Local actions to health risks of heatwaves and dengue fever under climate change: Strategies and barriers among primary healthcare professionals in southern China.

BACKGROUND: Climate change and extreme weather poses significant threats to community health, which need to be addressed by local health workforce. This study investigated the perceptions of primary healthcare professionals in Southern China on individual and institutional strategies for actions on health impacts of climate change and the related barriers. METHODS: A mixed methodological approach was adopted, involving a cross-sectional questionnaire survey of 733 primary healthcare professionals (including medical doctors, nurses, public health practitioners, allied health workers and managers) selected through a multistage cluster randomized sampling strategy, and in-depth interviews of 25 key informants in Guangdong Province, China. The questionnaire survey investigated the perceptions of respondents on the health impacts of climate change and the individual and institutional actions that need to be taken in response to climate change. Multivariate logistic regression models were established to determine sociodemographic factors associated with the perceptions. The interviews tapped into coping strategies and perceived barriers in primary health care to adapt to tackle challenges of climate change. Contents analyses were performed to extract important themes. RESULTS AND CONCLUSION: The majority (64%) of respondents agreed that climate change is happening, but only 53.6% believed in its human causes. Heat waves and infectious diseases were highly recognized as health problems associated with climate change. There was a strong consensus on the need to strengthen individual and institutional capacities in response to health impacts of climate change. The respondents believed that it is important to educate the public, take active efforts to control infectious vectors, and pay increased attention to the health care of vulnerable populations. The lack of funding and limited local workforce capacity is a major barrier for taking actions. Climate change should be integrated into primary health care development through sustainable governmental funding and resource support.

The historical roots and seminal research on health equity: a referenced publication year spectroscopy (RPYS) analysis.

BACKGROUND: Health equity is a multidimensional concept that has been internationally considered as an essential element for health system development. However, our understanding about the root causes of health equity is limited. In this study, we investigated the historical roots and seminal works of research on health equity. METHODS: Health equity-related publications were identified and downloaded from the Web of Science database (n = 67,739, up to 31 October 2018). Their cited references (n = 2,521,782) were analyzed through Reference Publication Year Spectroscopy (RPYS), which detected the historical roots and important works on health equity and quantified their impact in terms of referencing frequency. RESULTS: A total of 17 pronounced peaks and 31 seminal works were identified. The first publication on health equity appeared in 1966. But the first cited reference can be traced back to 1801. Most seminal works were conducted by researchers from the US (19, 61.3%), the UK (7, 22.6%) and the Netherlands (3, 9.7%). Research on health equity experienced three important historical stages: origins (1800-1965), formative (1966-1991) and development and expansion (1991-2018). The ideology of health equity was endorsed by the international society through the World Health Organization (1946) declaration based on the foundational works of Chadwick (1842), Engels (1945), Durkheim (1897) and Du Bois (1899). The concept of health equity originated from the disciplines of public health, sociology and political economics and has been a major research area of social epidemiology since the early nineteenth century. Studies on health equity evolved from evidence gathering to the identification of cost-effective policies and governmental interventions. CONCLUSION: The development of research on health equity is shaped by multiple disciplines, which has contributed to the emergence of a new stream of social epidemiology and political epidemiology. Past studies must be interpreted in light of their historical contexts. Further studies are needed to explore the causal pathways between the social determinants of health and health inequalities.

Preparing the next generation of health professionals to tackle climate change: Are China's medical students ready?

BACKGROUND: Climate change is the biggest global health threat of the 21st century. Medical students will lead the health sector responses and adaptation efforts in the near future, yet little is known in China about their knowledge, perceptions and preparedness to meet these challenges. METHODS: A nationwide study was conducted at five medical universities across different regions of China using a two-stage stratified cluster sampling design. A self-administered questionnaire was applied to collect the information including perception, preparedness and educational needs in response to climate change. The data were first analyzed descriptively, then chi-square tests and kruskal wallis tests were applied to determined differences among subgroups, and logistic regression analysis were deployed to detect the socio-demographic factors influencing student's perception. RESULTS: A total of 1436 medical students were approached and 1387 participated in the study (96.6% response rate). Most students were aware of the health impacts because of climate change, with over 90% perceived air quality-related and heat-related illness, while only a small part identified undernutrition and mental health. Approximately 90% embraced their role in tackling climate change, but 50% reported themselves and the health sectors were not adequately prepared. Compared to clinical students, preventive medicine students were more likely to perceive their responsibility to address climate change (OR:1.36, 95% CI: 1.04, 1.78). Also, 80% students admitted insufficient information and knowledge on climate change and health. Most students agreed that climate change and its health impacts should be included into their current curriculum. CONCLUSIONS: Medical students in China were aware of climate change and felt responsible, but were not ready to make responses to its health impacts. Educational efforts should reinforce eco-medical literacy development and capacity building in the era of climate change.

Patients' perceptions of interactions with hospital staff are associated with hospital readmissions: a national survey of 4535 hospitals.

BACKGROUND: Reducing 30-day hospital readmissions has become a focus of the current national payment policies. Medicare requires that hospitals collect and report patients' experience with their care as a condition of payment. However, the extent to which patients' experience with hospital care is related to hospital readmission is unknown. METHODS: We established multivariate regression models in which 30-day risk-adjusted readmission rates were the dependent variables and patients' perceptions of the responsiveness of the hospital staff and communication (as measured by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores) were the independent variables of interest. We selected six different clinical conditions for analyses, including acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure, hip/knee surgery, pneumonia, and stroke. Data included all acute care hospitals reporting in Hospital Compare in 2014. RESULTS: The number of hospitals with reported readmissions ranged from 2234 hospitals for AMI to 3758 hospitals for pneumonia. The average 30-day readmission rates ranged from 5.19% for knee/hip surgery to 22.7% for COPD. Patient experience of hospital-staff responsiveness as "top-box" ranged from 64% to 67% across the six clinical conditions, communication with nurses ranged from 77% to 79% and communication with doctors ranged from 80% to 81% (higher numbers are better). Our finding suggests that hospitals with better staff responsiveness were significantly more likely to have lower 30-day readmissions for all conditions. The effect size depended on the baseline readmission rates, with the largest effect on hospitals in the upper 75th quartile. A ten-percentage-point increase in staff responsiveness led to a 0.03-0.18 percentage point decrease in readmission rates. We found that neither communication with physicians nor communication with nurses was significantly associated with hospital readmissions. CONCLUSIONS: Our findings suggest that elements of care related to staff responsiveness during patients' stay may influence rehospitalization rates. Changes in staff responsiveness may offer an additional tool for hospitals to employ ongoing efforts to achieve reductions in readmissions, an important objective both financially and for patient health outcomes.

Prediction of virus-host infectious association by supervised learning methods.

BACKGROUND: The study of virus-host infectious association is important for understanding the functions and dynamics of microbial communities. Both cellular and fractionated viral metagenomic data generate a large number of viral contigs with missing host information. Although relative simple methods based on the similarity between the word frequency vectors of viruses and bacterial hosts have been developed to study virus-host associations, the problem is significantly understudied. We hypothesize that machine learning methods based on word frequencies can be efficiently used to study virus-host infectious associations. METHODS: We investigate four different representations of word frequencies of viral sequences including the relative word frequency and three normalized word frequencies by subtracting the number of expected from the observed word counts. We also study five machine learning methods including logistic regression, support vector machine, random forest, Gaussian naive Bayes and Bernoulli naive Bayes for separating infectious from non-infectious viruses for nine bacterial host genera with at least 45 infecting viruses. Area under the receiver operating characteristic curve (AUC) is used to compare the performance of different machine learning method and feature combinations. We then evaluate the performance of the best method for the identification of the hosts of contigs in metagenomic studies. We also develop a maximum likelihood method to estimate the fraction of true infectious viruses for a given host in viral tagging experiments. RESULTS: Based on nine bacterial host genera with at least 45 infectious viruses, we show that random forest together with the relative word frequency vector performs the best in identifying viruses infecting particular hosts. For all the nine host genera, the AUC is over 0.85 and for five of them, the AUC is higher than 0.98 when the word size is 6 indicating the high accuracy of using machine learning approaches for identifying viruses infecting particular hosts. We also show that our method can predict the hosts of viral contigs of length at least 1kbps in metagenomic studies with high accuracy. The random forest together with word frequency vector outperforms current available methods based on Manhattan and [Formula: see text] dissimilarity measures. Based on word frequencies, we estimate that about 95% of the identified T4-like viruses in viral tagging experiment infect Synechococcus, while only about 29% of the identified non-T4-like viruses and 30% of the contigs in the study potentially infect Synechococcus. CONCLUSIONS: The random forest machine learning method together with the relative word frequencies as features of viruses can be used to predict viruses and viral contigs for specific bacterial hosts. The maximum likelihood approach can be used to estimate the fraction of true infectious associated viruses in viral tagging experiments.

Distribution of essential medicines to primary care institutions in Hubei of China: effects of centralized procurement arrangements.

BACKGROUND: Poor distribution of essential medicines to primary care institutions has attracted criticism since China adopted provincial centralized regional tendering and procurement systems. This study evaluated the impact of new procurement arrangements that limit the number of distributors at the county level in Hubei province, China. METHODS: Procurement ordering and distribution data were collected from four counties that pioneered a new distribution arrangement (commencing September 2012) compared with six counties that continued the existing arrangement over the period from August 2011 to September 2013. The new arrangement allowed primary care institutions and/or suppliers to select a local distributor from a limited panel (from 3 to 5) of government nominated distributors. Difference-in-differences analyses were performed to assess the impact of the new arrangements on delivery and receipt of essential medicines. RESULTS: Overall, the new distribution arrangement has not improved distribution of essential medicines to primary care institutions. On the contrary, we found a 7.78-19.85 percentage point (p < 0.01) decrease in distribution rates to rural primary care institutions. Similar results were demonstrated using the indicator of received rates, with a 7.89-19.65 percentage point (p < 0.01) decrease. CONCLUSIONS: Simply limiting the number of distributors does not offer a solution to the poor performance of delivery of essential medicines for primary care institutions, especially those located in rural areas. Procurement arrangements need to consider the special characteristics of rural facilities. In a county, there are more rural primary care institutions than urban ones. On average, rural primary care institutions demand more and are more geographically dispersed compared to their urban counterparts, which may impose increased distribution costs.

An estimator for local analysis of genome based on the minimal absent word.

This study presents an alternative alignment-free relative feature analysis method based on the minimal absent word, which has potential advantages over the local alignment method in local analysis. Smooth-local-analysis-curve and similarity-distribution are constructed for a fast, efficient, and visual comparison. Moreover, when the multi-sequence-comparison is needed, the local-analysis-curves can illustrate some interesting zones.

An RNA secondary structure prediction method based on minimum and suboptimal free energy structures.

The function of an RNA-molecule is mainly determined by its tertiary structures. And its secondary structure is an important determinant of its tertiary structure. The comparative methods usually give better results than the single-sequence methods. Based on minimum and suboptimal free energy structures, the paper presents a novel method for predicting conserved secondary structure of a group of related RNAs. In the method, the information from the known RNA structures is used as training data in a SVM (Support Vector Machine) classifier. Our method has been tested on the benchmark dataset given by Puton et al. The results show that the average sensitivity of our method is higher than that of other comparative methods such as CentroidAlifold, MXScrana, RNAalifold, and TurboFold.

Use of appropriate healthcare technologies: a cross-sectional study in rural Zhejiang of China.

BACKGROUND: Appropriate healthcare technologies (AHTs) are an important strategy for improving the availability and accessibility of healthcare services. It is not clear what impact AHTs have on health workers and consumers; and whether those AHTs can continue in place without special or ongoing financial support. This study investigated the attitudes of health workers and consumers towards AHTs. METHODS: Health facilities from five counties in Zhejiang were surveyed. Participants of the study included all health workers who were involved in the delivery of AHTs in the selected organizations and a group of randomly selected patients who sought services from the participating organizations. A total of 822 questionnaires from health workers and 693 questionnaires from patients were collected for data analyses. The questionnaires measured perceptions and attitudes of respondents towards AHTs using a Likert scale. RESULTS: The respondents delivering public health services rated the highest scores to AHTs (4.42 ± 0.7), followed by those engaged in management of chronic conditions (4.41 ± 0.57) and Traditional Chinese Medicine (TCM) (4.29 ± 0.55). Around 90% of health workers believed that AHTs were meaningful for rural patients; however, only 69% of health workers believed that the technologies encouraged by the government were sufficiently developed or "mature", and more than 24% acknowledged difficulties in using those technologies. Overall, patients were satisfied with AHTs, with 71.6% feeling "very satisfied" or "satisfied", 24.2% feeling "acceptable" and 1.6% feeling "dissatisfied". Most (83%) patients were satisfied or very satisfied with Traditional Chinese Medicine, compared with management of chronic conditions (80%), family planning (67%), public health services (64%), and finally with maternal and child health care (59%). CONCLUSIONS: Local acceptability should be taken into consideration in determination of AHTs; consumer health literacy needs improvement, particularly in relation to public health and preventive services.

Public reporting improves antibiotic prescribing for upper respiratory tract infections in primary care: a matched-pair cluster-randomized trial in China.

BACKGROUND: Inappropriate use and overuse of antibiotics is a serious concern in the treatment of upper respiratory tract infections (URTIs), especially in developing countries. In recent decades, information disclosure and public reporting (PR) has become an instrument for encouraging good practice in healthcare. This study evaluated the impact of PR on antibiotic prescribing for URTIs in a sample of primary care institutions in China. METHODS: A matched-pair cluster-randomized trial was undertaken in QJ city, with 20 primary care institutions participating in the trial. Participating institutions were matched into pairs before being randomly assigned into a control and an intervention group. Prescription statistics were disclosed to patients, health authorities, and health workers monthly within the intervention group, starting from October 2013. Outpatient prescriptions for URTIs were collected from both groups before (1st March to 31st May, 2013) and after the intervention (1st March to 31st May, 2014). A total of 34,815 URTI prescriptions were included in a difference-in-difference analysis using multivariate linear or logistic regression models, controlling for patient attributes as well as institutional characteristics. RESULTS: Overall, 90% URTI prescriptions required antibiotics and 21% required combined use of antibiotics. More than 77% of URTI prescriptions required intravenous (IV) injection or infusion of drugs. PR resulted in a 9 percentage point (95% CI -17 to -1) reduction in the use of oral antibiotics (adjusted RR = 39%, P = 0.027), while the use of injectable antibiotics remained unchanged. PR led to a 7 percentage point reduction (95% CI -14 to 0; adjusted RR = 36%) in combined use of antibiotics (P = 0.049), which was largely driven by a significant reduction in male patients (-7.5%, 95% CI -14 to -1, P = 0.03). The intervention had little impact on the use of IV injections or infusions, or the total prescription expenditure. CONCLUSIONS: The results suggest that PR could improve prescribing practices in terms of reducing oral antibiotics and combined use of antibiotics; however, the impacts were limited. We suggest that PR would probably be enhanced by provider payment reform, management and training for providers, and health education for patients.

Prediction models for diagnosis and prognosis of the colonisation or infection of multidrug-resistant organisms in adults: A systematic review, critical appraisal, and meta-analysis.

BACKGROUND: Prediction models help target patients at risk of multidrug-resistant organism (MDRO) colonisation or infection and could serve as tools informing clinical practices to prevent MDRO transmission and inappropriate empiric antibiotic therapy. However, limited evidence identifies which among the available models are of low risk of bias and suitable for clinical application. OBJECTIVES: To identify, describe, appraise, and summarise the performance of all prognostic and diagnostic models developed or validated for predicting MDRO colonisation or infection. DATA SOURCES: Six electronic literature databases and clinical registration databases were searched until April 2022. STUDY ELIGIBILITY CRITERIA: Development and validation studies of any multivariable prognostic and diagnostic models to predict MDRO colonisation or infection in adults. ASSESSMENT OF RISK OF BIAS: The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Evidence certainty was assessed using the GRADE approach. METHODS OF DATA SYNTHESIS: Meta-analyses were conducted to summarise the discrimination and calibration of the models' external validations conducted in at least two non-overlapping datasets. RESULTS: We included 162 models (108 studies) developed for diagnosing (n=135) and predicting (n=27) MDRO colonisation or infection. Models exhibited a high risk of bias, especially in statistical analysis. High-frequency predictors were age, recent invasive procedures, antibiotic usage, and prior hospitalisation. Less than 25% of the models underwent external validations, with only seven by independent teams. Meta-analyses for one diagnostic and two prognostic models only produced very-low to low certainty of evidence. CONCLUSIONS: The review comprehensively described the models for identifying patients at risk of MDRO colonisation or infection. We cannot recommend which models are ready for application due to high risk of bias, limited validations, and low certainty of evidence from meta-analyses, indicating a clear need to improve the conducting and reporting of model development and external validation studies to facilitate clinical application.

Impacts of pharmacist-led multifaceted antimicrobial stewardship on antibiotic use and clinical outcomes in urology department of a tertiary hospital in Guangzhou, China: an interrupted time series study.

BACKGROUND: Limited research has explored the effectiveness of pharmacist-led antimicrobial stewardship programs (ASPs) in the urology department. OBJECTIVE: To evaluate the impact of pharmacist-led multifaceted ASPs on antibiotic use and clinical outcomes. METHODS: We conducted a prescription review of inpatients receiving one or more antibiotics in the urology department of a large teaching hospital in Guangzhou, China, from April 2019 to March 2023. The pharmacist-led multifaceted ASPs intervention included guidelines development, training, medication consultation, review of medical orders, indicator monitoring, and consultation. Our primary outcome was antibiotic consumption. The data was analysed using interrupted time series (ITS) analysis. RESULTS: Following the implementation of ASPs, we observed an immediate decrease in total antibiotic consumption (ß = -32.42 DDDs/100PD and -36.24 DOT/100PD, P < 0.001), Antibiotic use rate (ß = -7.87 %, P = 0.002), Second-generation cephalosporins (ß = -12.43 DDDs/100PD and -15.18 DOT/100PD, P < 0.001), Third-generation cephalosporins (ß = -5.13 DDDs/100PD, P = 0.001 and -6.16 DOT/100PD, P = 0.002), Fluoroquinolones (ß = -12.26 DDDs/100PD and -12.70 DOT/100PD, P < 0.001), and WHO Watch category antibiotics (ß = -32.07 DDDs/100PD and -34.96 DOT/100PD, P < 0.001). There were no differences observed in mortality rate before and after the intervention, and no significant short-term or long-term effects were found on length of hospital stay (LOS) using ITS. However, there was a significant short-term effect on average antibiotic cost (ß = -446.83 RMB, P = 0.004). CONCLUSION: The implementation of pharmacist-led multifaceted ASPs had positive impacts on reducing antimicrobial consumption without increasing LOS, antibiotic cost, or mortality rate.

Effects of pay-for-performance based antimicrobial stewardship on antimicrobial consumption and expenditure: An interrupted time series analysis.

Objectives: To evaluate the impact of pay-for-performance on antimicrobial consumption and antimicrobial expenditure in a large teaching hospital in Guangzhou, China. Methods: We collected data from hospital information system from January 2018 through September 2022 in the inpatient wards. Antimicrobial consumption was evaluated using antibiotic use density (AUD) and antibiotic use rate (AUR). The economic impact of intervention was assessed by antimicrobial expenditure percentage. The data was analyzed using interrupted time series (ITS) analysis. Results: Following the implementation of the intervention, immediate decreases in the level of AUD were observed in Department of Hematology Unit 3 (ß = -66.93 DDDs/100PD, P = 0.002), Urology (ß = -32.80 DDDs/100PD, P < 0.001), Gastrointestinal Surgery Unit 3 (ß = -11.44 DDDs/100PD, P = 0.03), Cardiac Surgery (ß = -14.30 DDDs/100PD, P = 0.01), ICU, Unit 2 (ß = -81.91 DDDs/100PD, P = 0.02) and Cardiothoracic Surgery ICU (ß = -41.52 DDDs/100PD, P = 0.05). Long-term downward trends in AUD were also identified in Organ Transplant Unit (ß = -1.64 DDDs/100PD, P = 0.02). However, only Urology (ß = -6.56 DDDs/100PD, P = 0.02) and Gastrointestinal Surgery Unit 3 (ß = -8.50 %, P = 0.01) showed an immediate decrease in AUR, and long-term downward trends in AUR were observed in Pediatric ICU (ß = -1.88 %, P = 0.05) and ICU Unit 1 (ß = -0.55 %, P = 0.02). Conclusion: This study demonstrates that the adoption of pay-for-performance effectively reduces antibiotic consumption in specific departments of a hospital in Guangzhou in the short term. However, it is important to recognize that the long-term impact of such interventions is often limited. Additionally, it should be noted that the overall effectiveness of the intervention across the entire hospital was not significant.

Global antimicrobial resistance and antibiotic use in COVID-19 patients within health facilities: A systematic review and meta-analysis of aggregated participant data.

OBJECTIVES: The COVID-19 pandemic has posed a significant threat to the global healthcare system, presenting a major challenge to antimicrobial stewardship worldwide. This study aimed to provide a comprehensive and up-to-date picture of global antimicrobial resistance (AMR) and antibiotic use in COVID-19 patients. METHODS: We conducted a systematic review to determine the prevalence of AMR and antibiotic usage among COVID-19 patients receiving treatment in healthcare facilities. Our search encompassed the PubMed, Web of Science, Embase, and Scopus databases, spanning studies published from December 2019 to May 2023. We utilized random-effects meta-analysis to assess the prevalence of multidrug-resistant organisms (MDROs) and antibiotic use in COVID-19 patients, aligning with both the WHO's priority list of MDROs and the AWaRe list of antibiotic products. Estimates were stratified by region, country, and country income. Meta-regression models were established to identify predictors of MDRO prevalence and antibiotic use in COVID-19 patients. The study protocol was registered with PROSPERO (CRD 42023449396). RESULTS: Among the 11,050 studies screened, 173 were included in the review, encompassing a total of 892,312 COVID-19 patients. MDROs were observed in 42.9% (95% CI 31.1-54.5%, I2 = 99.90%) of COVID-19 patients: 41.0% (95% CI 35.5-46.6%) for carbapenem-resistant organisms (CRO), 19.9% (95% CI 13.4-27.2%) for methicillin-resistant Staphylococcus aureus (MRSA), 24.9% (95% CI 16.7-34.1%) for extended-spectrum beta-lactamase-producing organisms (ESBL), and 22.9% (95% CI 13.0-34.5%) for vancomycin-resistant Enterococcus species (VRE), respectively. Overall, 76.2% (95% CI 69.5-82.9%, I2 = 99.99%) of COVID-19 patients were treated with antibiotics: 29.6% (95% CI 26.0-33.4%) with "Watch" antibiotics, 22.4% (95% CI 18.0-26.7%) with "Reserve" antibiotics, and 16.5% (95% CI 13.3-19.7%) with "Access" antibiotics. The MDRO prevalence and antibiotic use were significantly higher in low- and middle-income countries than in high-income countries, with the lowest proportion of antibiotic use (60.1% (95% CI 52.1-68.0%)) and MDRO prevalence (29.1% (95% CI 21.8-36.4%)) in North America, the highest MDRO prevalence in the Middle East and North Africa (63.9% (95% CI 46.6-81.2%)), and the highest proportion of antibiotic use in South Asia (92.7% (95% CI 90.4-95.0%)). The meta-regression identified antibiotic use and ICU admission as a significant predictor of higher prevalence of MDROs in COVID-19 patients. CONCLUSIONS: This systematic review offers a comprehensive and current assessment of MDRO prevalence and antibiotic use among COVID-19 patients in healthcare facilities. It underscores the formidable challenge facing global efforts to prevent and control AMR amidst the backdrop of the COVID-19 pandemic. These findings serve as a crucial warning to policymakers, highlighting the urgent need to enhance antimicrobial stewardship strategies to mitigate the risks associated with future pandemics.

Multiple impacts of the COVID-19 pandemic and antimicrobial stewardship on antimicrobial resistance in nosocomial infections: an interrupted time series analysis.

Objectives: The emergency response to the COVID-19 pandemic may disrupt hospital management activities of antimicrobial resistance (AMR). This study aimed to determine the changing AMR trend over the period in China when stringent COVID-19 response measures were implemented. Methods: This retrospective study was conducted in a designated hospital for COVID-19 patients in Guangzhou, China from April 2018 to September 2021. The prevalence of 13 antimicrobial-resistant bacteria was compared before and after the COVID-19 responses through Chi-square tests. Interrupted time series (ITS) models on the weekly prevalence of AMR were established to determine the changing trend. Controlled ITS models were performed to compare the differences between subgroups. Results: A total of 10,134 isolates over 1,265 days were collected. And antimicrobial-resistant strains presented in 38.6% of the testing isolates. The weekly AMR prevalence decreased by 0.29 percentage point (95% CI [0.05-0.80]) after antimicrobial stewardship (AMS) policy, despite an increase in the prevalence of penicillin-resistant Streptococcus pneumoniae (from 0/43 to 15/43, p < 0.001), carbapenem-resistant Escherichia coli (from 20/1254 to 41/1184, p = 0.005), and carbapenem-resistant Klebsiella pneumoniae (from 93/889 to 114/828, p = 0.042). And the changing trend did not vary by gender (male vs. female), age (<65 vs. ≥65 years), service setting (outpatient vs. inpatient), care unit (ICU vs. non-ICU), the primary site of infection (Lung vs. others), and Gram type of bacteria (positive vs. negative). Conclusion: The response to COVID-19 did not lead to an increase in overall AMR; however, it appears that management strategy on the prudent use of antimicrobials likely contributed to a sizable long-term drop. The frequency of several multidrug-resistant bacteria continues to increase after the COVID-19 epidemic. It is crucial to continue to monitor AMR when COVID-19 cases have surged in China after the relaxation of restriction measures.

Alignment free comparison: k word voting model and its applications.

Alignment free sequence comparison is widely used in sequence analysis, especially in computational biology for large scale similarity comparison. In this paper, we propose a word voting model to compare the biological sequences without alignment. Unlike many comparison methods based on the k word, this model does not use the k word frequency or statistics. Thus there is no limitation on the choice of k. Instead, we used information entropy of gamma distribution to characterize the differences among biological sequences in this model. Finally, we employed the model to do the similarity search and phylogenetic tree construction to further validate the model.

Application of propensity scores to estimate the association between government subsidy and injection use in primary health care institutions in China.

BACKGROUND: The problem posed by therapeutic injection is a clinical practice issue that influences health care quality and patient safety. Although sufficient government subsidy was one of the 12 key interventions to promote rational drug use initiated by WHO (World Health Organization), limited information is available about the association between government subsidy and injection use in primary health care institutions. In 2009, National Essential Medicines System (NEMS) was implemented in China. The subsidy policy plays an important role in maintaining primary health care institutions. This study explores the impact of government subsidies on the injection use in primary health care institutions in China. METHODS: 126 primary health institutions were included in this study. Institutions were divided into two groups (intervention and control groups) according to the median GS (General subsidy per personnel). Propensity score matching (PSM) was used to minimize the observed covariate differences in the characteristics of the primary institutions between the two groups. Kappa score was calculated to determine the consistency between the groups. Paired chi-square test and Relative Risk (RR) were calculated to compare the differences in injection use between the groups. RESULTS: Among all the investigated prescriptions, the overall percent of people who received an injection prescribed was 36.96% (n = 12600). PSM showed no significant covariate difference among the 34 groups obtained through this analysis. Kappa score (k = -0.082, p = 0.558) indicated an inconsistency between groups and paired chi-square test revealed a significant difference (p < 0.05) in injection use between the two groups. Relative Risk = 0.679 (95%CI [0.485, 0.950]) indicate that high General subsidy per personnel is a protective factor for primary health care institutions to prescribe injections properly. The intervention group obtained a higher possibility of using injection properly. CONCLUSIONS: The overall effect of government subsidy on the use of injection was positively significant. However, the mechanism by which government subsidy influence injection administration remains unclear, and thus requires further study.

Effects of the Implementation of Transport-Driven Poverty Alleviation Policy on Health Care-Seeking Behavior and Medical Expenditure Among Older People in Rural Areas: Quasi-Experimental Study.

BACKGROUND: Improving the rural residents' accessibility to and affordability of health care is recognized as a common target globally. The Health in All Policies approach, from the Declaration of Helsinki to the United Nations' Decade Of Healthy Ageing, strengthened the far-reaching effect of large-scale public policies on health care-seeking behavior; however, the effects of national transport policy on health care-seeking behavior is unclear. OBJECTIVE: This quasi-experimental study aimed to examine the effects of the implementation of transport-driven poverty alleviation (TPA) policy on health care-seeking behavior and medical expenditure among older adults in rural areas and the mechanism underlying these effects. METHODS: We designed a quasi-experiment to estimate the effects of TPA policy implementation on health care-seeking behavior and medical expenditure among older adults in rural areas through a difference-in-differences (DID) analysis based on data from the China Health and Retirement Longitudinal Study in 2011, 2013, 2015, and 2018. The underlying mechanism was analyzed and effect modification patterns were further investigated by poor households, health status, and age. RESULTS: Our findings validated a positive contribution of TPA policy on health care-seeking behavior among older adults in rural areas. After the implementation of TPA policy, the number of inpatient visits increased by annually 0.35 times per person, outpatient medical expenditure increased by 192% per month, and inpatient medical expenditure increased by 57% annually compared with those of older adults in rural areas without the implementation of TPA policy. Further, there was a significant modification effect, with a positive effect among poor households, healthier older adults, and those aged 60-80 years. Additionally, the policy improved the patients' capabilities to seek long-distance care (ß=23.16, 95% CI -0.99 to 45.31) and high-level hospitals (ß=.08, 95% CI -0.02 to 0.13), and increased individual income to acquire more medical services (ß=4.57, 95% CI -4.46 to 4.68). CONCLUSIONS: These findings validate the positive contribution of TPA policy on health care-seeking behavior among older adults in rural areas; however, the medical expenditure incurred was also high. Concerted efforts are needed to address health care-seeking dilemmas in rural areas, and attention must be paid to curbing medical expenditure growth for older adults in rural areas during TPA policy implementation.

Effects of social norm feedback on antibiotic prescribing and its characteristics in behaviour change techniques: a mixed-methods systematic review.

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.

Association between antibiotic resistance and increasing ambient temperature in China: An ecological study with nationwide panel data.

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).