Vaccines for COVID-19 are anticipated to be available by 2021. Vaccine uptake rate is a crucial determinant for herd immunity. We examined factors associated with acceptance of vaccine based on (1). constructs of the Health Belief Model (HBM), (2). trust in the healthcare system, new vaccine platforms and manufacturers, and (3). self-reported health outcomes. A population-based, random telephone survey was performed during the peak of the third wave of COVID-19 outbreak (27/07/2020 to 27/08/2020) in Hong Kong. All adults aged ≥ 18 years were eligible. The survey included sociodemographic details; self-report health conditions; trust scales; and self-reported health outcomes. Multivariable regression analyses were applied to examine independent associations. The primary outcome is the acceptance of the COVID-19 vaccine. We conducted 1200 successful telephone interviews (response rate 55%). The overall vaccine acceptance rate after adjustment for population distribution was 37.2% (95% C.I. 34.5–39.9%). The projected acceptance rates exhibited a “J-shaped” pattern with age, with higher rates among young adults (18–24 years), then increased linearly with age. Multivariable regression analyses revealed that perceived severity, perceived benefits of the vaccine, cues to action, self-reported health outcomes, and trust in healthcare system or vaccine manufacturers were positive correlates of acceptance; whilst perceived access barriers and harm were negative correlates. Remarkably, perceived susceptibility to infection carried no significant association, whereas recommendation from Government (aOR = 10.2, 95% C.I. 6.54 to 15.9, p < 0.001) was as the strongest driving factor for acceptance. Other key obstacles of acceptance included lack of confidence on newer vaccine platforms (43.4%) and manufacturers without track record (52.2%), which are of particular relevance to the current context. Governmental recommendation is an important driver, whereas perceived susceptibility is not associated with acceptance of COVID-19 vaccine. These HBM constructs and independent predictors inform evidence-based formulation and implementation of vaccination strategies.

Trisomy 21 is the most common reason that women opt for prenatal diagnosis. Conventional prenatal diagnostic methods involve the sampling of fetal materials by invasive procedures such as amniocentesis. Screening by ultrasonography and biochemical markers have been used to risk-stratify pregnant women before definitive invasive diagnostic procedures. However, these screening methods generally target epiphenomena, such as nuchal translucency, associated with trisomy 21. It would be ideal if noninvasive genetic methods were available for the direct detection of the core pathology of trisomy 21. Here we outline an approach using digital PCR for the noninvasive detection of fetal trisomy 21 by analysis of fetal nucleic acids in maternal plasma. First, we demonstrate the use of digital PCR to determine the allelic imbalance of a SNP on PLAC4 mRNA, a placenta-expressed transcript on chromosome 21, in the maternal plasma of women bearing trisomy 21 fetuses. We named this the digital RNA SNP strategy. Second, we developed a nonpolymorphism-based method for the noninvasive prenatal detection of trisomy 21. We named this the digital relative chromosome dosage (RCD) method. Digital RCD involves the direct assessment of whether the total copy number of chromosome 21 in a sample containing fetal DNA is overrepresented with respect to a reference chromosome. Even without elaborate instrumentation, digital RCD allows the detection of trisomy 21 in samples containing 25% fetal DNA. We applied the sequential probability ratio test to interpret the digital PCR data. Computer simulation and empirical validation confirmed the high accuracy of the disease classification algorithm.

We introduce Motion-I2V, a novel framework for consistent and controllable text-guided image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated image-to-video mapping, Motion-I2V factorizes I2V into two stages with explicit motion modeling. For the first stage, we propose a diffusion-based motion field predictor, which focuses on deducing the trajectories of the reference image’s pixels. For the second stage, we propose motion-augmented temporal attention to enhance the limited 1-D temporal attention in video latent diffusion models. This module can effectively propagate reference image features to synthesized frames with the guidance of predicted trajectories from the first stage. Compared with existing methods, Motion-I2V can generate more consistent videos even in the presence of large motion and viewpoint variation. By training a sparse trajectory ControlNet for the first stage, Motion-I2V can support users to precisely control motion trajectories and motion regions with sparse trajectory and region. This offers more controllability of the I2V process than solely relying on textual instructions. Additionally, Motion-I2V’s second stage naturally supports zero-shot video-to-video translation. Both qualitative and quantitative comparisons demonstrate the advantages of Motion-I2V over prior approaches in consistent and controllable image-to-video generation. Please see our project page at https://xiaoyushi97.github.io/Motion-I2V/.

There is little evidence to suggest that older people today are living in better health than their predecessors did at the same age. Only a few studies have evaluated whether there are birth cohort effects on frailty, an indicator of health in older people, encompassing physical, functional and mental health dimensions. this study examined longitudinal trajectories of frailty among Chinese older people in Hong Kong. this study utilised data from the 18 Elderly Health Centres of the Department of Health comprising a total of 417,949 observations from 94,550 community-dwelling Chinese people aged ≥65 years in one early birth cohort (1901–23) and four later birth cohorts (1924–29, 1930–35, 1936–41, 1942–47) collected between 2001 and 2012, to examine trajectories of the frailty index and how birth cohorts may have contributed to the trends using an age-period-cohort analysis. more recent cohorts had higher levels of frailty than did earlier cohorts at the same age, controlling for period, gender, marital status, educational levels, socioeconomic status, lifestyle and social factors. Older age, being female, widowhood, lower education and smoking were associated with higher levels of frailty. more recent cohorts had higher levels of frailty than did earlier cohorts. Frailty interventions, coupled with early detection, should be developed to combat the increasing rates of frailty in Hong Kong Chinese.