Antimicrobial Resistance & Infection Control

Objectives- Among clinical methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infection (BSI) strains, we sought to determine the prevalence of {beta}-lactam-{beta}-lactamase inhibitor (BLBLI) susceptibility, and its association with oxacillin susceptibility, genotypic factors, and patient characteristics. Methods- Clinical MRSA BSI strains were tested for susceptibility to penicillin-clavulanate by Etest (n=117, 36% of the dataset) and to oxacillin by disk diffusion assay (n=328, 100%). Penicillin-clavulanate susceptibility was defined as MIC [≤]2mg/L and oxacillin disk susceptibility as an inhibition zone > 6mm. All strains were whole-genome sequenced, and alleles of mecA annotated. The sensitivity and specificity of the oxacillin disk to predict penicillin-clavulanate 'susceptibility' were assessed. Clinical and genomic associations with BLBLI 'susceptibility' were assessed by calculating odds-ratios (OR). Results -We found 73/117 (62%) and 205/328 (62%) strains to be 'susceptible' to penicillin-clavulanate and oxacillin disk, respectively. Oxacillin disk susceptibility and penicillin-clavulanate susceptibility were highly correlated (sensitivity 97.3% and specificity 95.5%). We therefore used oxacillin disk susceptibility as a proxy for penicillin-clavulanate susceptibility. Comparative genomics of the mecA gene uncovered 8 alleles. The oxacillin disk 'susceptible' phenotype was associated with specific mecA alleles, community-associated MRSA sequence-types (OR 72.8, 95%CI 35.4-162), community acquisition of infection (OR 2.09, 95% CI 1.03-4.27), lower Charlson Comorbidity Index (OR 0.90, 95% CI 0.82-0.98) and SOFA (sequential organ failure assessment) scores at presentation (OR 0.88, 95% CI 0.79-0.98). Conclusion - BLBLI 'susceptibility' is common among MRSA strains and is strongly associated with the strain genotype. Infections caused by BLBLI 'susceptible' strains are associated with specific patients' characteristics, namely younger age, fewer comorbidities, acquisition in the community and milder presentations.

Importance: Antibiotic-resistant infections in neonates often arise from the infant's own colonizing bacteria harboring antibiotic resistance genes (ARG). This study evaluates ARG that impact antibiotic selection and drive resistance-related mortality, termed clinically important antibiotic resistance genes (CI-ARG). Objective: To determine differences in gut CI-ARG abundance in children from birth through 3 years old, stratified by neonatal intensive care unit (NICU) admission and antibiotic (abx) exposure in the first two months Design: Cohort study (sequencing, analysis completed 2025-2026) using shotgun metagenomic sequencing of stool samples from infants in two studies: Neonatal Intestinal Microbiome (+NICU groups, 2015-2022), The First 1000 Days of Life and Beyond (-NICU groups, 2018-2021). Infants grouped into four cohorts: +NICU/+abx, +NICU/-abx, -NICU/-abx, and -NICU/+abx. Prespecified CI-ARG abundance compared longitudinally among groups. Setting: NICU, well-baby nursery, Inova Fairfax Hospital, Virginia Participants: +NICU criteria: admission to the NICU, anticipated length of stay (LOS) of at least five days, maternal age at least 18 years. -NICU: parents with good general health and age at least 18 years enrolled prior to infant birth. Stool samples: adequate stool processing volume, at least one stool sample from before one month and after one year of age, 7-day minimum between serial samples. Exposures: NICU versus well-baby nursery; antibiotics versus none in first two months of corrected age Main Outcomes and Measures: Predefined primary outcome- longitudinal CI-ARG abundance by group, compared using linear mixed effects models with adjustment for multiple comparisons (Benjamini-Hochberg procedure). Predefined secondary outcomes- differences in overall microbiota and resistome composition. Results: 1000 serial stool samples, 179 infants (birth-39 months). Longitudinal abundance significantly differed among cohorts for 11 CI-ARG (p < 0.05); often higher in the +NICU groups in early life, with or without antibiotic exposure. Abundance of ARG conferring resistance to aminoglycosides, macrolides, and fluoroquinolones later decreased below -NICU levels. mecA, which often drives methicillin resistance in Staphylococcus, was detected only in +NICU infants during premature period. Conclusions: This longitudinal study demonstrates significant longitudinal CI-ARG differences in children grouped by early-life NICU status and/or antibiotic exposure. Future studies should explore the mechanisms driving these CI-ARG changes and evaluate their impact on infection risk and community spread.

Objectives To characterise COVID-19 inpatients with and without bacterial/fungal preceding, co- and secondary infections, and describe the distribution of organisms associated with COVID-19 and antibiotic use. Methods We linked ISARIC/WHO CCP-UK data from hospitals in England (admissions 01/01/2020-18/10/2021) with UK Health Security Agency infections datasets of COVID-19, and bacterial- and fungal-positive specimens using a multi-step hierarchical algorithm. We retained those aged >18 years and categorised COVID-19-associated infection as preceding (2-28 days prior to SARS-CoV-2 PCR positive date), co-infection ({+/-}1 day) or secondary (2-28 days after). Results During the study period, there were 173,947 hospitalised episodes of COVID-19; 5.8% (n=10,017) with a bacterial or fungal preceding, co- or secondary infection. Preceding and co-infections were rare (preceding: 0.7%; co-infection: 1.5%) while secondary infections were more common (3.5%). Escherichia coli (29.6%) and Staphylococcus aureus (15.2%) were the most identified organisms in blood specimens, while S. aureus (22.9%) and Pseudomonas aeruginosa (20.4%) were most common in lower respiratory tract specimens. The 28-day case fatality rate (CFR) remained static (36%) in those with secondary infection, whereas it decreased between early 2020 and mid-2021 in the other infection groups (37% to 27%). Of those with no positive microbiology, 72.8% received antibiotics, though this decreased between January-June 2020 (77.6%) and April-October 2021 (62.6%). Conclusion Bacterial and fungal infections complicated approximately 1-in-17 hospitalised episodes of COVID-19, with CFR of >25%. Antibiotic prescribing was common in those without firm evidence of bacterial infection. We recommend adhering to NICE guidance which discourages empirical antibiotic use for hospitalised COVID-19 patients.

Background: Half of US children are prescribed an antibiotic by age 2. Maternal education and socio-economic factors influence prescribing but the role of other factors, such as age of solid food introduction is unknown. Objectives: We assessed risk factors for time to first antibiotic use between birth to age 2 to identify modifiable drivers of antibiotic use. Methods: We analyzed interviews from mothers of 1032 children participating in the mother-child Center for Oral Health Research in Appalachia cohort 2 between 2011 and 2017. The cohort enrolled healthy, English-speaking, pregnant White women > 18 years with singleton pregnancies. We used time-to-event analyses and a Cox Proportional Hazards model to describe and estimate hazard ratios (HRs) for time to first antibiotic. Results: By age 2, 78% of children received at least one antibiotic (median age at first antibiotic: 12.5 months). Over half (58%) of antibiotics prescribed were for ear infections. After adjustment for household income and birth quarter as fixed variables, time of solid food introduction (aHR: 4.75; 95% CI: 3.19, 7.07), time of first ear infection (aHR: 3.28; 95% CI: 2.58,4.17), and time of first illness (aHR: 4.60; 95% CI: 3.32,6.36) were significantly associated with time of first antibiotic use. Conclusions: Earlier time of solid food introduction was associated with earlier antibiotic use. Childhood illnesses, especially ear infections, also strongly influence antibiotic initiation. These modifiable factors offer targets to reduce unnecessary early antibiotic use.

Background: Both over- and under-antibiotic use pose major global health challenges, yet there is no consensus on how to quantify deviations from optimal prescribing or set evidence-based targets. We developed a benchmarking tool for inpatient antibiotic use and evaluated its application in 10 countries. Methods: We developed decision-tree models to estimate expected empiric antibiotic use for 11 indications, based on the WHO AWaRe book for two age groups: 28 days to 12 years and >12 years. We parameterised the models using country-specific antimicrobial resistance estimates in the 10 countries and cross-sectional Global Point Prevalence Survey (Global-PPS) case-mix data from 2021 for 10 countries and from 2015-2022 in a subset of five countries. We then compared estimated expected antibiotic use with observed empiric use (from Global-PPS) in defined daily doses for adults and days of therapy for children, across indications and AWaRe categories. Findings: In 2021, among patients aged >12 years, in all countries but one, observed empiric Access antibiotic use, as a proportion of total antibiotic use, was lower than expected and empiric Watch antibiotic use was higher than expected. Similar patterns were observed in all countries but one in patients aged 28 days to 12 years. The magnitude of discrepancies between expected and observed Access and Watch antibiotic use varied across indications and countries. The median observed-to-expected ratios of usage across countries ranged from 0.3-0.8 for Access antibiotics, and 0.7-5.3 for Watch antibiotics in patients aged >12 years in 2021. Temporal trends from repeated surveys from 2015 to 2022 showed little change in observed-to-expected ratios for Access and Watch antibiotics. Interpretation: This benchmarking tool uses Global-PPS data to quantify differences between observed antibiotic use and WHO AWaRe recommendations. Our tool can be adaptable to local guidelines, provides policy-relevant estimates of expected antibiotic use to support monitoring, procurement planning, and targeted stewardship intervention.

Sepsis is a substantial contributor to neonatal mortality in Africa, with Klebsiella pneumoniae as the leading causative pathogen. Incorporating molecular tools such as whole genome sequencing (WGS) into routine surveillance of important bacterial pathogens, including those causing neonatal sepsis, can support targeted deployment of infection prevention and control measures and treatment interventions. This study aimed to understand the current practices and capacity for culture, identification and genomic analysis of bacterial pathogens in Africa, with a particular focus on K. pneumoniae, to support standardised genomic surveillance. A cross-sectional online survey was distributed to various clinician and scientist networks across Africa. All respondents completed a demographics section, while sections on laboratory test capacity, blood culture practices, WGS, and bioinformatics analysis were completed based on experience in these aspects. Responses were received from 52 institutions in 25 African countries. Among 51 institutions completing the laboratory test capacity section, 61% reported performing blood cultures, with the majority using manual commercial biochemical systems for species identification (71%) and manual disk diffusion for antibiotic susceptibility testing (82%). Participating institutions reported near-universal access to a -80{degrees}C freezer, centrifuge and thermocycler, but shaking incubators were less commonly available (67%). More than half of respondents (54%) indicated that they perform the entire WGS workflow (including DNA extraction, library preparation and WGS) internally, with most performing DNA extraction internally (88%) using column-based kits (70%). Outsourcing was progressively more common at later workflow stages. Infrastructure challenges that limit bioinformatics analysis capabilities were reported by all 23 respondents who completed this question, including limited access to high-performance computing and data storage space. This survey found sufficient capacity to support genomic surveillance of neonatal sepsis pathogens across participating African institutions. However, investments in blood culture, supply chains, sequencing, bioinformatics, and data dissemination capacity are needed to realise its full potential. These findings will support the development of standardised genomic surveillance protocols tailored to the diverse capacities of African laboratories.

Patient movement within and between hospitals creates a complex hospital network that facilitates the spread of antimicrobial-resistant bacteria and contributes to healthcare-associated infections. Yet most national-scale studies infer spread from aggregated hospital-to-hospital patient sharing, leaving patient-to-patient contact pathways and the role of routine patient mobility in shaping colonization risk poorly characterized. Using Frances 2023-2024 national hospital-discharge data, we reconstructed a temporal patient-based network of 10.4 million patients across 1,408 acute-care hospitals, comprising 326.6 million overnight ward co-location interactions. We simulated colonization over 365 days on the observed day-by-day temporal network using a stochastic susceptible-colonized-susceptible model, with a mean colonization duration of 180 days. We used national carbapenemase-producing Enterobacterales (CPE) surveillance data to calibrate differences in transmission risk across clinical settings. Across 2,000 simulations initiated on randomly selected dates in 2023, we calculated patient-level colonization probabilities and summarized risk across patients residential areas, wards, and hospitals. We further assessed hospital-level consistency between simulated risk and recorded CPE occurrence. Simulated risk was highly heterogeneous across patients and care settings. When mapped by place of residence, hospital-associated colonization risk showed strong spatial clustering in both urban and rural areas. Multivariable regression analyses identified patient- and hospital-level characteristics associated with heterogeneity in simulated colonization risk. Sensitivity analyses varying initial seeding and colonization duration showed that relative risk patterns remained highly stable. This nationwide framework shows how patient mobility and ward co-location patterns can reveal patterns of hospital-associated colonization risk and could support pathogen-specific surveillance and intervention evaluation. Significance StatementAsymptomatic carriage allows antimicrobial-resistant bacteria to spread through healthcare systems while colonized patients may remain unrecognized in the absence of active screening. We reconstructed a nationwide, time-resolved network of ward co-location among hospitalized patients in France. We accounted for differences in transmission risk across clinical settings using national surveillance data on carbapenemase-producing Enterobacterales. Using a transmission model, we characterized colonization-risk patterns and identified patient- and hospital-level features associated with variation in risk. This framework offers health authorities a way to examine where patient movement and hospital care may contribute to concentrations of colonization risk, although pathogen- and context-specific adaptation and evaluation remain necessary to guide surveillance or interventions. Author contributionsS.B., L.C., L.T., A.K., T.D., V.C., and P.C. designed research; S.B. and P.C. performed research; S.B. and P.C. analyzed data; S.B. and P.C. wrote the paper; all authors reviewed and edited the final manuscript.

Background Clostridioides difficile infections (CDI) continue to cause substantial morbidity and mortality, with increasing incidence in some countries post-COVID-19. Recurrence affects 10-20% of CDI patients: whether risk factors have changed over time is unclear, particularly post-COVID-19. Methods Using electronic health records from hospitals in Oxfordshire, UK, including results from community samples, we estimated the incidence of CDI recurrence across different calendar periods between 2000-2025. To investigate whether risk factors had changed over time, we used interaction tests within multivariable Fine-Gray regression models (modelling death as a competing risk), using backwards elimination, starting from 39 risk factors identified from the literature. Results Recurrence occurred within 1-year in 12.6%, 12.5%, 10.8% and 13.1% of CDI cases in "high virulence" 2003-2008 (n=527), "post-high virulence" 2008-2012 (n=252), "pre-pandemic" 2012-2020 (n=143) and "post-pandemic" 2020-2025 (n=110) periods respectively. The only factor with evidence of variation in its association with recurrence over time was surveillance classification (heterogeneity p=0.019; others p>0.05). Compared with hospital-onset cases, community-onset community-associated cases had increasing recurrence risks over time (subdistribution hazard ratios (SHRs)=2.05 (95% CI 1.27-3.31) in "post-pandemic" and 1.86 (1.16-2.98) in "pre-pandemic"), especially compared to the "high virulence" era of the early 2000s (SHR=0.81 (0.56-1.16)). This heterogeneity persisted after adjusting for baseline blood tests as a marker of severity (heterogeneity p=0.022). Conclusions Compared with hospital-onset hospital-associated cases, recurrence risks increased for community-onset community-associated CDI cases over time. Recurrence is a key contributor to overall CDI incidence and the underlying causes of increasing risks with community-onset community-associated cases should be explored further.

To characterise temporal changes in antimicrobial resistance (AMR) among clinically important bacterial pathogens in Iraq during 2021-2024 and examine their implications for empirical antimicrobial therapy and stewardship. We conducted a retrospective longitudinal analysis of aggregated national AMR surveillance data for Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus. Annual resistance proportions were evaluated across clinically relevant antimicrobials. Temporal change was characterised using absolute percentage-point changes and exploratory linear regression. Resistance trajectories were interpreted in relation to empirical treatment options and antimicrobial stewardship. The analysis included 92,338 organism records: 40,496 (43.9%) E. coli, 24,621 (26.7%) S. aureus, 18,223 (19.7%) K. pneumoniae and 8,998 (9.7%) P. aeruginosa. In 2024, ceftriaxone resistance reached 82.9% in E. coli and 65.2% in K. pneumoniae, while ciprofloxacin resistance was 55.4% and 57.9%, respectively. Meropenem resistance reached 37.4% in K. pneumoniae and 62.3% in P. aeruginosa. Conversely, resistance declined for amoxicillin-clavulanate in E. coli (83.5% in 2021 to 57.2% in 2024) and piperacillin-tazobactam in P. aeruginosa (46.4% to 32.9%). Several pathogen-antimicrobial combinations showed marked year-to-year variation, and no temporal trend remained statistically significant after false discovery rate correction. Resistance to several agents central to empirical therapy remains high in Iraq, while substantial carbapenem resistance constrains reliance on carbapenem escalation when resistance to other {beta}-lactams is suspected. Heterogeneous trajectories indicate that empirical recommendations should not rely on single-year national antibiograms alone and support regular integration of national and local resistance surveillance into empirical treatment and antimicrobial stewardship strategies.

Background Neonatal sepsis remains a major cause of neonatal morbidity and mortality, particularly in low- and middle-income countries. Its management is increasingly complicated by antimicrobial resistance (AMR), while limited facility-specific data on causative bacterial pathogens and susceptibility patterns often necessitate empirical antibiotic treatment. This study assessed the prevalence of neonatal sepsis, bacterial pathogens and antimicrobial resistance patterns, and maternal, neonatal and clinical factors associated with neonatal sepsis among neonates admitted to the Neonatal Intensive Care Unit (NICU) at Livingstone University Teaching Hospital (LUTH), Zambia. Methods A retrospective cross-sectional record review was conducted among neonates admitted to the NICU at LUTH from 2020 to 2025. A total of 150 neonatal records were analysed. Neonatal, maternal, clinical, blood culture and antimicrobial susceptibility data were analysed using descriptive statistics, chi-square tests and logistic regression. Missing information was treated as missing and was not imputed; denominators were reported according to the records available for each analysis. Results Neonatal sepsis was identified in 52/150 neonates, giving a prevalence of 34.7% (95% CI: 27.5%-42.6%). Among the 52 sepsis cases, 20 had positive blood cultures, corresponding to a culture positivity rate of 38.5% (95% CI: 26.5%-52.0%); this represented 13.3% of the full study sample. Maternal fever during labour (aOR=6.822; 95% CI: 2.032-22.905; p=0.002) and caesarean delivery (aOR=2.245; 95% CI: 1.050-4.801; p=0.037) were independently associated with neonatal sepsis, while increasing birth weight was protective (aOR=0.891 per 100 g; 95% CI: 0.817-0.973; p=0.010). Escherichia coli was the most frequent isolate (5/20; 25.0%), followed by Klebsiella pneumoniae (4/20; 20.0%) and Staphylococcus aureus (4/20; 20.0%). Resistance was highest to ampicillin (15/19; 78.9%), followed by gentamicin and ceftriaxone (10/19; 52.6% each), while all 19 isolates tested against meropenem were susceptible. Conclusion The findings indicate that empirical management of neonatal sepsis at LUTH should be informed by local microbiological surveillance rather than reliance on historical first-line susceptibility assumptions. Routine blood culture and susceptibility testing, a regularly updated facility antibiogram, strengthened infection prevention and antimicrobial stewardship are required to improve treatment decisions and preserve effective antibiotics. Interpretation should consider the retrospective single-centre design, incomplete routine records and the small number of culture-positive isolates.

Background: Optimising sampling frames for genomic surveillance of E. coli and Klebsiella may support interventions to mitigate bloodstream infections (BSIs), but approaches to estimating sample size and how these relate to bacterial population diversity at multiple genetic levels (strain/plasmid/antimicrobial resistance genes [ARGs]) are lacking. Methods: Using systematically collected, regionally-stratified, whole genome sequencing data from a 6-month genomic survey of English E. coli/Klebsiella BSI isolates (n=1,939; NEKSUS), we used Bayesian approaches to estimate the sample sizes required to capture genetic diversity at strain- (MLST, fastBAPS clusters), plasmid- and ARG-levels, using two diversity measures: 'coverage' (i.e. proportion of the bacterial population/plasmids/ARGs represented by features observed in the sample), and the number/proportion of unique features observed at varying surveillance sample sizes. Our method is available as a user-friendly R Shiny application, EpiSENTRY (https://01a0c3dd-90d2-e597-58a5-51391a468387.share.connect.posit.cloud/). Findings: Randomly sampling 1,400 E. coli/Klebsiella BSI isolates each achieved [&ge;]80% coverage of bacterial lineages and ARGs (i.e. capture features constituting [&ge;]80% of the population) at 95% certainty, but captured lower proportions of unique features (28% MLSTs, 59% fastBAPS clusters, 19% plasmid subcommunities, and 57% ARGs for E. coli; 49%, 87%, 50% and 83% for Klebsiella, respectively). Sample sizes required for 80% coverage of E. coli plasmid populations were higher than MLSTs (1,928 [95% CrI: 1,837-2,025] vs 1,351 [1,230-1,472]), while for Klebsiella, estimates were lower for plasmids (1,115 [1,052-1,181] vs 1,422 [1,331-1,515] for MLSTs). Lower sample sizes adequately captured 80% coverage of fastBAPS clusters and ARGs (649 [575-727] and 27 [23-30], respectively, for E. coli; 113 [84-145] and 83 [72-96] for Klebsiella), due to feature-specific frequency distributions. Klebsiella BSIs were more diverse than E. coli, with sampling 10.9% vs 3.2% of total annual BSIs in England needed to reach 80% MLST coverage. Plasmid populations and Klebsiella MLSTs were region-specific, emphasising the need for regionally-representative sampling. Interpretation: Bayesian analysis facilitates estimates of context-specific genomic surveillance sample sizes. Cost-effective targets for coverage require further optimisation.

BackgroundFebrile neutropenia requires rapid empirical antibiotic therapy, with regimen selection shaped by local prescribing practice and pathogen patterns. We described starting treatment, later drug changes, microbiological findings, and inpatient outcomes. MethodsThis ambispective cohort comprised 96 episodes from 90 patients admitted to a tertiary-level teaching hospital. Treatment and outcome analyses used each episode as the unit of observation. Recorded variables included the starting antibiotics, later regimen modification, microbiology, hospitalization length, invasive fungal infection (IFI) as captured in study records, and disposition. Comparisons based on escalation status were exploratory. ResultCefoperazone-sulbactam appeared in 62/96 initial regimens (64.6%), amikacin in 42 (43.8%), teicoplanin in 28 (29.2%), and meropenem in 14 (14.6%). Eighteen episodes (18.8%) required a change that broadened or substituted antibacterial therapy. Among 31 microbiologically documented infections, 22 (71.0%) yielded Gram-negative organisms and 9 (29.0%) were polymicrobial. Median length of admission was 18.5 days in the escalation group and 9 days in the remainder (p<0.001). Mortality was 27.8% (5/18) with escalation and 5.1% (4/78) without it (p=0.011), with nine inhospital deaths overall (9.4%). ConclusionAntibacterial management differed within this cohort, with treatment escalation required in 18 of 96 episodes. Gram-negative organisms comprised most microbiologically confirmed infections. Escalation marked a clinically complex course with prolonged hospitalization and greater observed mortality; the observational design does not establish comparative efficacy or causation.

Hospital-based surveillance captures important components of antimicrobial resistance in India, but community-facing data linking prescribing and resistance remain limited. To address this, we analysed routinely generated prescription and diagnostic data from Tata 1mg from 2023 to 2025. Among 25.7 million medicines prescribed, 10.8% were antibiotics, with Watch antibiotics exceeding Access antibiotics in every state meeting the inclusion criteria. Among 156,000 diagnostic microbiology samples, urine cultures predominated, with Escherichia coli accounting for 60.6% of culture-positive isolates. In urinary E. coli, resistance was low to the Access antibiotics nitrofurantoin and amikacin (4.9% each), but high to the Watch antibiotics ceftriaxone (53.6%) and ciprofloxacin (57.0%). Exploratory cross-correlation analyses identified lead-lag relationships in which resistance to selected Watch antibiotics preceded changes in resistance to Access antibiotics by approximately 3-6 months. Routine digital healthcare data can therefore support community-facing AMR surveillance by jointly characterising platform-recorded prescribing and susceptibility within the observed care pathway.

Objective. To identify antimicrobial stewardship targets by triangulating provider knowledge and practice, government-facility prescribing indicators and patient-reported treatment experience in three districts of Chhattisgarh, India. Methods. We analysed three independently sampled cross-sectional components: a provider survey (171 providers), a World Health Organization and International Network for Rational Use of Drugs assessment (600 encounters at 20 government facilities) and patient exit interviews (371 consultations). We used descriptive indicators and multivariable ordinal or binary logistic regression. Findings. Among providers, 149 of 163 (91.4%) recognized antimicrobial resistance, but 131 of 163 (80.4%) reported providing antibiotics for colds or sore throats to at least some patients. Guideline familiarity was not associated with less frequent provision (adjusted common odds ratio [aOR], 1.13; 95% confidence interval [CI], 0.57-2.24; P=0.725). Government facilities prescribed antibiotics in 329 of 600 encounters (54.8%), with a facility range of 16.7-80.0%. In exit interviews, 131 of 142 informal-provider consultations (92.3%) involved a reported injection; informal providers accounted for 131 of 181 reported injections (72.4%). Clear or very clear instructions were associated with satisfaction (aOR: 13.66; 95% CI: 6.37-29.28; P<0.001). Conclusion. High awareness coexisted with frequent self-reported antibiotic provision, wide facility variation and sector-specific injection exposure. Stewardship programmes should diagnose local drivers before selecting interventions and prospectively evaluate adapted decision support, audit and feedback, independent drug information, informal-provider engagement and communication training.

Background. Skilled healthcare workers are essential for neonatal survival; however, the Kenyan public health system has historically faced strikes compounded by a human resource crisis. Evidence on how strikes affect neonatal care and mortality remains limited. This study evaluated changes in neonatal admissions, clinical care processes, and inpatient mortality associated with 56 days of disruption during the 2024 Kenyan physicians' strike. Methods. We conducted a retrospective interrupted time-series analysis of 12,184 admissions to 11 Kenyan neonatal units implementing with the NEST360 Alliance, recorded in the Neonatal Inpatient Dataset from December 2023 to August 2024. Weekly admissions and inpatient mortality were modeled over a 72-week window (27,638 admissions) using hospital-clustered generalized estimating equations with seasonal terms. Care processes, case fatality, and birthweight-specific mortality were compared across study periods. Results. Weekly admissions fell from 413 to 189 during the strike (incidence rate ratio (IRR) 0.49, 95% confidence interval (CI) 0.31-0.75), approximately 1,700 fewer admissions than expected, and returned to baseline afterward (IRR 1.00, CI 0.81-1.23). Newborns admitted during the strike were of lower birthweight, more often premature, and more often outborn. Admissions fell across all birth-location categories, most steeply among inborn neonates. No measurable change was detected in documented inpatient coverage of care measures, in crude mortality (12.5% to 14.9%; risk ratio (RR) 1.07, CI 0.85-1.33), or in trend-adjusted mortality (IRR 0.88, CI 0.53-1.45). Case fatality among neonates with recorded infection doubled, from 4.7% to 9.6% (RR 2.06, CI 1.18-3.58; adjusted p = 0.047). Conclusions. The 2024 physicians' strike was associated with severe disruption to neonatal service utilization, with admissions returning to baseline when the strike ended. Among newborns who continued to reach care, inpatient mortality did not change measurably, but case fatality among those with recorded infection doubled. This analysis was confined to inpatient data; hence, the outcomes of newborns who did not reach the hospitals were not captured. Both inpatient and population-level data are needed to assess the full impact of the strike. Mitigating harm during future labor disruptions requires interventions such as resilient care models, formalized task-shifting protocols, and minimum service coverage agreements.

Introduction Bubble Continuous Positive Airway Pressure (bCPAP) is an effective intervention for managing respiratory distress syndrome among preterm newborns. However, its successful utilization depends on healthcare providers possessing adequate knowledge and practical skills. In Tanzania, competency-based equipment user training has been introduced to strengthen providers' capacity to use neonatal technologies, including bCPAP. Despite these efforts, there is limited qualitative evidence on how this training influences healthcare providers' competence and routine clinical practice. This study explored the role of competency-based equipment user training in enhancing healthcare providers' skills in utilizing bCPAP devices for newborn care in Dar es Salaam, Tanzania. Methods A phenomenological qualitative study was conducted in three regional referral hospitals implementing the NEST360 programme. Purposive sampling was used to recruit doctors and nurses who had completed competency-based equipment user training. Data were collected through in-depth interviews using a semi-structured interview guide and analysed using Braun and Clarke's thematic analysis approach. Findings Six major themes emerged. Participants described competency-based training as a great approach for improving practical skills, confidence, and clinical decision-making regarding patient selection, device operation, monitoring, and weaning. Participants also reported improved equipment maintenance practices, reduced preventable equipment damage, and stronger collaboration with biomedical engineering professional . The training promoted positive changes in provider behaviour, including greater autonomy, internal mentorship of newly recruited staff, and increased accountability for equipment management. Participants further perceived improvements in neonatal care through earlier initiation of bCPAP, fewer unnecessary referrals, and better management of preterm newborns within their facilities. Conclusion Competency-based equipment user training strengthened healthcare providers' competence and confidence in utilizing bCPAP for newborn care while improving equipment management and interdisciplinary collaboration. Integrating competency-based training into routine newborn care programmes may enhance the effective implementation and sustainability of life-saving neonatal technologies in resource-limited settings.

Background: Non-optimal air temperature increases the risk of preterm birth, but how temperature-related risks may translate into future population burden remains uncertain. We aimed to estimate the association between temperature and preterm birth in Sweden and assess how preterm birth burden may change under plausible future temperature conditions. Methods: We conducted a nationwide population-based cohort study of singleton births in Sweden from 1973 to 2018. Weekly mean temperature was assigned at the parish level according to maternal residence. Cox proportional hazards models with a distributed lag nonlinear model were used to estimate nonlinear and delayed associations between temperature and preterm birth. The estimated exposure response relationship and baseline hazards were then incorporated into an individual-based microsimulation of gestational progression under projected temperatures for 2025 to 2055. Future projections were examined across multiple climate models under SSP1-2.6 and SSP3-7.0 scenarios. Outcomes included the annual number and cumulative incidence of preterm births and the temperature-attributable fraction. Results: Among 4,338,825 singleton births, 211,397 (4.9%) were preterm. Temperature preterm birth associations were modest overall. The clearest increase in hazard was observed following exposure to very low temperatures, particularly -10C at short lags. Higher temperatures showed no clear increase in risk. From 2025 to 2055, the annual cumulative incidence of preterm birth and the temperature-attributable fraction was expected to remain broadly stable, with limited differences between emissions scenarios. In contrast, the absolute number of preterm births was expected to over the projection period, primarily reflecting increases in the projected number of pregnancies rather than substantial changes in temperature-associated risk. Conclusions: Very low temperatures were associated with a modest short-term increase in preterm birth risk in Sweden, hot temperatures showed little evidence of increased risk. Applying these associations to future climate conditions suggested limited changes in preterm birth incidence or the proportion attributable to temperature through 2055. However, the absolute burden of preterm birth may increase as the population at risk grows. This highlights the importance of considering demographic change alongside climate projections when assessing future maternal and neonatal health burden.

Purpose: To compare the efficacy and safety of intravenous cefazolin versus antistaphylococcal penicillins for the treatment of MSSA bacteremia in adults using evidence exclusively from randomized controlled trials. Methods: We searched 5 databases for RCTs comparing definitive intravenous cefazolin with ASPs (oxacillin, cloxacillin, flucloxacillin, nafcillin) in adults with MSSA bacteremia. Primary outcomes were 90-day all-cause mortality and acute kidney injury (AKI). Secondary outcomes included adverse event-related treatment discontinuation and persistent bacteremia (>72h). Dichotomous outcomes were synthesized as risk ratios (RRs) with 95% confidence intervals (CIs) using random-effects models with Paule-Mandel estimation and Hartung-Knapp-Sidik-Jonkman inference. Fixed-effect Mantel-Haenszel models were performed as sensitivity analyses. Results: Two RCTs randomized 1,656 participants (SNAP, n = 1,341; CloCeBa, n = 315), of whom 1,579 contributed to the 90-day mortality analysis. There was no statistically significant difference in 90-day mortality (RR 0.90, 95% CI 0.57-1.41; I2 = 0%). Both trials favoured cefazolin for acute kidney injury, but the random-effects estimate was highly imprecise (RR 0.26, 95% CI 0.00-939,970.59; I2 = 81.7%). Treatment discontinuation also favoured cefazolin directionally, although the random-effects estimate was imprecise (RR 0.24, 95% CI 0.00-24.41; I2 = 36.2%). Microbiological outcomes were synthesized narratively because definitions and assessment time points differed between trials. Conclusion: Randomized evidence supports cefazolin as a potential definitive treatment option when adequate source control, appropriate antimicrobial dosing, and clinical monitoring can be achieved. However, the limited number of trials and imprecision in pooled estimates warrant cautious interpretation.

Introduction Medicines account for 20% of the National Health Service (NHS) carbon footprint, but it is unclear how consistently they are measured by individual NHS trusts. This study assessed medicine carbon footprint (MCF) practices across NHS trusts in England and whether these changed between 2021 and 2024. Methods Freedom of Information requests were sent to NHS trusts about MCF practices in 2021 and 2024. Responses were analysed to determine the proportion of trusts calculating MCFs, the medicines included and the emission factors used for spend-based calculations. Reported spend-based factors were compared with the median factor for each year to assess the effect of factor choice on MCFs. Results Of 196 trusts included in analysis, 178 (91%) responded for 2021 and 182 (93%) for 2024. Among responding trusts, 30 of 178 calculated MCFs in 2021 compared with 46 of 182 in 2024. Spend-based medicine footprinting increased from 19 trusts in 2021 to 31 in 2024. Ten different factors were used by 15 trusts in 2021 and 13 by 21 trusts in 2024. Reported factors ranged from 31% below to 258% above the median in 2024. Conclusions Medicine carbon footprinting remained uncommon, with only one-quarter of responding NHS trusts calculating a footprint in 2024. Among trusts using spend-based methods, wide variation in emission factors produced substantially different estimated MCFs. Clear national guidance on spend-based methodology could improve consistency in the short term, while greater use of standardised product-level approaches may better support medicine decarbonisation over time.

Antimicrobial resistance (AMR) is a major threat to modern medicine and an emerging environmental pollutant. Wastewater-based monitoring offers a scalable alternative to traditional surveillance by enabling population-level monitoring across One Health compartments. However, it remains unclear how well bacterial variants detected in wastewater reflect those causing clinical infections. Here, we assessed the prevalence of carbapenem-resistant Escherichia coli (CREC) in wastewater from Uppsala, Sweden, and compared wastewater isolates with clinical isolates from the same region and period. We observed partial overlap between wastewater and clinical CREC populations, but several common clinical variants were not detected in wastewater and vice versa. CREC prevalence was an order of magnitude higher in wastewater receiving hospital effluent, yet this did not improve concordance with clinical isolates, suggesting that hospital wastewater may artificially inflate CREC prevalence estimates. These findings indicate that wastewater CREC prevalence does not necessarily reflect the regional clinical burden. Furthermore, metagenomic sequencing of wastewater-derived E. coli populations rarely detected CREC resistance genes, suggesting that CREC abundance is below the detection limit of this approach and that targeted enrichment is required for reliable monitoring. Together, our results show that while wastewater-based monitoring can complement AMR surveillance, it should be interpreted cautiously when used as an indicator of clinical risk.