Parental Seasonal Influenza Vaccine Hesitancy and Associated Factors in Shanghai, China, during the COVID-19 Pandemic: A Cross-Sectional Study.

BACKGROUND: Seasonal influenza may overlap with the COVID-19 pandemic, and children are one of the priority populations for influenza vaccination in China, yet vaccine coverage has been low. This study aimed to investigate the extent of parental influenza vaccine hesitancy (IVH) and to explore the associated factors. METHODS: The study was conducted in Shanghai, China, from 1 June 2022 to 31 July 2022, using an anonymous questionnaire to survey a random sample of parents of children aged six months to 14 years. Binary logistic regression models were used to identify factors associated with IVH. RESULTS: Of the 5016 parents, 34.05% had IVH. Multivariate analysis showed that after adjustment for non-modifiable markers (i.e., sociodemographic, health status, and past vaccination status), being affected by negative influenza vaccine news and having higher "complacency" were positively associated with parental IVH. Higher knowledge of influenza vaccination, being recommended by healthcare workers (HCWs), people around having a positive attitude toward influenza vaccine and having higher levels of "confidence" and "convenience" were negatively associated with parental IVH. CONCLUSIONS: In China, public health education aimed at modifying vaccination-related attitudes and beliefs, as well as knowledge and societal influences, could help reduce influenza vaccination hesitancy.

CapsCovNet: A Modified Capsule Network to Diagnose COVID-19 From Multimodal Medical Imaging.

Since the end of 2019, novel coronavirus disease (COVID-19) has brought about a plethora of unforeseen changes to the world as we know it. Despite our ceaseless fight against it, COVID-19 has claimed millions of lives, and the death toll exacerbated due to its extremely contagious and fast-spreading nature. To control the spread of this highly contagious disease, a rapid and accurate diagnosis can play a very crucial part. Motivated by this context, a parallelly concatenated convolutional block-based capsule network is proposed in this article as an efficient tool to diagnose the COVID-19 patients from multimodal medical images. Concatenation of deep convolutional blocks of different filter sizes allows us to integrate discriminative spatial features by simultaneously changing the receptive field and enhances the scalability of the model. Moreover, concatenation of capsule layers strengthens the model to learn more complex representation by presenting the information in a fine to coarser manner. The proposed model is evaluated on three benchmark datasets, in which two of them are chest radiograph datasets and the rest is an ultrasound imaging dataset. The architecture that we have proposed through extensive analysis and reasoning achieved outstanding performance in COVID-19 detection task, which signifies the potentiality of the proposed model.

Infectivity rate of COVID-19 following close contact with COVID-19 cases in Quzhou

Objective: To determine the infectivity rate following close contact with confirmed COVID-19 cases in Quzhou from January to September 2020, and to provide reference for pandemic control and prevention.

Expert Consensus on Clinical Practice of Burn Units in Shanghai During the COVID-19 Epidemic.

In response to coronavirus disease 2019 (COVID-19), the Shanghai Burn Clinical Quality Control Center organized experts to formulate and implement a set of rapid, simple, and effective prevention and control measures, and there have not been any cases of health care professionals or inpatients in burn units suspected or confirmed with COVID-19. This article elaborates on the specific measures in burn units in response to the epidemic, including the implementation of standardized procedures, remote consultations, strengthened follow-up, exchange of experience, and popular science, among others. We share experience from Shanghai to benefit related disciplines in other countries and regions.

The effectiveness of active surveillance measures for COVID-19 cases in Pudong New Area Shanghai, China, 2020.

The aim of this study was to thoroughly document the effects of multiple intervention and control methods to mitigate the ongoing coronavirus disease 2019 (COVID-19) outbreak in Pudong New Area, Shanghai. After identification of the first confirmed case of COVID-19 in Pudong on January 21, 2020, the local Center for Disease Control and Prevention (CDC) launched a case investigation involving isolation, close-contact (CC) tracing and quarantine of persons with a potential exposure risk to prevent and control transmission. Epidemiological features of cases detected by three different strategies were compared to assess the impact of these active surveillance measures. As of February 16, 2020, a total of 108 confirmed COVID-19 cases had been identified in Pudong, Shanghai. Forty-five (41.67%) cases were identified through active surveillance measures, with 22 (20.37%) identified by CC tracing and 23 (21.30%) by quarantine of potential exposure populations (PEPs). The average interval from illness onset to the first medical visit was 1 day. Cases identified by CC tracing and PEPs were quarantined for 0.5 and 1 day before illness onset, respectively. The time intervals from illness onset to the first medical visit and isolation among actively screened cases were 2 days (p = .02) and 3 days (p = .00) shorter, respectively, than those among self-admission cases. Our study highlights the importance of active surveillance for potential COVID-19 cases, as demonstrated by shortened time intervals from illness onset to both the first medical visit and isolation. These measures contributed to the effective control of the COVID-19 outbreak in Pudong, Shanghai.