ABSTRACT
BACKGROUND: To investigate the epidemiological characteristics and resistance changes of carbapenem-resistant organisms (CROs) under the COVID-19 outbreak to provide evidence for precise prevention and control measures against hospital-acquired infections during the pandemic. METHODS: The distribution characteristics of CROs (i.e., carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii) were analyzed by collecting the results of the antibiotic susceptibility tests of diagnostic isolates from all patients. Using interrupted time series analysis, we applied Poisson and linear segmented regression models to evaluate the effects of COVID-19 on the numbers and drug resistance of CROs. We also conducted a stratified analysis using the Cochran-Mantel-Haenszel test. RESULTS: The resistance rate of carbapenem-resistant Acinetobacter baumannii (CRAB) was 38.73% higher after the COVID-19 outbreak compared with before (p < 0.05). In addition, the long-term effect indicated that the prevalence of CRAB had a decreasing trend (p < 0.05). However, the overall resistance rate of Klebsiella pneumoniae did not significantly change after the COVID-19 outbreak. Stratified analysis revealed that the carbapenem-resistant Klebsiella pneumoniae (CRKP) rate increased in females (OR = 1.98, p < 0.05), those over 65 years old (OR = 1.49, p < 0.05), those with sputum samples (OR = 1.40, p < 0.05), and those in the neurology group (OR = 2.14, p < 0.05). CONCLUSION: The COVID-19 pandemic has affected the change in nosocomial infections and resistance rates in CROs, highlighting the need for hospitals to closely monitor CROs, especially in high-risk populations and clinical departments. It is possible that lower adherence to infection control in crowded wards and staffing shortages may have contributed to this trend during the COVID-19 pandemic, which warrants further research.
ABSTRACT
Low-cost and low-barrier antibiotic stewardship strategies are urgently needed to deal with the widespread problem of antibiotic resistance. Social norm feedback could be a promising strategy. In this mixed-methods systematic review (PROSPERO: CRD42022361039), we aimed to identify the key behaviour change techniques used in social norm feedback for antibiotic stewardship and assess their effectiveness in reducing antibiotic prescribing. We searched PubMed, Embase, Web of Science, and Scopus for peer-reviewed studies published between Jan 1, 2000, and Jan 20, 2022. 3547 studies were screened, of which 23 studies reporting the effects of social norm feedback interventions on antibiotic prescribing met the inclusion criteria. 19 behaviour change techniques were tested in the included studies. The meta-analyses showed that social norm feedback is an effective strategy for reducing antibiotic prescribing, with an overall rate difference of 4% (p<0·0001). The behaviour change technique with the highest effective ratio (ER=13) was information about health consequences, followed by instruction on how to perform the behaviour (ER=9) and adding objects to the environment (ER=9). Social norm feedback is a promising strategy to reduce antibiotic prescribing, and can be incorporated into the clinical decision-making support system.
Subject(s)
Anti-Bacterial Agents , Antimicrobial Stewardship , Humans , Anti-Bacterial Agents/therapeutic use , Feedback , Social NormsABSTRACT
Background: Antibiotic resistance leads to longer hospital stays, higher medical costs, and increased mortality. However, research into the relationship between climate change and antibiotic resistance remains inconclusive. This study aims to address the gap in the literature by exploring the association of antibiotic resistance with regional ambient temperature and its changes over time. Methods: Data were obtained from the China Antimicrobial Surveillance Network (CHINET), monitoring the prevalence of carbapenem-resistant Acinetobacter baumannii (CRAB), Klebsiella pneumoniae (CRKP) and Pseudomonas aeruginosa (CRPA) in 28 provinces/regions over the period from 2005 to 2019. Log-linear regression models were established to determine the association between ambient temperature and antibiotic resistance after adjustment for variations in socioeconomic, health service, and environmental factors. Findings: A 1 °C increase in average ambient temperature was associated with 1.14-fold increase (95%-CI [1.07-1.23]) in CRKP prevalence and 1.06-fold increase (95%-CI [1.03-1.08]) in CRPA prevalence. There was an accumulative effect of year-by-year changes in ambient temperature, with the four-year sum showing the greatest effect on antibiotic resistance. Higher prevalence of antibiotic resistance was also associated with higher antibiotic consumption, lower density of health facilities, higher density of hospital beds and higher level of corruption. Interpretation: Higher prevalence of antibiotic resistance is associated with increased regional ambient temperature. The development of antibiotic resistance under rising ambient temperature differs across various strains of bacteria. Funding: The National Key R&D Program of China (grant number: 2018YFA0606200), National Natural Science Foundation of China (grant number: 72074234), Fundamental Scientific Research Funds for Central Universities, P.R. China (grant number: 22qntd4201), China Medical Board (grant number: CMB-OC-19-337).
ABSTRACT
Cyberattacks are increasing in both number and severity for private, corporate, and governmental bodies. To prevent these attacks, many intrusion detection systems and intrusion prevention systems provide computer security by monitoring network packets and auditing system records. However, most of these systems only monitor network packets rather than the computer itself, so physical intrusion is also an important security issue. Furthermore, with the rapid progress of the Internet of Things (IoT) technology, security problems of IoT devices are also increasing. Many IoT devices can be disassembled for decompilation, resulting in the theft of sensitive data. To prevent this, physical intrusion detection systems of the IoT should be considered. We here propose a physical security system that can protect data from unauthorized access when the computer chassis is opened or tampered with. Sensor switches monitor the chassis status at all times and upload event logs to a cloud server for remote monitoring. If the system finds that the computer has an abnormal condition, it takes protective measures and notifies the administrator. This system can be extended to IoT devices to protect their data from theft.