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Jidi Zhao,1 Jianguo Jia,2 Ying Qian,3 Lumin Zhong,4 Jiancong Wang,5 Yuyang Cai4,6 1Faculty of Economics and Management, East China Normal University, Shanghai, People’s Republic of China; 2System Dynamics Chapter, Systems Engineering Society of China, Beijing, People’s Republic of China; 3School of Management, Shanghai University, Shanghai, People’s Republic of China; 4School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 5Institute of Global Health, University of Geneva, Geneva, Switzerland; 6China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaCorrespondence: Yuyang Cai; Ying Qian Email caiyuyang@sjtu.edu.cn; qian.ying@t.shu.edu.cnPurpose: It is unclear how and to what extent various infection prevention and control (IPC) policies affect the spread of an epidemic during work resumption. In order to assess the impact of IPC policies, this research addresses the results of a policy simulation in Shanghai, China, which estimates the transmission dynamics of COVID-19 under various IPC policies and offers evidence-based outcomes of work resumption policies for the world.Materials and Methods: This simulation research is based on a system dynamics (SD) model that integrates IPC work resumption policies implemented in Shanghai into the classical susceptible-exposed-infected-removed (SEIR) epidemiological model. Input data were obtained from official websites, the Baidu migration index and published literature. The SD model was validated by comparing results with real-world data.Results: The simulations show that a non-quarantined and non-staged approach to work resumption (Policy 1) would bring a small secondary outbreak of COVID-19. The quarantined but non-staged approach (Policy 2) and the non-quarantined but staged approach (Policy 3) would not bring a secondary outbreak of COVID-19. However, they both would generate more newly confirmed cases than the staged and quarantined approach (Policy 4). Moreover, the 14-day quarantine policy alone appears to be more effective in reducing transmission risk than the staged work resumption policy alone. The combined staged and quarantined IPC policy led to the fewest confirmed cases caused by work resumption in Shanghai, and the spread of COVID-19 stopped (ie, the number of newly confirmed cases reduced to zero) at the earliest date.Conclusion: Conservative IPC policies can prevent a second outbreak of COVID-19 during work resumption. The dynamic systems model designed in this study can serve as a tool to test various IPC work resumption policies, facilitating decision-making in responses to combating the COVID-19 pandemic.Keywords: IPC policies, work resumption, COVID-19, system dynamics, SEIR

Background: Emerging third-generation cephalosporin-resistant Enterobacteriaceae (3GCR-EB) pose global healthcare concern. This study assessed the in-hospital mortality attributed to 3GCR-EB. Methods: The study cohort comprised inpatients with community-onset or healthcare-associated infection caused by Enterobacteriaceae in three tertiary-care public hospitals in 2017. In-hospital mortality was compared between 3GCR-EB infected patients and third-generation cephalosporin-susceptible Enterobacteriaceae (3GCS-EB) infected patients using competing risk survival models. Results: Of 2,343 study patients (median age 60 years; 45.2% male), 1,481 (63.2%) had 3GCS-EB and 862 (36.8%) 3GCR-EB infection. 494 (57.0%) 3GCR-EB isolates were co-resistant to fluoroquinolones and 15 (1.7%) to carbapenems. In-hospital mortality was similar in 3GCS-EB and 3GCR-EB infections (2.4% vs. 2.8%; p = 0.601). No increase in the hazard of in-hospital mortality was detected for 3GCR-EB compared to 3GCS-EB infection (sub-distribution hazard ratio [HR] 0.80; 95%CI, 0.41���1.55) adjusting for patient age, sex, intensive care admission, origin of infection and site of infection. Analysis of cause-specific hazards showed that 3GCR-EB infections significantly decreased the daily rate of hospital discharge (cause-specific HR = 0.84; 95%CI, 0.76���0.92) leading to lengthier hospitalizations. Conclusion: 3GCR-EB infection per se was not associated with increased in-hospital mortality in this study, but placed significant healthcare burden by increasing the length of hospitalization.

Healthcare-associated infection (HAI) and antimicrobial resistance (AMR) are major public health threats. The aims of this research were to estimate HAI prevalence, AMR incidence, as well as to assess adoption and implementation of infection prevention and control (IPC) in Mainland China. In 2015, the pooled HAIs prevalence of all hospitals in Dongguan was 2.9%. Between 2006 and 2016, the weighted HAI prevalence in Mainland China, as identified in the systematic review, was 3.1%. Incidence proportion of AMR in Dongguan was lower than average incidence proportion in mainland China. Most of the ECDC key and WHO core components were reported to be implemented by acute care hospitals in China, but significant gaps in effective IPC were identified. This is the first multilevel research on HAI and AMR in the context of implementing key elements for effective IPC. These outcomes serve as a reference for future IPC strategies in Mainland China.

Background: Surgical site infection (SSI) is a serious complication after orthopedic surgery, and it is associated with high morbidity rates, high healthcare costs and in some cases poor patients outcomes. Aims: The purpose of this study was to identify the burden of SSI among orthopedic surgery and its associated risk factors of SSI among the people underwent spinal surgery in a selected hospital in China. Methods: From June 26 to November 30 in 2014, we performed a prospective surveillance study in the patients who underwent orthopedic surgery in a selected Chinese hospital. SSI was diagnosed based on the definition established by the Centers for Disease Control and Prevention (CDC) and was identified by bedside surveillance and post-discharge checkup. Detailed pre-, intra-, post-operative patient characteristics were prospectively recorded using a standardized data collection format. Results: A total of 287 orthopedic surgery cases, among them 192 cases of spinal surgery, were included, of which 8 cases developed surgical site infection. Wound contamination class, wound drains and blood transfusion were surgery-related risk factors for orthopedic spinal surgery during the hospital stay after bivariate analysis. Intravenous AMP was given in 176 of 287 (61.3%) after orthopedic surgery. The average duration of AMP administration was 2.2 days (range 1-9 days). Conclusion: In conclusion, we identified an incidence proportion of SSI after orthopedic surgery of 2.8%. The orthopedic SSI risk factors (wound contamination class, wound drains and blood transfusion) identified in present study may use to be reducing the incidence of SSI in the future.

Longitudinal assessment of brain atrophy, particularly in the hippocampus, is a well-studied biomarker for neurodegenerative diseases, such as Alzheimer's disease (AD). In clinical trials, estimation of brain progressive rates can be applied to track therapeutic efficacy of disease modifying treatments. However, most state-of-the-art measurements calculate changes directly by segmentation and/or deformable registration of MRI images, and may misreport head motion or MRI artifacts as neurodegeneration, impacting their accuracy. In our previous study, we developed a deep learning method DeepAtrophy that uses a convolutional neural network to quantify differences between longitudinal MRI scan pairs that are associated with time. DeepAtrophy has high accuracy in inferring temporal information from longitudinal MRI scans, such as temporal order or relative inter-scan interval. DeepAtrophy also provides an overall atrophy score that was shown to perform well as a potential biomarker of disease progression and treatment efficacy. However, DeepAtrophy is not interpretable, and it is unclear what changes in the MRI contribute to progression measurements. In this paper, we propose Regional Deep Atrophy (RDA), which combines the temporal inference approach from DeepAtrophy with a deformable registration neural network and attention mechanism that highlights regions in the MRI image where longitudinal changes are contributing to temporal inference. RDA has similar prediction accuracy as DeepAtrophy, but its additional interpretability makes it more acceptable for use in clinical settings, and may lead to more sensitive biomarkers for disease monitoring in clinical trials of early AD., Competing Interests: Declaration of Interest D.A.Wolk having received grants from Eli Lilly/Avid Radiopharmaceuticals, grants and personal fees from Merck, grants from Biogen, personal fees from Janssen, and personal fees from GE Healthcare; and L. Xie having received consulting fees from Galileo DSC, Inc. S.R. Das having received personal fees from Rancho Biosciences. None of the other authors has any financial relation to disclose.