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This year, the Pint of Science festival in Thailand is in not one but two cities! Join us in Bangkok at WeLearn on 21st-22nd May, and at Hungry Wolf's in Chiang Rai on 25th May.
Vaccine effects on in-hospital COVID-19 outcomes.
Here, we posit that studies comparing outcomes of patients hospitalized with COVID-19 by vaccination status are important descriptive epidemiologic studies, but contrast two groups that are not comparable with regard to causal analyses. We use the principal stratification framework to show that these studies can estimate a causal vaccine effect only for the subgroup of individuals who would be hospitalized with or without vaccination. Further, we describe the methodology for, and present sensitivity analyses of, this effect. Using this approach can change the interpretation of studies only reporting the standard analyses that condition on observed hospital admission status - that is, analyses comparing outcomes for all hospitalised COVID-19 patients by vaccination status.
Prevalence of hepatitis B virus infection among pregnant women and cord blood hepatitis B surface antigen positive newborns in sub-Saharan Africa and South Asia
Background: Newborns infected with Hepatitis B Virus (HBV) are at risk of chronic liver disease and hepatocellular carcinoma. Objectives: This study investigated the prevalence of HBV infection among pregnant women and cord blood Hepatitis B surface antigen (HBsAg) positivity of their newborns in Bangladesh, Bhutan, India, Ethiopia, Mozambique, Kenya, Nigeria, Mali, and South Africa. Study design: Randomly selected paired maternal and cord blood samples (n = 101 each site) taken at delivery were tested for HBsAg and Hepatitis B extractable antigen (HBeAg) in the women using a chemiluminescent microparticle immunoassay. Similarly, cord blood sample of newborn was assessed for HBsAg reactivity. HBV DNA was quantified using the Xpert® HBV viral load assay, followed by genotyping. Results: The overall prevalence of maternal HBsAg positivity was 5.5 % (95 %CI: 0.4 %–7.1 %; n = 50/909). HBsAg positivity was higher in African countries (7.3 %; 95 %CI: 5.4 %–9.6 %; n = 44/606) compared to South Asian countries (2.0 %; 95 %CI: 0.8 %–4.3 %; n = 6/303; p = 0.002). Relative to South Africa, there were higher odds of HBsAg sero-positivity in women from Mozambique ((aOR): 7.7, 95 %CI: 1.6 %–37.8 %) and Mali (aOR: 5.7; 95 %CI: 1.1 %–29.7 %). The rate of HBsAg positivity in cord blood of babies born to HBsAg positive women was 28.0 % (95 %CI: 17.1 %–42.3 %; n = 14/50), including 31.8 % (95 %CI: 19.5–47.4 %; n = 14/44) in African countries. No cord blood HBsAg positivity was observed in South Asia. Genotypic analysis revealed HBV genotypes A (41.7 %) and E (58.3 %) were pre-dominant. Conclusion: The high rate of cord blood positivity (28.0 %) for HBsAg underscores the urgency of enhancing HBV prevention strategies to meet the World Health Organization's target of a 90 % reduction in new HBV infections by 2030.
Using the microbiota to study connectivity at human–animal interfaces
Interfaces between humans, livestock, and wildlife, mediated by the environment, are critical points for the transmission and emergence of infectious pathogens and call for leveraging the One Health approach to understanding disease transmission. Current research on pathogen transmission often focuses on single-pathogen systems, providing a limited understanding of the broader microbial interactions occurring at these interfaces. In this review, we make a case for the study of host-associated microbiota for understanding connectivity between host populations at human–animal interfaces. First, we emphasize the need to understand changes in microbiota composition dynamics from interspecies contact. Then, we explore the potential for microbiota monitoring at such interfaces as a predictive tool for infectious disease transmission and as an early-warning system to inform public health interventions. We discuss the methodological challenges and gaps in knowledge in analyzing microbiota composition dynamics, the functional meaning of these changes, and how to establish causality between microbiota changes and health outcomes. We posit that integrating microbiota science with social-ecological systems modeling is essential for advancing our ability to manage health risks and harness opportunities arising from interspecies interactions.
Inclusion of under-served groups in trials: an audit at a UK primary care clinical trials unit
Abstract Background Clinical trials need to include patients who are representative of the population who may receive the tested interventions in the future. The importance of inclusivity is recognised by ethical and funding bodies and has public support. Appropriate inclusion is required to provide equitable evidence-based healthcare and to comply with ethical principles for research. However, there is little information about the inclusivity of most under-served groups in UK clinical trials. Methods This audit assesses the inclusion of under-served groups in trials run by the Oxford Primary Care Clinical Trials Unit (PC-CTU). We included trials with ethical approval between 2017 and 2023. We checked protocols, patient-facing information and selected data collection tools for information on the under-served groups in the INCLUDE guidance and protected characteristics in the UK Equality Act 2010, to identify explicit exclusions and data collection. Results We included 19 trials. They were in a variety of clinical conditions, testing different types of interventions, both Clinical Trial of an Investigational Medicinal Product (CTIMP) and non-CTIMP. Most were non-commercially funded. We reviewed 21 protocols, 29 Patient Information Sheets/Leaflets and 40 data collection tools. Common exclusions were based on age (19), sex or gender (11), language (8), capacity to consent (14), pregnancy (11), multiple health conditions (10) and severity of illness (17). Trials most often collected data on age (19), sex or gender (15), ethnicity (16), education (11), address (13), mental health conditions (6), who gave consent (19), addiction (6), multiple health conditions (10), severity of illness (17), smoking status (12) and obesity (13). Conclusions Often, exclusions were due to the focusing of the trial for a specific group, such as older people, women, or people being treated for a specific severity of condition. However, many explicit exclusions may not have been essential, may have reduced the inclusivity of the trials and might limit the applicability of the trial’s findings to people to whom the tested interventions might be relevant. These include the exclusion of people aged under 18, people without English language fluency and people without capacity to consent. All trials could have collected more informative data on under-served group status.
Piloting the options assessment toolkit with national malaria programme leaders from the Asia-Pacific countries: a meeting report.
Plasmodium vivax malaria remains a major challenge in the Asia-Pacific region, where National Malaria Programmes (NMPs) will need to determine optimal radical cure strategies given the availability of novel options, such as high-dose primaquine and tafenoquine. The Options Assessment Toolkit (OAT) was developed to assist NMPs to make decisions on the optimal combination of G6PD testing and radical cure drug regimen. This study reports on the piloting of OAT with NMP representatives during the APMEN Vivax Working Group Annual Meeting in December 2022. A total of 23 NMP representatives from 13 Asia-Pacific countries participated in facilitated discussions. Thematic analysis of qualitative data revealed that NMPs found the OAT useful and timely for structuring malaria policy discussions. However, concerns were raised regarding mismatches between OAT-generated scenarios and country-specific contexts, the inclusion of political and economic factors, and the feasibility of implementing expert-suggested options. Many NMPs expressed enthusiasm for single-dose tafenoquine, but preferred to await WHO recommendations before considering policy changes. Overall, the OAT was well received as a tool for initiating policy discussions on P. vivax radical cure. The OAT represents an important step toward accelerating evidence-based policy change in malaria-endemic countries, with further refinements enhancing its utility.
Why should we be concerned by internalised racism in global health?
Internalised racism constitutes an adoption of beliefs about one's inferiority, weaknesses or shortcomings as a function of racial hierarchy affecting one's identity and self-worth, thoughts, emotions and behaviours. Internalised racism stems from widely known and discussed institutional racial discrimination, which perpetuates epistemic injustice, social injustice and health inequities in global health. In this article, reflecting on our experiential knowledge from working on global health, we engage with relevant literature to (1) highlight the concepts associated with internalised racism, (2) explore the potential impacts of internalised racism on individuals, organisations and global health and (3) propose strategies to redress and mitigate its impact on global health practice.
Spatial distribution and population structure of the invasive Anopheles stephensi in Kenya from 2022 to 2024.
This study analyzes the distribution, genetic diversity, and spread of Anopheles stephensi in Kenya following initial detection in December 2022. A total of 114 larval and 33 adult An. stephensi samples were confirmed in 7 of 18 surveyed counties majorly along transportation routes. Genetic analyses revealed three distinct genetic compositions with different levels of genetic diversity, suggesting multiple introductions into the country. The genetic composition of mosquitoes in most counties resembled southern Ethiopian populations, while those from Turkana showed a unique haplotype. A species distribution model predicts a more extensive range than currently observed, with low precipitation and minimal seasonal temperature variations as key factors influencing distribution. Challenges in adult sampling were noted, with larval sampling revealing co-occurrence with native Anopheles species. The findings have implications for surveillance and control strategies, emphasizing the need for continued monitoring, refined sampling techniques to inform bionomics, and cross-border collaboration.
Iron deficiency causes aspartate-sensitive dysfunction in CD8+ T cells.
Iron is an irreplaceable co-factor for metabolism. Iron deficiency affects >1 billion people and decreased iron availability impairs immunity. Nevertheless, how iron deprivation impacts immune cell function remains poorly characterised. We interrogate how physiologically low iron availability affects CD8+ T cell metabolism and function, using multi-omic and metabolic labelling approaches. Iron limitation does not substantially alter initial post-activation increases in cell size and CD25 upregulation. However, low iron profoundly stalls proliferation (without influencing cell viability), alters histone methylation status, gene expression, and disrupts mitochondrial membrane potential. Glucose and glutamine metabolism in the TCA cycle is limited and partially reverses to a reductive trajectory. Previous studies identified mitochondria-derived aspartate as crucial for proliferation of transformed cells. Despite aberrant TCA cycling, aspartate is increased in stalled iron deficient CD8+ T cells but is not utilised for nucleotide synthesis, likely due to trapping within depolarised mitochondria. Exogenous aspartate markedly rescues expansion and some functions of severely iron-deficient CD8+ T cells. Overall, iron scarcity creates a mitochondrial-located metabolic bottleneck, which is bypassed by supplying inhibited biochemical processes with aspartate. These findings reveal molecular consequences of iron deficiency for CD8+ T cell function, providing mechanistic insight into the basis for immune impairment during iron deficiency.
Research Electronic Data Capture (REDCap) for Population-Based Data Collection in Low- and Middle-Income Countries: Opportunities, Challenges, and Solutions.
Health research requires high-quality data, and population-based health research comes with specific opportunities and challenges for data collection. Electronic data capture can mitigate some of the challenges of working with large populations in multiple, sometimes difficult-to-reach, locations. This viewpoint paper aims to describe experiences during the implementation of two mixed methods studies in Vietnam, Nepal, and Indonesia, focusing on understanding lived experiences of the COVID-19 pandemic across 3 countries and understanding knowledge and behaviors related to antibiotic use in Vietnam. We present the opportunities, challenges, and solutions arising through using Research Electronic Data Capture (REDCap) for designing, collecting, and managing data. Electronic data capture using REDCap made it possible to collect data from large populations in different settings. Challenges related to working in multiple languages, unstable internet connections, and complex questionnaires with nested forms. Some data collectors lacked the digital skills to comfortably use REDCap. To overcome these challenges, we included regular team meetings, training, supervision, and automated error-checking procedures. The main types of errors that remained were incomplete and duplicate records due to disruption during data collection. However, with immediate access to data, we were able to identify and troubleshoot these problems quickly, while data collection was still in progress. By detailing our lessons learned-such as the importance of iterative testing, regular intersite meetings, and customized modifications-we provide a roadmap for future projects to boost productivity, enhance data quality, and effectively conduct large-scale population-based research. Our suggestions will be beneficial for research teams working with electronic data capture for population-based data.
Clinicians’ use of metaphoric language in conversations with families of critically ill patients in the intensive care unit
Objectives: During conversations with families of critically ill patients in intensive care units (ICUs), clinicians’ metaphoric language use may facilitate families’ understanding, but also has potential drawbacks. We sought to obtain insights regarding how ICU clinicians use metaphors regarding patients’ disease and treatment trajectory. Methods: We identified clinicians’ metaphor use in N=101 audio-recorded neonatal, pediatric, and adult ICU family conversations about life-sustaining treatments. Using qualitative content analyses, each metaphor's semantic domain, disease phase, and dialogical function were coded. Overarching themes and patterns were analyzed. Results: Journey metaphors (N = 140 in N = 54 conversations) most frequently referred to the semantic domains boundary, path and bridge. Although most functioned to convey clinical information (72 %), metaphors were mainly presented in an emotionally charged way, serving to manage families’ perceptions. As patients’ conditions deteriorated, metaphors more often functioned to prepare families for medical limits. Metaphors were sometimes potentially unclear. Others suggested high patient agency, starkly contrasting with patients’ unconscious state. Conclusions: Metaphors related to ICU patients’ disease and treatment trajectory are common. They may clarify information or strengthen clinicians’ arguments but can also cause confusion and thereby hinder decision-making. Practice implications: Enhancing clinicians’ awareness about their metaphor use may promote more effective information exchange and decision-making.
Pathogen-specific host response in critically ill patients with blood stream infections: a nested case–control study
Background: Knowledge of the contribution of the pathogen to the heterogeneity of the host response to infection is limited. We aimed to compare the host response in critically ill patients with a bloodstream infection (BSI). Methods: RNA profiles were determined in blood obtained between one day before and after a positive blood culture. Differential expression and pathway analyses were performed on independent patients’ samples by RNA sequencing (discovery) or microarray (validation). Additional patients were included for the discovery and validation of transcriptome classifiers of pathogen-specific BSIs. Twenty biomarkers reflecting key host response pathways were measured in blood. Findings: We included 341 patients, among which 255 with BSI, 25 with viral infection and 61 non-infectious controls. The cultured pathogen explained 41·8% of the blood transcriptomic variance in patients with BSI. Gene set enrichment analysis showed a global resemblance between monomicrobial BSIs caused by Streptococcus, Staphylococcus aureus and Escherichia coli, which were clearly different from BSI caused by coagulase-negative staphylococci or Enterococcus. BSI by Streptococcus was associated with the highest number of differentially expressed genes, indicating strong innate and adaptive immune activation. An eight-gene streptococcal classifier performed well across different Streptococcus species, and was validated in external cohorts. Plasma biomarker profiling showed that E. coli BSI was associated with the strongest response in the cytokine and systemic inflammation domain, and S. aureus BSI with the strongest endothelial cell activation. Interpretation: The causative pathogen explains a substantial part of the heterogeneity of the host response in critically ill patients with BSI. Funding: Center for Translational Molecular Medicine and the European Commission.
Simplifying medicine dosing for children by harmonising weight bands across therapeutic areas.
Generally, dose recommendations for children are expressed as fixed dosing increments related to bodyweight, known as weight bands. The weight bands recommended in WHO treatment guidelines vary between diseases, leading to complexity and potential dosing errors when treating children for multiple diseases simultaneously. The introduction of a harmonised weight banding approach for orally administered drugs across disease areas could streamline dosing for young children, but implementing such an approach would require changes in current dosing recommendations. In this Health Policy, we describe the process we conducted to: identify therapeutic areas for harmonisation of weight bands; propose a harmonised weight-banding system to align with current use of weight bands in antibiotic guidance; and simulate the expected effect of dose adjustments due to weight-band harmonisation. Each step of this process, along with the effect and feasibility of weight-band harmonisation was discussed with clinical, policy, and pharmacology experts convened by WHO, representing four therapeutic areas: tuberculosis, HIV, malaria, and hepatitis C. Dosing according to harmonised weight bands across the targeted therapeutic areas was found to be feasible and should be considered for implementation by WHO disease programmes through their appropriate normative processes.
Handheld Spatially Offset Raman Spectroscopy for rapid non-invasive detection of ethylene glycol and diethylene glycol in medicinal syrups.
We investigate the potential of Spatially Offset Raman Spectroscopy (SORS) as a rapid, non-invasive screening tool deployable in the field to detect diethylene glycol (DEG) and ethylene glycol (EG) in medicinal syrups within closed containers. Measurements were performed on neat propylene glycol (PG) and glycerol, key components of many medicinal syrups, as well as marketed medicinal syrup formulations spiked with DEG and EG at various concentration levels to assess the technique's limit of detection in real-life samples. SORS was able to detect these down to ∼0.5 % concentration level in neat PG for both DEG and EG compounds and ∼1 % concentration level for DEG and EG in neat glycerol. The DEG and EG detection thresholds for the marketed formulations measured through original bottles was ∼1 %, for Benylin (active ingredient: Glycerol) and Piriteze (active ingredient: Cetirizine Hydrochloride). For Calpol (active ingredient: Paracetamol) the detection limit was higher, ∼2 % for EG and ∼5 % for DEG. Although not reaching the International Pharmacopeial 0.1 % detection threshold currently required for purity checks for human consumption, the method can still be used to detect products where DEG or EG has been wrongly used instead of PG or glycerol or if present in large quantities. The technique could also be used for raw material identification testing to ensure no mislabelling has occurred in pre-production stages and as a screening device in distribution chains to detect major deviations from permitted content in non-diffusely scattering, clear formulations, to help prevent serious adverse outcomes, such as acute renal failure and deaths.
Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19.
BackgroundDisease presentation and progression can vary greatly in heterogeneous diseases, such as COVID-19, with variability in patient outcomes, even within the hospital setting. This variability underscores the need for tailored treatment approaches based on distinct clinical subgroups.ObjectivesThis study aimed to identify COVID-19 patient subgroups with unique clinical characteristics using real-world data (RWD) from electronic health records (EHRs) to inform individualized treatment plans.Materials and methodsA Factor Analysis of Mixed Data (FAMD)-based agglomerative hierarchical clustering approach was employed to analyze the real-world data, enabling the identification of distinct patient subgroups. Statistical tests evaluated cluster differences, and machine learning models classified the identified subgroups.ResultsThree clusters of COVID-19 in patients with unique clinical characteristics were identified. The analysis revealed significant differences in hospital stay durations and survival rates among the clusters, with more severe clinical features correlating with worse prognoses and machine learning classifiers achieving high accuracy in subgroup identification.ConclusionBy leveraging RWD and advanced clustering techniques, the study provides insights into the heterogeneity of COVID-19 presentations. The findings support the development of classification models that can inform more individualized and effective treatment plans, improving patient outcomes in the future.