Socioeconomic factors associated with antimicrobial resistance of Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli in Chilean hospitals (2008-2017)

Linking epidemiological and genomic data in cases of enteric fever in England to inform clinical management and public health action

OBJECTIVES

To explore the feasibility of linking data from enhanced surveillance patient questionnaires from each enteric fever case in England with genome sequencing data, including antimicrobial resistance (AMR) profiles, from the corresponding isolate of typhoidal salmonellae.

METHODS

After linking data we interrogated the merged dataset and assessed the utility of passive surveillance data to match and monitor antimicrobial treatment regimens in enteric fever patients with the AMR profiles of the infectious agent.

RESULTS

A high proportion of cases were given antibiotics (n = 1230/1415; 86.9%); half of the cases stated the class of antibiotic they were given (n = 630/1239) and half were prescribed cephalosporins (n = 316/630). Reported treatment with a combination of antibiotics increased with symptom severity. Nearly half of isolates (n = 644/1415; 45.5%) had mutations conferring resistance to ciprofloxacin. Based on genome-derived AMR profiles, typhoidal salmonellae isolates inferred to be susceptible to the recommended first-line antimicrobials were twice as likely to be isolated from individuals residing in the least deprived areas compared with the most deprived (n = 26/169; 15.4% versus n = 32/442; 7.2%).

CONCLUSIONS

Due to the high proportion of missing data obtained from patient interviews, we recommend a more transparent and systematic approach to recording the antibiotic prescription details by healthcare professionals in primary and secondary care. A more robust approach to data capture at this point in the care pathway would enable us to audit inconsistencies in the prescribing algorithms across England and ensure equitable treatment across all sections of society. Integrating prescribing data with the genome-derived AMR profiles of the causative agent at the individual patient level provides an opportunity to monitor the impact of treatment on clinical outcomes, and to promote best practice in real time.

Potential Causes of Spread of Antimicrobial Resistance and Preventive Measures in One Health Perspective-A Review

Antimicrobial resistance, referring to microorganisms' capability to subsist and proliferate even when there are antimicrobials is a foremost threat to public health globally. The appearance of antimicrobial resistance can be ascribed to anthropological, animal, and environmental factors. Human-related causes include antimicrobial overuse and misuse in medicine, antibiotic-containing cosmetics and biocides utilization, and inadequate sanitation and hygiene in public settings. Prophylactic and therapeutic antimicrobial misuse and overuse, using antimicrobials as feed additives, microbes resistant to antibiotics and resistance genes in animal excreta, and antimicrobial residue found in animal-origin food and excreta are animals related contributive factors for the antibiotic resistance emergence and spread. Environmental factors including naturally existing resistance genes, improper disposal of unused antimicrobials, contamination from waste in public settings, animal farms, and pharmaceutical industries, and the use of agricultural and sanitation chemicals facilitatet its emergence and spread. Wildlife has a plausible role in the antimicrobial resistance spread. Adopting a one-health approach involving using antimicrobials properly in animals and humans, improving sanitation in public spaces and farms, and implementing coordinated governmental regulations is crucial for combating antimicrobial resistance. Collaborative and cooperative involvement of stakeholders in public, veterinary and ecological health sectors is foremost to circumvent the problem effectively.

Association of health, nutrition, and socioeconomic variables with global antimicrobial resistance: a modelling study

BACKGROUND

Although antimicrobial use is a key selector for antimicrobial resistance, recent studies have suggested that the ecological context in which antimicrobials are used might provide important factors for the prediction of the emergence and spread of antimicrobial resistance.

METHODS

We used 1547 variables from the World Bank dataset consisting of socioeconomic, developmental, health, and nutritional indicators; data from a global sewage-based study on antimicrobial resistance (abundance of antimicrobial resistance genes [ARGs]); and data on antimicrobial usage computed from the ECDC database and the IQVIA database. We characterised and built models predicting the global resistome at an antimicrobial class level. We used a generalised linear mixed-effects model to estimate the association between antimicrobial usage and ARG abundance in the sewage samples; a multivariate random forest model to build predictive models for each antimicrobial resistance class and to select the most important variables for ARG abundance; logistic regression models to test the association between the predicted country-level antimicrobial resistance abundance and the country-level proportion of clinical resistant bacterial isolates; finite mixture models to investigate geographical heterogeneities in the abundance of ARGs; and multivariate finite mixture models with covariates to investigate the effect of heterogeneity in the association between the most important variables and the observed ARG abundance across the different country subgroups. We compared our predictions with available clinical phenotypic data from the SENTRY Antimicrobial Surveillance Program from eight antimicrobial classes and 12 genera from 56 countries.

FINDINGS

Using antimicrobial use data from between Jan 1, 2016, and Dec 31, 2019, we found that antimicrobial usage was not significantly associated with the global ARG abundance in sewage (p=0·72; incidence rate ratio 1·02 [95% CI 0·92-1·13]), whereas country-specific World Bank's variables explained a large amount of variation. The importance of the World Bank variables differed between antimicrobial classes and countries. Generally, the estimated global ARG abundance was positively associated with the prevalence of clinical phenotypic resistance, with a strong association for bacterial groups in the human gut. The associations between bacterial groups and ARG abundance were positive and significantly different from zero for the aminoglycosides (three of the four of the taxa tested), β-lactam (all the six microbial groups), fluoroquinolones (seven of nine of the microbial groups), glycopeptide (one microbial group tested), folate pathway antagonists (four of five microbial groups), and tetracycline (two of nine microbial groups).

INTERPRETATION

Metagenomic analysis of sewage is a robust approach for the surveillance of antimicrobial resistance in pathogens, especially for bacterial groups associated with the human gut. Additional studies on the associations between important socioeconomic, nutritional, and health factors and antimicrobial resistance should consider the variation in these associations between countries and antimicrobial classes.

FUNDING

EU Horizon 2020 and Novo Nordisk Foundation.

Healthcare-associated infections by multidrug-resistant bacteria in Andalusia, Spain, 2014 to 2021

BackgroundMultidrug-resistant (MDR) bacteria are among chief causes of healthcare-associated infections (HAIs). In Spain, studies addressing multidrug resistance based on epidemiological surveillance systems are lacking.AimIn this observational study, cases of HAIs by MDR bacteria notified to the epidemiological surveillance system of Andalusia, Spain, between 2014-2021, were investigated. Notified cases and their spatiotemporal distribution were described, with a focus on social determinants of health (SDoH).MethodsNew cases during the study period of HAIs caused by extended-spectrum β-lactamase (ESBL)-/carbapenemase-producing Enterobacterales, MDR Acinectobacter baumannii, MDR Pseudomonas aeruginosa or meticillin resistant Staphylococcus aureus were considered. Among others, notification variables included sex and age, while socio-economic variables comprised several SDoH. Cases' spatial distribution across municipalities was assessed. The smooth standardised incidence ratio (sSIR) was obtained using a Bayesian spatial model. Association between municipalities' sSIR level and SDoH was evaluated by bivariate analysis.ResultsIn total, 6,389 cases with a median age of 68 years were notified; 61.4% were men (n = 3,921). The most frequent MDR bacteria were ESBL-producing Enterobacterales (2,812/6,389; 44.0%); the main agent was Klebsiella spp. (2,956/6,389; 46.3%). Between 2014 and 2021 case numbers appeared to increase. Overall, up to 15-fold differences in sSIR between municipalities were observed. In bivariate analysis, there appeared to be an association between municipalities' sSIR level and deprivation (p = 0.003).ConclusionThis study indicates that social factors should be considered when investigating HAIs by MDR bacteria. The case incidence heterogeneity between Andalusian municipalities might be explained by SDoH, but also possibly by under-notification. Automatising reporting may address the latter.

Social demographics determinants for resistome and microbiome variation of a multiethnic community in Southern Malaysia

The prevalence of antibiotic-resistant bacteria in Southeast Asia is a significant concern, yet there is limited research on the gut resistome and its correlation with lifestyle and environmental factors in the region. This study aimed to profile the gut resistome of 200 individuals in Malaysia using shotgun metagenomic sequencing and investigate its association with questionnaire data comprising demographic and lifestyle variables. A total of 1038 antibiotic resistance genes from 26 classes were detected with a mean carriage rate of 1.74 ± 1.18 gene copies per cell per person. Correlation analysis identified 14 environmental factors, including hygiene habits, health parameters, and intestinal colonization, that were significantly associated with the resistome (adjusted multivariate PERMANOVA, p < 0.05). Notably, individuals with positive yeast cultures exhibited a reduced copy number of 15 antibiotic resistance genes. Network analysis highlighted Escherichia coli as a major resistome network hub, with a positive correlation to 36 antibiotic-resistance genes. Our findings suggest that E. coli may play a pivotal role in shaping the resistome dynamics in Segamat, Malaysia, and its abundance is strongly associated with the community's health and lifestyle habits. Furthermore, the presence of yeast appears to be associated with the suppression of antibiotic-resistance genes.

Knowledge, Attitude, and Practices (KAP) on Antibiotic Use and Disposal Ways in Sidama Region, Ethiopia: A Community-Based Cross-Sectional Survey

Antibiotic resistance has been among the top public health threats elsewhere. Scientific information on knowledge, attitudes, and practices (KAP) at the community level towards antibiotic use and disposal ways is a vital step for effective intervention. This study aimed at determining the levels of KAP and associated risk factors for antibiotics in and around Hawassa City, southern Ethiopia. A community-based cross-sectional study was conducted, and data were collected using a structured questionnaire. Descriptive statistics, chi-square test, and logistic regression were used to analyze and interpret the results. A total of 504 participants with a mean age of 35.32 ± 9.03 years were included in the study. Most of the participants were urban dwellers (59.5%); more than half (55.6%) of the participants were male; most of the participants (62.7%) were at least college graduates; about half were employed (52.4%); about 41.7% of the participants had a large family size (≥7) with a mean family size of 5.7 ± 2.7; the average family monthly income was ETB 7213.71 ± 3673, and over three-fourth (74.8%) of the study participants were married. In addition, about 83.13% of the study participants heard about antibiotics; almost all of them (99.8%) had ever used antibiotics at some point in their life (75% of which used antibiotics within 6 months), and all of them could name at least one common type of antibiotic. Moreover, most of the participants (86.5%) did not receive any training related to antibiotics, and 29.4% of them obtained antibiotics without a prescription. Most participants had poor knowledge (64%), negative attitudes (60.4%), and poor practices (55%) towards antibiotic use, resistance, and disposal methods. Significant and positive linear correlations between knowledge and attitude (r = 0.539, P ≤ 0.001), knowledge-practice (r = 0.532, P ≤ 0.001), and attitude-practice (r = 0.786, P < 0.001) were also observed. Most of the sociodemographic variables were significantly associated with the mean KAP scores of the study participants. Living in a rural area, having a large family size, and being female, married, illiterate, and farmer resulted in a very low level of knowledge. Similarly, living in a rural area, having a small family size, and being older and married resulted in a negative attitude. Furthermore, having a smaller family size, having a low family monthly income, and being married, illiterate, and self-employed resulted in poor practice. A very low level of KAP towards antibiotics among people living in and around Hawassa City calls for urgent and effective intervention strategies.

Trends and socioeconomic, demographic, and environmental factors associated with antimicrobial resistance: a longitudinal analysis in 39 hospitals in Chile 2008-2017

Background

Antimicrobial resistance (AMR) is among the most critical global health threats of the 21st century. AMR is primarily driven by the use and misuse of antibiotics but can be affected by socioeconomic and environmental factors. Reliable and comparable estimates of AMR over time are essential to making public health decisions, defining research priorities, and evaluating interventions. However, estimates for developing regions are scant. We describe the evolution of AMR for critical priority antibiotic-bacterium pairs in Chile and examine their association with hospital and community-level characteristics using multivariate rate-adjusted regressions.

Methods

Drawing on multiple data sources, we assembled a longitudinal national dataset to analyse AMR levels for critical priority antibiotic-bacterium combinations in 39 private and public hospitals (2008-2017) throughout the country and characterize the population at the municipality level. We first described trends of AMR in Chile. Second, we used multivariate regressions to examine the association of AMR with hospital characteristics and community-level socioeconomic, demographic, and environmental factors. Last, we estimated the expected distribution of AMR by region in Chile.

Findings

Our results show that AMR for priority antibiotic-bacterium pairs steadily increased between 2008 and 2017 in Chile, driven primarily by Klebsiella pneumoniae resistant to third-generation cephalosporins and carbapenems, and vancomycin-resistant Enterococcus faecium. Higher hospital complexity, a proxy for antibiotic use, and poorer local community infrastructure were significantly associated with greater AMR.

Interpretation

Consistent with research in other countries in the region, our results show a worrisome increase in clinically relevant AMR in Chile and suggest that hospital complexity and living conditions in the community may affect the emergence and spread of AMR. Our results highlight the importance of understanding AMR in hospitals and their interaction with the community and the environment to curtail this ongoing public health crisis.

Funding

This research was supported by the Agencia Nacional de Investigación y Desarrollo (ANID), Fondo Nacional de Desarrollo Científico y Tecnológico FONDECYT, The Canadian Institute for Advanced Research (CIFAR), and Centro UC de Políticas Públicas, Pontificia Universidad Católica de Chile.

Antimicrobial Resistance Profile of Pseudomonas aeruginosa from Different Clinical Samples in Debre Tabor Comprehensive Specialized Hospital, Northwest Ethiopia

Background

Pseudomonas aeruginosa is one of the leading causes of hospital-acquired infections and the most common antimicrobial-resistant pathogens. It is associated with a variety of infections. This study aimed to determine the prevalence of P. aeruginosa and its antimicrobial resistance profile from different clinical specimens at Debre Tabor Comprehensive Referral Hospital (DTCRH).

Methods

A cross-sectional study was conducted from May to July 2022 at DTCRH. Socio-demographic and clinical data were collected using a structured questionnaire. Clinical samples (blood, wound swab, urine, and sputum) were collected from 348 study participants and processed following the standard bacteriological techniques. Antibiotic susceptibility testing was done by the Kirby-Bauer disc diffusion method. Data were entered and analyzed using SPSS version 25 statistical software. Descriptive statistics was used to present the findings of the study.

Results

The prevalence of P.aeruginosa was 74(19.3%). The detection of the isolates was different based on the type of samples that ranged from 0% to 54.5% from sputum and wound swabs, respectively. P.aeruginosa showed resistance against gentamicin at 62.2%, ceftazidime 51.4%, cefepime 50%, amikacin 29.7%, imipenem 28.4% and ciprofloxacin 14.9%. The level of multi-drug resistance (MDR) was 45.9%, and the suspicious extreme-drug resistance (XDR) rate was 9.5%. Being inpatient and wound swab samples were factors associated with the detection of P.aeruginosa from clinical samples.

Conclusion

The antibiotic resistance profile of P. aeruginosa isolates in the present study area was found to be alarming. Actions to minimize the effect of antimicrobial resistance should be strengthened, and further large-scale study should be conducted to find out the main reasons behind antibiotic resistance of P.aeruginosa and other clinically relevant isolates.

Adsorption kinetics studies of ciprofloxacin in soils derived from volcanic materials by electrochemical approaches and assessment of socio-economic impact on human health

The use of antibiotics in the livestock sector has resulted in the entry of these drugs into the soil matrix through the disposal of manure as an organic amendment. To define the fate of these drugs, it is necessary to evaluate kinetic aspects regarding transport in the soil-solution. The aim of this paper is to evaluate the adsorption kinetic parameters of Ciprofloxacin (CIPRO) in Ultisol and Andisol soil which allows obtaining main kinetic parameters (pseudo-first and pseudo-second order models) and to establish the solute transport mechanism by applying kinetic models such as the Elovich equation, Intraparticle diffusion (IPD) and, the Two-site non-equilibrium models (TSNE). The adsorption kinetics of this fluoroquinolone (FQ), on both soils derived from volcanic ashes, is developed using electrochemical techniques for their determination. The experimental amount of CIPRO adsorbed over time (Qt) data best fit with the pseudo-second order kinetic models; R² = 0.9855, Ɛ = 10.17% and R² = 0.9959, Ɛ = 10.77% for Ultisol and Andisol, respectively; and where CIPRO adsorption was considered time dependent for both soils but the lower adsorption capacity in Ultisol; with 17.6 ± 2.8 μmol g^-1; which could mean a greater risk in environmental. Subsequently, applying models to describe solute transport mechanisms showed differences in the CIPRO adsorption extent for the fast and slow phases. Adsorption isotherms were evaluated, where Ultisol occurs on heterogenous sites as multilayers and Andisol by monolayer with similar Q_max. Finally, the socio-economic impact of antibiotic usage is presented, giving the importance of antibiotics in the livestock sector and their effects on human health.

Rate of Multidrug-resistance to Antimicrobial Drugs in Patients in Pediatric Neurointensive Care

Background

Multidrug-resistant (MDR) organisms in the critical care unit are a worldwide concern. The vulnerability to MDR infection in pediatric patients admitted in neurocritical care are due to altered mental status, immature immune system, higher risk of aspiration, and more frequent use of invasive devices. We aimed to measure the burden of MDR infection in pediatric neurosurgical intensive care unit (NSICU) patients.

Methods

All pediatric patients between 1 and 18 years for intracranial and spine surgeries admitted for more than 48 hours in NSICU were enrolled in the study. If patients showed a clinical picture of pneumonia, bloodstream infection (BSI), or urinary tract infection (UTI) after receiving mechanical ventilation or an indwelling device for at least 48 hours, samples of tracheal aspirates, urine, blood, and cerebrospinal fluid (CSF) were sent for microbiological culture. We noted the type of organism, MDR infection rate, and associated risk factors. Pearson Chi-squared test and Fisher's test were used for statistical analysis; p < 0.05 was considered statistically significant.

Results

A total of 274 pediatric patients were studied. In 1 year, there was a total of 1,790 patient days. The inclusive MDR infection rate was 17.3/1,000 patient days. Also, Klebsiella pneumoniae (38.7%) was the commonest MDR pathogen. The commonest source of infection was BSI (32.3%). The risk factors associated with MDR infections were the length of stay in NSICU, mechanical ventilation of more than 5 days, emergency surgery, respiratory and cardiac comorbidities, and poor nutrition status (p < 0.05).

Conclusion

The MDR infection rate in our study was 17.3/1,000 patient days in pediatric patients. Also, K. pneumonia e was found to be the commonest MDR pathogen. Bloodstream was the commonest source of infection.

How to cite this article

Patel S, Prabhakar H, Kapoor I. Rate of Multidrug-resistance to Antimicrobial Drugs in Patients in Pediatric Neurointensive Care. Indian J Crit Care Med 2023;27(1):67-72.

Transmission of gram-negative antibiotic-resistant bacteria following differing exposure to antibiotic-resistance reservoirs in a rural community: a modelling study for bloodstream infections

Exposure to community reservoirs of gram-negative antibiotic-resistant bacteria (GN-ARB) genes poses substantial health risks to individuals, complicating potential infections. Transmission networks and population dynamics remain unclear, particularly in resource-poor communities. We use a dynamic compartment model to assess GN-ARB transmission quantitatively, including the susceptible, colonised, infected, and removed populations at the community-hospital interface. We used two side streams to distinguish between individuals at high- and low-risk exposure to community ARB reservoirs. The model was calibrated using data from a cross-sectional cohort study (N = 357) in Chile and supplemented by existing literature. Most individuals acquired ARB from the community reservoirs (98%) rather than the hospital. High exposure to GN-ARB reservoirs was associated with 17% and 16% greater prevalence for GN-ARB carriage in the hospital and community settings, respectively. The higher exposure has led to 16% more infections and attributed mortality. Our results highlight the need for early-stage identification and testing capability of bloodstream infections caused by GN-ARB through a faster response at the community level, where most GN-ARB are likely to be acquired. Increasing treatment rates for individuals colonised or infected by GN-ARB and controlling the exposure to antibiotic consumption and GN-ARB reservoirs, is crucial to curve GN-ABR transmission.

Mapping local variation in household overcrowding across Africa from 2000 to 2018: a modelling study

BACKGROUND

Household overcrowding is a serious public health threat associated with high morbidity and mortality. Rapid population growth and urbanisation contribute to overcrowding and poor sanitation in low-income and middle- income countries, and are risk factors for the spread of infectious diseases, including COVID-19, and antimicrobial resistance. Many countries do not have adequate surveillance capacity to monitor household overcrowding. Geostatistical models are therefore useful tools for estimating household overcrowding. In this study, we aimed to estimate household overcrowding in Africa between 2000 and 2018 by combining available household survey data, population censuses, and other country-specific household surveys within a geostatistical framework.

METHODS

We used data from household surveys and population censuses to generate a Bayesian geostatistical model of household overcrowding in Africa for the 19-year period between 2000 and 2018. Additional sociodemographic and health-related covariates informed the model, which covered 54 African countries.

FINDINGS

We analysed 287 surveys and population censuses, covering 78 695 991 households. Spatial and temporal variability arose in household overcrowding estimates over time. In 2018, the highest overcrowding estimates were observed in the Horn of Africa region (median proportion 62% [IQR 57-63]); the lowest regional median proportion was estimated for the north of Africa region (16% [14-19]). Overall, 474·4 million (95% uncertainty interval [UI] 250·1 million-740·7 million) people were estimated to be living in overcrowded conditions in Africa in 2018, a 62·7% increase from the estimated 291·5 million (180·8 million-417·3 million) people who lived in overcrowded conditions in the year 2000. 48·5% (229·9 million) of people living in overcrowded conditions came from six African countries (Nigeria, Ethiopia, Democratic Republic of the Congo, Sudan, Uganda, and Kenya), with a combined population of 538·3 million people.

INTERPRETATION

This study incorporated survey and population censuses data and used geostatistical modelling to estimate continent-wide overcrowding over a 19-year period. Our analysis identified countries and areas with high numbers of people living in overcrowded conditions, thereby providing a benchmark for policy planning and the implementation of interventions such as in infectious disease control.

FUNDING

UK Department of Health and Social Care, Wellcome Trust, Bill & Melinda Gates Foundation.

Bugs That Can Resist Antibiotics but Not Men: Gender-Specific Differences in Notified Infections and Colonisations in Germany, 2010-2019

Data from surveillance networks show that men have a higher incidence rate of infections with anti-microbial-resistant (AMR) pathogens than women. We systematically analysed data of infections and colonisations with AMR pathogens under mandatory surveillance in Germany to quantify gender-specific differences. We calculated incidence-rates (IR) per 100,000 person-years for invasive infections with Methicillin-resistant Staphylococcus aureus (MRSA), and for infections or colonisations with carbapenem-non-susceptible Acinetobacter spp. (CRA), and Enterobacterales (CRE), using the entire German population as a denominator. We limited the study periods to years with complete notification data (MRSA: 2010-2019, CRA/CRE: 2017-2019). We used Poisson regression to adjust for gender, age group, federal state, and year of notification. In the study periods, IR for all notifications were 4.2 for MRSA, 0.90 for CRA, and 4.8 for CRE per 100,000 person--years. The adjusted IR ratio for infections of men compared to women was 2.3 (95% confidence interval [CI]: 2.2-2.3) for MRSA, 2.2 (95%CI: 1.9-2.7) for CRA, and 1.7 (95%CI: 1.6-1.8) for CRE. Men in Germany show about double the risk for infection with AMR pathogens than women. This was also true for colonisations, where data were available. Screening procedures and associated hygiene measures may profit from a gender-stratified approach.