Background: COVID-19 arise global attention since their first public reporting. Infection prevention and control (IPC) is critical to combat COVID-19, especially at the early stage of pandemic outbreak. This study aimed to measure level of healthcare workers’ (HCW’) self-reported IPC behaviors with the risk of COVID-19 emerges and increases. Methods: A cross-sectional study was conducted in two tertiary hospitals. A structured self-administered questionnaire was delivered to HCWs in selected hospitals. The dependent variables were self-reported IPC behavior compliance; and independent variables were outbreak risk and three intent of infection risk (risk of contact with suspected patients, high-risk department, risk of affected area). Chi-square tests and multivariable negative binomial regression models were employed. Results: A total of 1386 participants were surveyed. The risk of outbreak increased self-reported IPC behavior on each item (coefficient varied from 0.029 to 0.151). Considering different extent of risk, HCWs from high-risk department had better self-reported practice in most IPC behavior (coefficient ranged from 0.027 to 0.149). HCWs in risk-affected area had higher self-reported compliance in several IPC behavior (coefficient ranged from 0.028 to 0.113). However, HCWs contacting with suspected patients had lower self-reported compliance in several IPC behavior (coefficient varied from − 0.159 to − 0.087). Conclusions: With the risk of COVID-19 emerges, HCWs improve IPC behaviors comprehensively, which benefits for better combat COVID-19. With the risk (high-risk department and affected area) further increases, majority of IPC behaviors achieved improvement. Nevertheless, under the risk of contact with suspected patients, HCWs show worse IPC behaviors. Which may result from higher work load and insufficient supplies and resources among these HCWs. The preparedness system should be improved and medical assistance is urgently needed.

Few studies have explored air and surface contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare settings. Air and surface samples were collected from the isolation wards and intensive care units designated for coronavirus disease 2019 (COVID-19) patients. Clinical data and the results of nasopharyngeal specimen and serum antibody testing were also collected for the patient sample. A total of 367 air and surface swab samples were collected from the patient care areas of 15 patients with mild COVID-19 and nine patients with severe/critical COVID-19. Only one air sample taken during the intubation procedure tested positive. High-touch surfaces were slightly more likely to be contaminated with SARS-CoV-2 RNA than low-touch surfaces. Contamination rates were slightly higher near severe/critical patients than near mild patients, although this difference was not statistically significant (p > 0.05). Surface contamination was still found near the patients with both positive IgG and IgM. Air and surface contamination with viral RNA was relatively low in these healthcare settings after the enhancement of infection prevention and control. Environmental contamination could still be found near seroconverted patients, suggesting the need to maintain constant vigilance in healthcare settings to reduce healthcare-associated infection during the COVID-19 pandemic.

Background: This study aims to explore the impacts of knowledge and attitude on the behavior of antibiotic use during the treatment of the common cold based on the expanding KAP model, and then identify the critical behavioral stage. Methods: A cross-sectional study was conducted on 815 public from 21 community health centers (CHCs) in Chongqing, China. Based on the expanding KAP model, a self-administered questionnaire was designed to measure knowledge, attitude, multi-stage behavior, and perceived threat, in which multi-stage behavior was divided into pre-use antibiotic behavior, during-use antibiotic behavior, and post-use antibiotic behavior. A structural equation model was used to examine the model fit and the direct, indirect, mediating effects, and moderating effect of the variables. Results: The expanding KAP showed good model fit indices with χ²/df = 0.537, RMSEA = 0.033, CFI = 0.973, GFI = 0.971, NFI = 0.934, TLI = 0.979. Knowledge had a positive effect on attitude (β = 0.503, p < 0.05), pre-use antibiotic behavior (β = 0.348, p < 0.05), during-use antibiotic behavior (β = 0.461, p < 0.001), and post-use antibiotic behavior (β = 0.547, p < 0.001). Attitude had a positive effect on during-use antibiotic behavior (β = 0.296, p < 0.001), and post-use antibiotic behavior (β = 0.747, p < 0.001). The mediating effect of attitude was positive among knowledge, during-use antibiotic behavior (β = 0.149, p < 0.05), and post-use antibiotic behavior (β = 0.376, p < 0.001). Perceived threat also had a positive moderating effect between knowledge and post-use antibiotic behavior (β = 0.021, p < 0.001). Conclusions: Knowledge, attitude and perceived threat had different effects on different stages of antibiotic behavior. The critical behavioral stage prioritized the post-use antibiotic behavior and during-use antibiotic behavior over pre-use antibiotic behavior.

Background: Hand hygiene among healthcare workers is the leading measure to reduce healthcare-associated infections. However, hand hygiene behavior is complex and not readily understood. This study aimed to identify the determinants and the underlying mechanism of hand hygiene behavior based on the capability, opportunity, motivation-behavior model. Methods: A self-constructed questionnaire survey was conducted among healthcare workers in Chongqing, China. Capability, opportunity, and motivation were designed as independent variables, and hand hygiene behavior was measured as a dependent variable. Internal consistency reliability analysis and confirmatory factor analysis were applied to examine the reliability and validity of the questionnaire. Structural equation modeling was performed to explore the relationships among capability, opportunity, motivation, and hand hygiene behavior. Results: Four hundred and ninety-nine physicians and nurses were investigated. The Cronbach’s α coefficients were above 0.764. Confirmatory factor analysis was confirmed with good data fitness. The structural equation modeling had a good fit (root mean square error of approximation=0.070, comparative fit index=0.960, Tucker–Lewis index=0.956). Both opportunity (β=0.265, p< 0.05) and motivation (β=0.333, p< 0.05) directly affected hand hygiene behavior. Both capability (β=0.194, p< 0.001) and opportunity (β=0.719, p< 0.001) were indirectly linked to hand hygiene behavior through motivation. Conclusion: To improve hand hygiene behavior, more efforts need to be focused on resource provision and motivation enhancement in the future compared to training.

Background: The current evidence of extra length of stay (LOS) attributable to healthcare-associated infection (HCAI) scarcely takes time-dependent bias into consideration. Plus, limited evidences were from developing countries. We aim to estimate the extra LOS and risk factors of mortality attributable to HCAI for inpatients. Methods: Multi-state model (MSM) was adopted to estimate the extra LOS attributable to HCAI of each type and subgroup. COX regression model was used to examine the risk of mortality. Results: A total of 51,691 inpatients were included and 1709 (3.31%) among them developed HCAI. Lower respiratory tract infection and Acinetobacter baumannii were the most prevalent HCAI and causative pathogen in surveyed institute. Generally, the expected extra LOS attributable to HCAI was 2.56 days (95% confidence interval: 2.54–2.61). Patients below 65 had extra LOS attributable to HCAI longer about 2 days than those above. The extra LOS attributable to HCAI of male patients was 1.33 days longer than female. Meanwhile, age above 65 years old and HCAI were the risk factors of mortality for inpatients. Conclusions: HCAI contributes to an increase in extra LOS of inpatients in China. The effect of HCAI on extra LOS is different among subgroups, with the age below 65, male and medicine department more sensitive.

Background: Healthcare-associated infections have become a serious public health problem. Various types of information systems have begun to be applied in hospital infection prevention and control (IPC) practice. Clinicians are the key users of these systems, but few studies have assessed the use of infection prevention and control information systems (IPCISs) from their perspective. Objective: This study aimed to (1) apply the extended DeLone and McLean Information Systems Success model (D&M model) that incorporates IPC culture to examine how technical factors like information quality, system quality, and service quality, as well as organizational culture factors affect clinicians’ use intention, satisfaction, and perceived net benefits, and (2) identify which factors are the most important for clinicians’ use intention. Methods: A total of 12,317 clinicians from secondary and tertiary hospitals were surveyed online. Data were analyzed using partial least squares-structural equation modeling and the importance-performance matrix analysis. Results: Among the technical factors, system quality (β=.089-.252; P<.001), information quality (β=.294-.102; P<.001), and service quality (β=.126-.411; P<.001) were significantly related to user satisfaction (R2=0.833), use intention (R2=0.821), and perceived net benefits (communication benefits [R2=0.676], decision-making benefits [R2=0.624], and organizational benefits [R2=0.656]). IPC culture had an effect on use intention (β=.059; P<.001), and it also indirectly affected perceived net benefits (β=.461-.474; P<.001). In the importance-performance matrix analysis, the attributes of service quality (providing user training) and information quality (readability) were present in the fourth quadrant, indicating their high importance and low performance. Conclusions: This study provides valuable insights into IPCIS usage among clinicians from the perspectives of technology and organization culture factors. It found that technical factors (system quality, information quality, and service quality) and hospital IPC culture have an impact on the successful use of IPCISs after evaluating the application of IPCISs based on the extended D&M model. Furthermore, service quality and information quality showed higher importance and lower performance for use intention. These findings provide empirical evidence and specific practical directions for further improving the construction of IPCISs.