ImportanceIn 2022, Omicron variants circulated globally, and Urumqi, China, experienced a COVID-19 outbreak seeded by Omicron BA.5 variants, resulting in the highest number of infections in the city’s record before the exit of the zero COVID-19 strategy. Little was known about the characteristics of Omicron variants in mainland China.ObjectiveTo evaluate transmission characteristics of Omicron BA.5 variants and the effectiveness of inactivated vaccine (mainly BBIBP-CorV) against their transmission.Design, Setting, and ParticipantsThis cohort study was conducted using data from an Omicron-seeded COVID-19 outbreak in Urumqi from August 7 to September 7, 2022. Participants included all individuals with confirmed SARS-CoV-2 infections and their close contacts identified between August 7 and September 7, 2022 in Urumqi.ExposuresA booster dose was compared vs 2 doses (reference level) of inactivated vaccine and risk factors were evaluated.Main Outcomes and MeasuresDemographic characteristics, timeline records from exposure to laboratory testing outcomes, contact tracing history, and contact setting were obtained. The mean and variance of the key time-to-event intervals of transmission were estimated for individuals with known information. Transmission risks and contact patterns were assessed under different disease-control measures and in different contact settings. The effectiveness of inactivated vaccine against the transmission of Omicron BA.5 was estimated using multivariate logistic regression models.ResultsAmong 1139 individuals diagnosed with COVID-19 (630 females [55.3%]; mean [SD] age, 37.4 [19.9] years) and 51 323 close contacts who tested negative for COVID-19 (26 299 females [51.2%]; mean [SD] age, 38.4 [16.0] years), the means of generation interval, viral shedding period, and incubation period were estimated at 2.8 days (95% credible interval [CrI], 2.4-3.5 days), 6.7 days (95% CrI, 6.4-7.1 days), and 5.7 days (95% CrI, 4.8-6.6 days), respectively. Despite contact tracing, intensive control measures, and high vaccine coverage (980 individuals with infections [86.0%] received ≥2 doses of vaccine), high transmission risks were found in household settings (secondary attack rate, 14.7%; 95% CrI, 13.0%-16.5%) and younger (aged 0-15 years; secondary attack rate, 2.5%; 95% CrI, 1.9%-3.1%) and older age (aged >65 years; secondary attack rate, 2.2%; 95% CrI, 1.5%-3.0%) groups. Vaccine effectiveness against BA.5 variant transmission for the booster-dose vs 2 doses was 28.9% (95% CrI, 7.7%-45.2%) and 48.5% (95% CrI, 23.9%-61.4%) for 15-90 days after booster dose. No protective outcome was detected beyond 90 days after the booster dose.Conclusions and RelevanceThis cohort study revealed key transmission characteristics of SARS-CoV-2 as they evolved, as well as vaccine effectiveness against variants. These findings suggest the importance of continuously evaluating vaccine effectiveness against emerging SARS-CoV-2 variants.

1.1. Background: Recently, typical CT features of coronavirus disease (COVID-19) pneumonia have been reported. However, the prognostic value of CT evaluations has not been fully elucidated. Methods:In this retrospective, multi-center cohort study, we reviewed 645 patients who had died or recovered from laboratory-confirmed COVID-19 between January 23, 2020 and March 6, 2020 in two hospitals in Wuhan and Shenyang, China. Demographic, clinical, laboratory, and CT data were extracted and compared between the non-survivor and survivor group. Multivariable logistic regression analysis identified risk factors for in-hospital death. Results:This study enrolled 253 patients (63 died in the hospital, 190 were discharged). Compared to survivors, non-survivors were older, mostly male, had a higher prevalence of preexisting comorbidity, higher incidences of hypoxemia, lymphopenia and bacterial coinfection (p<0.001 for each). Regarding CT evaluations, non-survivors had higher CT scores (14.3±3.4 vs. 8.1±2.9), higher incidences of bronchial dilation with mosaic (34.9% vs. 10.5%), emphysema (28.6% vs. 10.5%), and diffuse opacity distribution (76.1% vs. 36.8%; all p<0.001). Multivariable regression analysis showed that increasing odds of in-hospital death were associated with preexisting comorbidity (OR=12.48, 95% CI: 1.48-105.07; p=0.020), lower peripheral capillary oxygen saturation (per 1% increase OR=0.681, 95%CI: 0.50-0.93; p=0.016), bacterial coin-Volume 2 | Issue 7 ajsccr.org 2 fection (OR=10.73, 95%CI: 1.01-114.01; p=0.049), and higher CT involvement scores (per 0.5-point increase OR=1.41, 95%CI: 1.04-1.91; p=0.028). Conclusion:The CT involvement score is a potential predictor of short-term outcomes in patients with COVID-19. A thorough assessment combining CT evaluation with demographic and clinical information may help establish risk stratifications and optimize treatment decisions at an early stage.

<abstract> <p>Knowledge of viral shedding remains limited. Repeated measurement data have been rarely used to explore the influencing factors. In this study, a joint model was developed to explore and validate the factors influencing the duration of viral shedding based on longitudinal data and survival data. We divided 361 patients infected with Delta variant hospitalized in Nanjing Second Hospital into two groups (≤ 21 days group and &gt; 21 days group) according to the duration of viral shedding, and compared their baseline characteristics. Correlation analysis was performed to identify the factors influencing the duration of viral shedding. Further, a joint model was established based on longitudinal data and survival data, and the Markov chain Monte Carlo algorithm was used to explain the influencing factors. In correlation analysis, patients having received vaccination had a higher antibody level at admission than unvaccinated patients, and with the increase of antibody level, the duration of viral shedding shortened. The linear mixed-effects model showed the longitudinal variation of logSARS-COV-2 IgM sample/cutoff (S/CO) values, with a parameter estimate of 0.193 and a standard error of 0.017. Considering gender as an influencing factor, the parameter estimate of the Cox model and their standard error were 0.205 and 0.1093 (P = 0.608), the corresponding OR value was 1.228. The joint model output showed that SARS-COV-2 IgM (S/CO) level was strongly associated with the risk of a composite event at the 95% confidence level, and a doubling of SARS-COV-2 IgM (S/CO) level was associated with a 1.38-fold (95% CI: [1.16, 1.72]) increase in the risk of viral non-shedding. A higher antibody level in vaccinated patients, as well as the presence of IgM antibodies in serum, can accelerate shedding of the mutant virus. This study provides some evidence support for vaccine prevention and control of COVID-19 variants.</p> </abstract>

<abstract><p>When an outbreak of COVID-19 occurs, it will cause a shortage of medical resources and the surge of demand for hospital beds. Predicting the length of stay (LOS) of COVID-19 patients is helpful to the overall coordination of hospital management and improves the utilization rate of medical resources. The purpose of this paper is to predict LOS for patients with COVID-19, so as to provide hospital management with auxiliary decision-making of medical resource scheduling. We collected the data of 166 COVID-19 patients in a hospital in Xinjiang from July 19, 2020, to August 26, 2020, and carried out a retrospective study. The results showed that the median LOS was 17.0 days, and the average of LOS was 18.06 days. Demographic data and clinical indicators were included as predictive variables to construct a model for predicting the LOS using gradient boosted regression trees (GBRT). The MSE, MAE and MAPE of the model are 23.84, 4.12 and 0.76 respectively. The importance of all the variables involved in the prediction of the model was analyzed, and the clinical indexes creatine kinase-MB (CK-MB), C-reactive protein (CRP), creatine kinase (CK), white blood cell count (WBC) and the age of patients had a higher contribution to the LOS. We found our GBRT model can accurately predict the LOS of COVID-19 patients, which will provide good assistant decision-making for medical management.</p></abstract>

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.