Weighted gene co-expression network-based identification of genetic effect of mRNA vaccination and previous infection on SARS-CoV-2 infection.

To investigate the effect conferred by vaccination and previous infection against SARS-CoV-2 infection in molecular level, weighted gene co-expression network analysis was applied to screen vaccination, prior infection and Omicron infection-related gene modules in 46 Omicron outpatients and 8 controls, and CIBERSORT algorithm was used to infer the proportions of 22 subsets of immune cells. 15 modules were identified, where the brown module showed positive correlations with Omicron infection (r = 0.35, P = 0.01) and vaccination (r = 0.62, P = 1 × 10-6). Enrichment analysis revealed that LILRB2 was the unique gene shared by both phosphatase binding and MHC class I protein binding. Pathways including "B cell receptor signaling pathway" and "FcγR-mediated phagocytosis" were enriched in the vaccinated samples of the highly correlated LILRB2. LILRB2 was also identified as the second hub gene through PPI network, after LCP2. In conclusion, attenuated LILRB2 transcription in PBMC might highlight a novel target in overcoming immune evasion and improving vaccination strategies.

A panel regression analysis for the COVID-19 epidemic in the United States.

This study explored the roles of epidemic-spread-related behaviors, vaccination status and weather factors during the COVID-19 epidemic in 50 U.S. states since March 2020. Data from March 1, 2020 to February 5, 2022 were incorporated into panel model. The states were clustered by the k-means method. In addition to discussing the whole time period, we also took multiple events nodes into account and analyzed the data in different time periods respectively by panel linear regression method. In addition, influence of cluster grouping and different incubation periods were been discussed. Non-segmented analysis showed the rate of people staying at home and the vaccination dose per capita were significantly negatively correlated with the daily incidence rate, while the number of long-distance trips was positively correlated. Weather indicators also had a negative effect to a certain extent. Most segmental results support the above view. The vaccination dose per capita was unsurprisingly proved to be the most significant factor especially for epidemic dominated by Omicron strains. 7-day was a more robust incubation period with the best model fit while weather had different effects on the epidemic spread in different time period. The implementation of prevention behaviors and the promotion of vaccination may have a successful control effect on COVID-19, including variants' epidemic such as Omicron. The spread of COVID-19 also might be associated with weather, albeit to a lesser extent.

Prevalence and correlates of psychological distress in the front-line anti-epidemic medical staff during the COVID-19 outbreak in Wuhan.

BACKGROUND: Since the outbreak of the novel coronavirus disease 2019 (COVID-19), medical staff and affiliated healthcare staff are under both physical and psychological pressures. Due to this serious situation, it is extremely important to assess the prevalence and possible predictors of psychological distress in front-line, anti-epidemic medical staff. METHODS: A cross-sectional study was conducted through the use of the network crowdsourcing platform (which provides functions equivalent to Amazon Mechanical Turk) in Jilin, China. A total of 725 Jilin medical staff who had returned from Wuhan participated in the survey. The collected data included demographics and psychological responses to COVID-19, and the following tests were used to measure the data: (I) the Social Support Rate Scale (SSRS) was used to measure the types and levels of social support that were received by the medical staff; (II) the Stanford Acute Stress Reaction Questionnaire (SASRQ) was used to evaluate anxiety and dissociation symptoms in the aftermath of traumatic events; (III) the Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality; and (IV) the Kessler Psychological Distress Scale (K10) was used to evaluate nonspecific psychological distress. The χ2 test, Kruskal-Wallis test, ANOVA test and binary logistic regression were used to identify the factors that were correlated with psychological distress. RESULTS: In our study, 475 (65.5%) participants reported low psychological distress, and 72 (10%) participants reported high psychological distress. The results of the binary logistic regression analysis identified that the performance of physical activity in Wuhan (ß=-0.585; P<0.001; OR =0.557) and years of work experience (in contrast to approximately 0-5 years, approximately 6-15 years: ß=-1.258; P=0.008; OR =0.284, >15 years: ß=-0.562; P=0.016; OR =0.570) were protective factors for the possibility of having a mental disorder, whereas a high PSQI score (ß=0.106; P=0.024; OR =1.112) and a high SASRQ score (ß=0.242; P<0.001; OR =1.274) were risk factors. CONCLUSIONS: The high psychological distress (10%) of Jilin medical staff who returned from the front-line areas of Wuhan was higher than that in other studies. Medical staff with less physical activity and work experience in Wuhan, as well as high PSQI and SASRQ scores, had higher psychological distress.

Epidemiological study on severe acute respiratory syndrome coronavirus 2 virus transmission network in northeast China.

ABSTRACT: In this study, corona virus disease 2019 (COVID-19) transmission networks were built to analyze the epidemic situation of COVID-19 in Liaoning and Jilin provinces in early 2020. We explore the characteristics of the spread of COVID-19, and put forward effective recommendations for epidemic prevention and control. We collected demographic characteristics, exposure history, and course of action of COVID-19 cases. We described the demographic and case characteristics of these cases to show the basic characteristics of COVID-19 cases in both provinces. Combined with the spatial analysis of confirmed cases, the distribution law of the number of confirmed cases in different regions was analyzed. We exhibit the relationship among COVID-19 cases with a transmission network. The transmission characteristics of COVID-19 were analyzed through the transmission network. Mainly cases in Liaoning and Jilin provinces were imported cases from other provinces and the vast majority of these cases were related to Hubei province. The number of confirmed cases in different regions was positively correlated with their GDP and population. The main clinical symptoms of the cases were fever. Judge from the transmission network relationship between the 2 provinces, the transmission chain in Liaoning province contains fewer cases than that in Jilin province. The main transmission routes of the local cases in the 2 provinces were the family members, and the infection of the imported cases were mainly occurred in public places. It was estimated that the unidentified asymptomatic infected cases in the 2 provinces account for approximately 7.3% of the total number of infected cases. The length of the transmission chain suggests that the spread of COVID-19 can be effectively controlled with effective prevention measures.