, encompassing 18 low-income countries and evaluating 15 vaccines at varying doses, were included in the final review. We found that routine childhood vaccinations during the COVID-19 pandemic varied considerably by vaccine type, location, and phase of the pandemic. Nine different themes were identified as factors that influenced changes in vaccination. Documenting past experiences and lessons learned is crucial for informing preparedness efforts in anticipation of future public health emergencies. Failure to effectively address these things in the next public health emergency could result in a recurrence of declining routine childhood vaccinations.

Psychological Distress Reported by Patients with Atrial Fibrillation in China During COVID-19 (preprint)

Background: The COVID-19 pandemic significantly impacted routine cardiovascular health assessments and services. The objective of this study was to explore the factors associated with self-reported psychological distress among a sample of patients with atrial fibrillation (AF) in China in relation to COVID-19. Methods: An online survey was administered to 288 patients with AF at several hospitals in China. The survey consisted of three sections: demographic characteristics, questions related to COVID-19, and the General Health Questionnaire-12 (GHQ-12). Results: A total of 177 patients with AF completed the baseline survey; 177 (61.46%) were male and 133 (46.18%) were older than 65 years. High levels of psychological distress (GHQ-12 ≥3) were observed in 27 (9.4%) participants of the sample. These high levels were found to be associated with older age, radiofrequency ablation, drinking, and combined basic diseases (p values < .05). Logistic regression analysis showed that psychological distress in patients with AF was associated with radiofrequency ablation (OR = 0.316, 95% CI = 0.147–0.666), drinking (OR = 4.761, 95% CI = 2.076–10.916), and concerns regarding infection (OR = 1.244, 95% CI = 1.052–1.472). Conclusions: COVID-19 has resulted in high levels of psychological distress in approximately 9.4% of patients with AF in China. Factors associated with high levels of psychological distress in AF patients include older age, radiofrequency ablation, drinking, and combined comorbidities. These findings highlight the importance of enhancing psychological health throughout the course of infectious pandemics.

Transmission risk of asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis

Background Global evidence on the transmission of asymptomatic SARS-CoV-2 infection needs to be synthesized. Methods A search of 4 electronic databases (PubMed, EMBASE, Cochrane Library, and Web of Science databases) as of January 24, 2021 was performed. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Studies which reported the transmission rate among close contacts with asymptomatic SARS-CoV-2 cases were included, and transmission activities occurred were considered. The transmission rates were pooled by zero-inflated beta distribution. The risk ratios (RRs) were calculated using random-effects models. Results Of 4923 records retrieved and reviewed, 15 studies including 3917 close contacts with asymptomatic indexes were eligible. The pooled transmission rates were 1.79 per 100 person-days (or 1.79%, 95% confidence interval [CI] 0.41%–3.16%) by asymptomatic index, which is significantly lower than by presymptomatic (5.02%, 95% CI 2.37%–7.66%;P<.001), and by symptomatic (5.27%, 95% CI 2.40%–8.15%;P<.001). Subgroup analyses showed that the household transmission rate of asymptomatic index was (4.22%, 95% CI 0.91%–7.52%), four times significantly higher than non-household transmission (1.03%, 95% CI 0.73%–1.33%;P=.03), and the asymptomatic transmission rate in China (1.82%, 95% CI 0.11%–3.53%) was lower than in other countries (2.22%, 95% CI 0.67%–3.77%;P=.01). Conclusions People with asymptomatic SARS-CoV-2 infection are at risk of transmitting the virus to their close contacts, particularly in household settings. The transmission potential of asymptomatic infection is lower than symptomatic and presymptomatic infections. This meta-analysis provides evidence for predicting the epidemic trend and promulgating vaccination and other control measures. Trial Registration Registered with PROSPERO International Prospective Register of Systematic Reviews, CRD42021269446;https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=269446

Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns

In this study, we construct China's aggregate sentiment indicator (SsPCA) based on the method of Huang et al. (2021a), which employs a new dimension reduction method of scaled principal component analysis (PCA), to aggregate useful information from individual sentiment proxies, and further examine its return predictability for the Chinese stock market. The empirical evidence suggests that SsPCA significantly improves the prediction accuracy for stock market returns both in and out of the sample, and also obtains considerable economic gain for a mean-variance investor. Additionally, the forecasting effect of SsPCA is superior to that of SPCA and SPLS, evaluated using the traditional PCA and partial least square methods, respectively. Moreover, relative to the period of the bull market, SsPCA exhibits better ability in forecasting stock market returns during the bear market. Finally, special events, such as the outbreak of coronavirus disease 2019 (COVID-19), also affect the predictive performance of the sentiment indicator.

Identification of asymptomatic COVID-19 patients on chest CT images using Transformer-or CNN-based deep learning models (preprint)

Backgroud To evaluate the feasibility of deep learning (DL) models in identifying asymptomatic COVID-19 patients, based on chest CT images.Methods In this retrospective study, six DL models (Xception, NASNet, ResNet, EfficientNet, ViT, and Swin), based on convolutional neural networks (CNNs)-or Transformer-architectures, were trained to identify asymptomatic patients with COVID-19 on chest CT images. Data from Yangzhou was randomly split into the training set (n = 2,140) and the internal-validation set (n = 360). Data from Suzhou was the external-test set (n = 200). Models’ performance was assessed by accuracy, recall and specificity and was compared with that of two radiologists.Results A total of 2,700 chest CT images were collected in this study. In the validation dataset, the Swin model achieved the highest accuracy of 0.994, followed by EfficientNet model (0.954). The recall and precision of the Swin model were 0.989 and 1.000. In the test dataset, the Swin model still was the best that achieved the highest accuracy (0.980). All the DL models performed remarkable than two experts. Lastly, the time on the test set diagnosis spent by two experts 42min17s (Junior) and 29min43s (Senior), was significantly higher than that of those DL models (all below 2min).Conclusions This study evaluated the feasibility of multiple DL models in distinguishing asymptomatic patients with COVID-19 from healthy subjects on chest CT images. It found a Transformer model, the Swin model, performed best.

The relationship between online learning and eye strain in college students during the COVID-19 outbreak

Objective To describe online learning and eye strain situation of college students during the COVID-19 outbreak, to provide a scientific basis for guiding students' eye health. Methods A self-filled electronic questionnaire survey through questionnaire star was administered to college students across China. Information about online learning and eye strain of 1 046 college students during the epidemic was collected in Hefei, Anhui Province from March 16 to 20, 2020. The univariate and multivariate Logistic regression analysis were performed to analyze the association between online learning and eye strain of college students. Results The rate of eye strain during online learning was 72.1%, totally of 68.4% in 421 male students and 74.6% in 625 female students. Boys with online learning time < 6 h/d, slow internet access, difficulty in understanding online class reported higher rate of eye strain than girls(X 2=17.36, 8.72, 7.02, P < 0.05). Freshmen reported the highest rate of slow internet access occasionally and active online class(X 2=15.26, 16.11, P < 0.05), junior students reported highest rate of online learning time < 6 h/d, and easy understandable online class(X 2=15.33, 32.59, P < 0.05), medical college students reported higher rate of slow internet access, inactive online class than non-medical college students(X 2=11.79, 11.03, P < 0.05). Multivariate Logistic regression analysis showed that odds ratio(OR) of eye strain in females was 1.40 (1.06-1.87), compared with males;the OR of eye strain were 1.43 (1.01-2.03) and 1.54 (1.10-2.15) in the groups with online learning time 6- < 8 h/d and 8 h/d, respectively, compared with the group with online learning time < 6 h/d, the OR of eye strain in the groups with slow internet access was 2.28 (1.25-4.14), compared with students without slow internet access, the OR of eye strain in the capable-to-understand and difficult-to-understand group were 2.54 (1.73-3.74) and 5.40 (2.70-10.80) respectively, compared with the easy-to-understand group. Conclusion Female students, online learing time 8 h/d, slow internet access, difficult to understand class content were positively related with college students eye strain. Attention should be paid to the eye health of college students to reduce the adverse effects of online learning on vision.during the COVID-19 epidemic.

Homo-harringtonine (HHT) - A highly effective drug against coronaviruses and the potential for large-scale clinical applications (preprint)

In the search for treatment schemes of COVID-19, we start by examining the general weakness of coronaviruses and then identify approved drugs attacking that weakness. The approach, if successful, should identify drugs with a specific mechanism that is at least as effective as the best drugs proposed and are ready for clinical trials. All coronaviruses translate their non-structural proteins (~16) in concatenation, resulting in a very large super-protein. Homo-harringtonine (HHT), which has been approved for the treatment of leukemia, blocks protein elongation very effectively. Hence, HHT can repress the replication of many coronaviruses at the nano-molar concentration. In two mouse models, HHT clears SARS-CoV-2 in 3 days, especially by nasal dripping of 40 ug per day. We also use dogs to confirm the safety of HHT delivered by nebulization. The nebulization scheme could be ready for large-scale applications at the onset of the next epidemics. For the current COVID-19, a clinical trial has been approved by the Ditan hospital of Beijing but could not be implemented for want of patients. The protocol is available to qualified medical facilities.

Chest CT for Detecting COVID-19: A Systematic Review and Meta-Analysis of Diagnostic Accuracy (preprint)

OBJECTIVE: The purpose of this article was to perform a systematic review and meta- analysis regarding the diagnostic test accuracy of chest CT for detecting Coronavirus Disease 2019 (COVID-19).METHODS: PubMed, EMBASE, Web of Science and CNKI were searched up to March 12, 2020. We included studies providing information regarding diagnostic test accuracy of chest CT for COVID-19 detection. The methodologic quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies–2 tool. Sensitivity and specificity were pooled.RESULTS: Ten studies (n = 2657 patients) were included. The risks of bias in all studies were moderate in general. Pooled sensitivity was 93% (95% CI: 85 - 97%), and only one study reported specificity (25%, 95% CI:22-30%). There was substantial heterogeneity according to the Cochran Q test (p < 0.01) and Higgins I2 heterogeneity index (96% for sensitivity). After dividing the studies into two groups based on the study site, we found that the sensitivity of chest CT was great in Wuhan (the most affected city by the epidemic) and the sensitivity values were very close to each other (97%, 96% and 99%, respectively). In the regions other than Wuhan, the sensitivity varied from 69% to 98%.CONCLUSION: Chest CT offers the great sensitivity for detecting COVID-19, especially in region with severe epidemic situation. However, the specificity is low. In the context of emergency disease control, chest CT provide a fast, convenient and effective method to early recognize suspicious cases and might contribute to confine epidemic.