Case clustering, contact stratification, and transmission heterogeneity of SARS-CoV-2 Omicron BA.5 variants in Urumqi, China: An observational study.

Background: From August to September 2022, Urumqi, the capital of the Xinjiang Uygur Autonomous Region in China, faced its largest COVID-19 outbreak caused by the emergence of the SARS-CoV-2 Omicron BA.5.2 variants. Although the superspreading of COVID-19 played an important role in triggering large-scale outbreaks, little was known about the superspreading potential and heterogeneity in the transmission of Omicron BA.5 variants. Methods: In this retrospective observational, contact tracing study, we identified 1139 laboratory-confirmed COVID-19 cases of Omicron BA.5.2 variants, and 51 323 test-negative close contacts in Urumqi from 7 August to 7 September 2022. By using detailed contact tracing information and exposure history of linked case-contact pairs, we described stratification in contact and heterogeneity in transmission across different demographic strata, vaccine statuses, and contact settings. We adopted beta-binomial models to characterise the secondary attack rate (SAR) distribution among close contacts and modelled COVID-19 transmission as a branching process with heterogeneity in transmission governed by negative binomial models. Results: After the city lockdown, the mean case cluster size decreased from 2.0 (before lockdown) to 1.6, with decreased proportions of contacts in workplace and community settings compared with household settings. We estimated that 14% of the most infectious index cases generated 80% transmission, whereas transmission in the community setting presented the highest heterogeneity, with 5% index cases seeding 80% transmission. Compared with zero, one, and two doses of inactivated vaccine (Sinopharm), index cases with three doses of vaccine had a lower risk of generating secondary cases in terms of the reproduction number. Contacts of female cases, cases with ages 0-17 years, and household settings had relatively higher SAR. Conclusions: In the context of intensive control measures, active case detection, and relatively high vaccine coverage, but with an infection-naive population, our findings suggested high heterogeneity in the contact and transmission risks of Omicron BA.5 variants across different demographic strata, vaccine statuses, and contact settings. Given the rapid evolution of SARS-CoV-2, investigating the distribution of transmission not only helped promote public awareness and preparedness among high-risk groups, but also highlighted the importance of continuously monitoring the transmission characteristics of genetic variants of SARS-CoV-2.

Platelet-albumin-bilirubin score and neutrophil-to-lymphocyte ratio predict intensive care unit admission in patients with end-stage kidney disease infected with the Omicron variant of COVID-19: a single-center prospective cohort study.

OBJECTIVES: The objective of this study was to develop clinical scores to predict the risk of intensive care unit (ICU) admission in patients with COVID-19 and end stage kidney disease (ESKD). METHODS: This was a prospective study in which 100 patients with ESKD were enrolled and divided into two groups: the ICU group and the non-ICU group. We utilized univariate logistic regression and nonparametric statistics to analyze the clinical characteristics and liver function changes of both groups. By plotting receiver operating characteristic curves, we identified clinical scores that could predict the risk of ICU admission. RESULTS: Out of the 100 patients with Omicron infection, 12 patients were transferred to the ICU due to disease aggravation, with an average of 9.08 days from hospitalization to ICU transfer. Patients transferred to the ICU more commonly experienced shortness of breath, orthopnea, and gastrointestinal bleeding. The peak liver function and changes from baseline in the ICU group were significantly higher, with p values <.05. We found that the baseline platelet-albumin-bilirubin score (PALBI) and neutrophil-to-lymphocyte ratio (NLR) were good predictors of ICU admission risk, with area under curve values of 0.713 and 0.770, respectively. These scores were comparable to the classic Acute Physiology and Chronic Health Evaluation II (APACHE-II) score (p > .05). CONCLUSION: Patients with ESKD and Omicron infection who are transferred to the ICU are more likely to have abnormal liver function. The baseline PALBI and NLR scores can better predict the risk of clinical deterioration and early transfer to the ICU for treatment.

The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (B.1.1.529) variant is highly transmissible with potential immune escape. Hence, control measures are continuously being optimized to guard against large-scale coronavirus disease 2019 (COVID-19) outbreaks. This study aimed to explore the relationship between the intensity of control measures in response to different SARS-CoV-2 variants and the degree of outbreak control at city level. METHODS: A retrospective study was conducted in 49 cities with COVID-19 outbreaks between January 2020 and June 2022. Epidemiological data on COVID-19 were extracted from the National Health Commission, People's Republic of China, and the population flow data were sourced from the Baidu migration data provided by the Baidu platform. Outbreak control was quantified by calculating the degree of infection growth and the time-varying reproduction number ([Formula: see text]). The intensity of the outbreak response was quantified by calculating the reduction in population mobility during the outbreak period. Correlation and regression analyses of the intensity of the control measures and the degree of outbreak control for the Omicron variant and non-Omicron mutants were conducted, respectively. RESULTS: Overall, 65 outbreaks occurred in 49 cities in China from January 2020 to June 2022. Of them, 66.2% were Omicron outbreaks and 33.8% were non-Omicron outbreaks. The intensity of the control measures was positively correlated with the degree of outbreak control (r = 0.351, P = 0.03). The degree of reduction in population mobility was negatively correlated with the Rt value (r = - 0.612, P < 0.01). Therefore, under the same control measure intensity, the number of new daily Omicron infections was 6.04 times higher than those attributed to non-Omicron variants, and the Rt value of Omicron outbreaks was 2.6 times higher than that of non-Omicron variants. In addition, the duration of non-Omicron variant outbreaks was shorter than that of the outbreaks caused by the Omicron variant (23.0 ± 10.7, 32.9 ± 16.3, t = 2.243, P = 0.031). CONCLUSIONS: Greater intensity of control measures was associated with more effective outbreak control. Thus, in response to the Omicron variant, the management to restrict population movement should be used to control its spread quickly, especially in the case of community transmission occurs widely. Faster than is needed for non-Omicron variants, and decisive control measures should be imposed and dynamically adjusted in accordance with the evolving epidemic situation.

Applying the Student Response System in the Online Dermatologic Video Curriculum on Medical Students' Interaction and Learning Outcomes during the COVID-19 Pandemic.

Background: The coronavirus disease 2019 (COVID-19) pandemic impacted medical education worldwide. Online lecture is increasingly prevalent in higher education, but students' completion rate is quite low. Aims: This study aimed to determine the effectiveness of the student response system (SRS) in the online dermatologic video curriculum on medical students. Methods: A prospective study was conducted on 176 undergraduate fourth-year medical students. The online video lecture was integrated with SRS. Results: A total of 173 students completed the pre-test, and the attendance rate (pre-test/total) was 98.3%. A total of 142 students completed the post-test, and the completion rate (post-test/pre-test) was 82.8%. The post-test score (83.69 ± 4.34) was found to be significantly higher than that of the pre-test (62.69 ± 6.08, P =0.0002). A total of 138 students completed the questionnaire, and 92% of students opined that SRS was easy to operate. 86% of students agreed with the fact that the use of SRS could increase their learning performance by interacting with teachers. In the open-ended question, students stated that SRS offered opportunities for student-faculty interaction, allowed them to get immediate feedback, and promote active participation. Conclusions: These results highlight that the integration of SRS in the online video curriculum increases students' completion rates and learning outcomes. Moreover, the SRS is easy to operate for the students and enhances student-faculty interaction. The SRS may be adopted in online learning during this challenging time.

Changes in the types of patients in Burn Unit: A single center experience

Background Burns are a common concern around the world, with the majority of cases happening in low- and middle-income nations. China is the largest developing country. With the unremitting efforts of domestic colleagues, China has taken the lead in the treatment of burn in the world. With the change of times, we have observed some noteworthy changes in the types of patients that have admitted our Burns and Plastic Surgery, the Affiliated Hospital of Yangzhou University. Methods This retrospective observational study included brought into;all patients reached to our burn unit during 2013-2021. The gathered data were descriptively examined and statistically contrasted with each other year. Results Of 4407 cases admitted to burn unit during 2013-2021, men constituted 56% of such cases, with an average age of 47.3 ± 19.3 years. Moreover, among the patients hospitalized, January and February usually admit fewer than other months. Between 2013 and 2021, both the number of patients admitted to burn unit and the expense of their hospitalization rose yearly. The percentage of burn patients admitted to burn ward of our hospital is decreasing, especially during the period of serious Coronavirus disease (COVID-19) epidemic. We also observed that during the COVID-19 pandemic, patients with superficial masses also dropped off a cliff because of government controls. Conclusion The diseases in the department show the trend of maximizing marginal disciplines, burn surgeons are facing a more complex challenge. Further research addressing the relationship between the change of patient types and economic and social development in burn department will help to foster better pinpoint hospitalization patients need, fine service for hospitalized patients.

DRPADC: A novel drug repositioning algorithm predicting adaptive drugs for COVID-19.

Given that the usual process of developing a new vaccine or drug for COVID-19 demands significant time and funds, drug repositioning has emerged as a promising therapeutic strategy. We propose a method named DRPADC to predict novel drug-disease associations effectively from the original sparse drug-disease association adjacency matrix. Specifically, DRPADC processes the original association matrix with the WKNKN algorithm to reduce its sparsity. Furthermore, multiple types of similarity information are fused by a CKA-MKL algorithm. Finally, a compressed sensing algorithm is used to predict the potential drug-disease (virus) association scores. Experimental results show that DRPADC has superior performance than several competitive methods in terms of AUC values and case studies. DRPADC achieved the AUC value of 0.941, 0.955 and 0.876 in Fdataset, Cdataset and HDVD dataset, respectively. In addition, the conducted case studies of COVID-19 show that DRPADC can predict drug candidates accurately.

Modelling COVID-19 outbreak on the Diamond Princess ship using the public surveillance data.

The novel coronavirus disease 2019 (COVID-19) outbreak on the Diamond Princess (DP) ship has caused over 634 cases as of February 20, 2020. We model the transmission process on DP ship as a stochastic branching process, and estimate the reproduction number at the innitial phase of 2.9 (95%CrI: 1.7-7.7). The epidemic doubling time is 3.4 days, and thus timely actions on COVID-19 control were crucial. We estimate the COVID-19 transmissibility reduced 34% after the quarantine program on the DP ship which was implemented on February 5. According to the model simulation, relocating the population at risk may sustainably decrease the epidemic size, postpone the timing of epidemic peak, and thus relieve the tensive demands in the healthcare. The lesson learnt on the ship should be considered in other similar settings.

Two waves of COIVD-19 in Brazilian cities and vaccination impact.

BACKGROUNDS: Brazil has suffered two waves of Coronavirus Disease 2019 (COVID-19). The second wave, coinciding with the spread of the Gamma variant, was more severe than the first wave. Studies have not yet reached a conclusion on some issues including the extent of reinfection, the infection fatality rate (IFR), the infection attack rate (IAR) and the effects of the vaccination campaign in Brazil, though it was reported that confirmed reinfection was at a low level. METHODS: We modify the classical Susceptible-Exposed-Infectious-Recovered (SEIR) model with additional class for severe cases, vaccination and time-varying transmission rates. We fit the model to the severe acute respiratory infection (SARI) deaths, which is a proxy of the COVID-19 deaths, in 20 Brazilian cities with the large number of death tolls. We evaluate the vaccination effect by a contrast of "with" vaccination actual scenario and "without" vaccination in a counterfactual scenario. We evaluate the model performance when the reinfection is absent in the model. RESULTS: In the 20 Brazilian cities, the model simulated death matched the reported deaths reasonably well. The effect of the vaccination varies across cities. The estimated median IFR is around 1.2%. CONCLUSION: Overall, through this modeling exercise, we conclude that the effects of vaccination campaigns vary across cites and the reinfection is not crucial for the second wave. The relatively high IFR could be due to the breakdown of medical system in many cities.

Large-scale synchronized replacement of Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2 in the COVID-19 pandemic.

In this work, we report a large-scale synchronized replacement pattern of the Alpha (B.1.1.7) variant by the Delta (B.1.617.2) variant of SARS-COV-2. We argue that this phenomenon is associated with the invasion timing and the transmissibility advantage of the Delta (B.1.617.2) variant. Alpha (B.1.1.7) variant skipped some countries/regions, e.g. India and neighboring countries/regions, which could have led to a mild first wave before the invasion of the Delta (B.1.617.2) variant, in term of reported COVID-deaths per capita.

The Heterogeneous Severity of COVID-19 in African Countries: A Modeling Approach.

The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number ([Formula: see text]) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher [Formula: see text] and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).

Potent prophylactic and therapeutic efficacy of recombinant human ACE2-Fc against SARS-CoV-2 infection in vivo.

The current COVID-19 pandemic, caused by SARS-CoV-2, poses a serious public health threat. Effective therapeutic and prophylactic treatments are urgently needed. Angiotensin-converting enzyme 2 (ACE2) is a functional receptor for SARS-CoV-2, which binds to the receptor binding domain (RBD) of SARS-CoV-2 spike protein. Here, we developed recombinant human ACE2-Fc fusion protein (hACE2-Fc) and a hACE2-Fc mutant with reduced catalytic activity. hACE2-Fc and the hACE2-Fc mutant both efficiently blocked entry of SARS-CoV-2, SARS-CoV, and HCoV-NL63 into hACE2-expressing cells and inhibited SARS-CoV-2 S protein-mediated cell-cell fusion. hACE2-Fc also neutralized various SARS-CoV-2 strains with enhanced infectivity including D614G and V367F mutations, as well as the emerging SARS-CoV-2 variants, B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.1 (Kappa), and B.1.617.2 (Delta), demonstrating its potent and broad-spectrum antiviral effects. In addition, hACE2-Fc proteins protected HBE from SARS-CoV-2 infection. Unlike RBD-targeting neutralizing antibodies, hACE2-Fc treatment did not induce the development of escape mutants. Furthermore, both prophylactic and therapeutic hACE2-Fc treatments effectively protected mice from SARS-CoV-2 infection, as determined by reduced viral replication, weight loss, histological changes, and inflammation in the lungs. The protection provided by hACE2 showed obvious dose-dependent efficacy in vivo. Pharmacokinetic data indicated that hACE2-Fc has a relative long half-life in vivo compared to soluble ACE2, which makes it an excellent candidate for prophylaxis and therapy for COVID-19 as well as for SARS-CoV and HCoV-NL63 infections.

Shrinkage in serial intervals across transmission generations of COVID-19.

One of the key epidemiological characteristics that shape the transmission of coronavirus disease 2019 (COVID-19) is the serial interval (SI). Although SI is commonly considered following a probability distribution at a population scale, recent studies reported a slight shrinkage (or contraction) of the mean of effective SI across transmission generations or over time. Here, we develop a likelihood-based statistical inference framework with truncation to explore the change in SI across transmission generations after adjusting the impacts of case isolation. The COVID-19 contact tracing surveillance data in Hong Kong are used for exemplification. We find that for COVID-19, the mean of individual SI is likely to shrink with a factor at 0.72 per generation (95%CI: 0.54, 0.96) as the transmission generation increases, where a threshold may exist as the lower boundary of this shrinking process. We speculate that one of the probable explanations for the shrinkage in SI might be an outcome due to the competition among multiple candidate infectors within the same case cluster. Thus, the nonpharmaceutical interventive strategies are crucially important to block the transmission chains, and mitigate the COVID-19 epidemic.

Negative Emotion Arousal and Altruism Promoting of Online Public Stigmatization on COVID-19 Pandemic.

The outbreak of COVID-19 is a public health crisis that has had a profound impact on society. Stigma is a common phenomenon in the prevalence and spread of infectious diseases. In the crisis caused by the pandemic, widespread public stigma has influenced social groups. This study explores the negative emotions arousal effect from online public stigmatization during the COVID-19 pandemic and the impact on social cooperation. We constructed a model based on the literature and tested it on a sample of 313 participants from the group being stigmatized. The results demonstrate: (1) relevance and stigma perception promote negative emotions, including anxiety, anger, and grief; (2) the arousal of anger and grief leads to a rise in the altruistic tendency within the stigmatized group; and (3) stigmatization-induced negative emotions have a complete mediating effect between perceived relevance and altruistic tendency, as well as perceived stigma and altruistic tendency. For a country and nation, external stigma will promote the group becoming more united and mutual help. One wish to pass the buck but end up helping others unintentionally. We should not simply blame others, including countries, regions, and groups under the outbreak of COVID-19, and everyone should be cautious with the words and actions in the Internet public sphere.

Estimating the time interval between transmission generations and the presymptomatic period by contact tracing surveillance data from 31 provinces in the mainland of China

The global pandemic of 2019 coronavirus disease (COVID-19) is a great assault to public health. Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons, such as isolation. This study aimed to estimate the interval of the transmission generation (TG) and the presymptomatic period of COVID-19, and compare the fitting effects of TG and serial interval (SI) based on the SEIHR model incorporating the surveillance data of 3453 cases in 31 provinces. These data were allocated into three distributions and the value of AIC presented that the Weibull distribution fitted well. The mean of TG was 5.2 days (95% CI: 4.6-5.8). The mean of the presymptomatic period was 2.4 days (95% CI: 1.5-3.2). The dynamic model using TG as the generation time performed well. Eight provinces exhibited a basic reproduction number from 2.16 to 3.14. Measures should be taken to control presymptomatic transmission in the COVID-19 pandemic.

Factors associated with psychological distress among patients with breast cancer during the COVID-19 pandemic: a cross-sectional study in Wuhan, China.

PURPOSE: This study aimed to examine the prevalence of psychological distress and the corresponding risk factors among patients with breast cancer affected by the outbreak of coronavirus disease 2019 (COVID-19). METHODS: This cross-sectional, survey-based, region-stratified study was conducted from March 14 to March 21, 2020. An online survey was used to collect the basic characteristics of patients with breast cancer. The degree of depression, anxiety, and insomnia symptoms were assessed using the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder (GAD-7), and the Insomnia Severity Index (ISI) questionnaires, respectively. Multivariate logistic analysis was performed to identify factors associated with psychological distress outcomes. RESULTS: Among the 834 patients with breast cancer included in the study, the prevalence of depression, anxiety, and insomnia was 21.6%, 15.5%, and 14.7%, respectively. No statistically significant difference in the prevalence of these symptoms was observed between patients in Wuhan and those outside Wuhan. Multivariate logistic regression analyses revealed that comorbidity, living alone, deterioration of breast cancer, and affected treatment plan were risk factors for psychological distress including depression, anxiety, and insomnia. When stratified by location, living alone was associated with depression and insomnia only among patients in Wuhan, but not those outside Wuhan. CONCLUSIONS: This study shows an elevated prevalence of depression, anxiety, and insomnia among patients with breast cancer during part of the COVID-19 pandemic. Patients with comorbidity, living alone, deterioration of breast cancer, and whose treatment plan was affected should be paid more attention to prevent mental disorders.

Quantifying the improvement in confirmation efficiency of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the early phase of outbreak in Hong Kong in 2020

BACKGROUNDS: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of coronavirus disease COVID-19 in Wuhan, China since December 2019. The COVID-19 soon spread to other regions of China and overseas. In Hong Kong, local mitigation measures have been implemented since the first imported case was confirmed on January 23, 2020. Here we evaluated the temporal variation of detection delay from symptoms onset to laboratory confirmation of SARS-CoV-2 in Hong Kong. METHODS: A regression model is adopted to quantify the association between the SARS-CoV-2 detection delay and the calendar time. The association is tested and further validated by a Cox proportional hazard model. FINDINGS: The estimated median detection delay was 9.5 days (95%CI: 6.5-11.5) in the second half of January, and reduced to 6.0 days (95%CI: 5.5-9.5) in the first half of February 2020. We estimate that the SARS-CoV-2 detection efficiency improves at a daily rate of 5.40% (95%CI: 2.54-8.33) in Hong Kong. CONCLUSION: The detection efficiency of SARS-CoV-2 was likely being improved substantially in Hong Kong since the first imported case was detected. The sustaining enforcement in timely detection and other effective control measures are recommended to prevent the SARS-CoV-2 infection.

A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action.

The ongoing coronavirus disease 2019 (COVID-19) outbreak, emerged in Wuhan, China in the end of 2019, has claimed more than 2600 lives as of 24 February 2020 and posed a huge threat to global public health. The Chinese government has implemented control measures including setting up special hospitals and travel restriction to mitigate the spread. We propose conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions, e.g., holiday extension, travel restriction, hospitalisation and quarantine. We employe the estimates of these two key components from the 1918 influenza pandemic in London, United Kingdom, incorporated zoonotic introductions and the emigration, and then compute future trends and the reporting ratio. The model is concise in structure, and it successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak.