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Oxford University has been ranked as the world's best institution for medical and health teaching and research in the Times Higher Education World University Rankings for the eighth consecutive year. This ranking is based on criteria measuring teaching, research, industry income, international outlook and citations. It was noted that both research and clinical trials are supported by our network of international research units in Africa and Asia.
Global spatiotemporal analysis of suicide epidemiology and risk factor associations from 2000 to 2019 using Bayesian space time hierarchical modeling.
Suicide is a significant global public health issue, with marked disparities in rates between countries. Much of the existing research has concentrated on high-income nations, creating a gap in the understanding of global suicide epidemiology. This study aims to address this gap through a comprehensive spatiotemporal analysis of global suicide trends from 2000 to 2019. Data were collected from the Global Health Observatory, encompassing 183 countries across five regions. Bayesian spatiotemporal modeling and cluster detection techniques were employed to assess variations in suicide rates and identify high-risk clusters, alongside examining associations with various risk factors. The findings indicate diverse global and regional age-standardized suicide trends, with overall rates decreasing from an average of 12.97 deaths per 100,000 population in 2000 to 9.93 deaths per 100,000 in 2019. Significant regional variations were noted, particularly in Europe, Asia, and Africa, where high-risk clusters were identified. Additionally, age and sex-specific trends revealed consistently higher rates among males, although these rates have been declining over time. Spatial maps illustrated hotspots of elevated suicide rates, which can inform targeted intervention strategies. Risk factor analysis further revealed associations with socioeconomic and health indicators. The results underscore the necessity for tailored prevention strategies and highlight the importance of international collaboration and surveillance systems in addressing the complexities of global suicide epidemiology. This study contributes valuable insights into suicide patterns and offers implications for mental health policies worldwide.
A comparison of national seasonal influenza treatment guidelines across the Asia Pacific region.
Seasonal influenza leads to 2-3 million infections and up to 650,000 global deaths annually, with particularly high mortality in Asia and relatively low annual vaccination rates for prevention. Relatively lower attention is paid to antiviral treatment as a facet of influenza response strategy both in research and national policy. This study compares national influenza treatment guidelines across countries in the Asia Pacific region, and assesses the antiviral recommendations, comprehensiveness, availability, and quality, compared with World Health Organisation (WHO) guidelines. Ministry of Health websites were searched, and key stakeholders were contacted to obtain national influenza treatment guidelines. Official guidelines detailing pharmacologic treatment for seasonal influenza were included. Key data for comparison were extracted and quality appraisal was conducted using the AGREE II instrument. Out of 49 countries and areas in the World Health Organisation Western Pacific and South-East Asia regions, under half (14/49; 28.6%) had established national influenza treatment guidelines. Nine (9/49; 18.4%) reported no seasonal flu guidelines at all, and information could not be obtained for 25 (51.0%). All guidelines recommend oseltamivir in line with WHO recommendations, although rationale and evidence reviews were often missing. There was variation in recommendations for other antivirals, indications for treatment, definitions of severity and recency of publication. The AGREE II tool quality assessments revealed the highest average scores were observed in the 'presentation' domain and lowest scores in 'editorial independence' and 'rigour of development' domains, demonstrating limited evidence-based guideline development. The variability in recommendations and definitions highlight the need for a stronger evidence base with direct comparisons of antiviral treatment for hard and soft endpoints, and improvements in systematic guideline development. Established treatment guidelines are a key component of national influenza response strategy and in the post-covid pandemic era, renewed attention to seasonal influenza management is surely warranted.
Hide and seek with falsified medicines: Current challenges and physico-chemical and biological approaches for tracing the origin of trafficked products.
The criminal trafficking of falsified medical products is a worldwide, yet still largely overlooked, public health problem. A falsified medicine fraudulently misrepresents its identity, composition and/or source, often being ineffective or toxic for patients. Although techniques have been developed to detect falsified medicines, it remains a challenge to trace where- and by whom- the products are manufactured. We aim to discuss plausible biological and physico-chemical analytical techniques that could reveal information about the origin of medical falsifications. We first provide a brief overview on the prevalence, criminal activities, health impacts and (bio)chemical features of falsified medical products. We then explore diverse laboratory approaches, that are used in food fraud, illicit drug and wildlife trafficking investigations, and discuss how they could be combined and redirected towards tracing falsified medicine origin and hence empowering enforcement to counter this pernicious but neglected global health problem.
Understanding the primary healthcare context in rural South and Southeast Asia: a village profiling study
Abstract Background Understanding contextual factors is critical to the success of health service planning and implementation. However, few contextual data are available at the village level in rural South and Southeast Asia. This study addressed the gap by profiling representative villages across seven sites in Thailand (n=3), Cambodia, Laos, Myanmar and Bangladesh. Methods Key informant surveys supplemented by other information sources were used to collect data from 687 villages on four key indicators (literacy rate, and percentages of attended deliveries, fully immunised children and latrine coverage), as well as access to various services. Data were analysed descriptively. Results Sites varied considerably. Five were highly diverse ethno-culturally and linguistically, and all relied on primary health centres and village health/malaria workers as the main providers of primary healthcare. These were generally bypassed by severely ill patients for urban first-level referral hospitals and private sector facilities. While >75% of villages were near primary schools, educational attainment was generally low. Over 70% of villages at each site had mobile phone coverage and availability of electricity was high (≥65% at all sites bar Myanmar). Conclusion These results illustrate the similarities and differences of villages in this region that must be considered in public health research and policymaking.
Lung ultrasound for the diagnosis and monitoring of pneumonia in a tuberculosis-endemic setting: a prospective study.
Lung ultrasound (LUS) has proven high diagnostic accuracy for community-acquired pneumonia (CAP) in developed countries. However, its diagnostic performance in resource-limited settings with high pulmonary tuberculosis (TB) incidence is less established. Additionally, the role of LUS in monitoring CAP progression remains underexplored.ObjectivesTo validate the diagnostic performance, monitoring and prognostic utility of LUS for CAP in a high pulmonary TB incidence setting.DesignProspective single-centre cohort study.SettingPulmonary department of a tertiary hospital in Vietnam.ParticipantsA total of 158 patients suspected of having CAP were enrolled, with 136 (mean age 62 years, 72.8% male) included in the final analysis.InterventionsPatients underwent LUS and chest X-ray (CXR) within 24 hours of admission, with a follow-up LUS on days 5-8.Primary and secondary outcome measuresThe primary outcome was the diagnostic accuracy of LUS and CXR compared with discharge diagnosis. Secondary outcomes included the accuracy compared with CT scan results, changes in LUS parameters-consolidation size, number and Lung Ultrasound Score (LUSS)-and their association with in-hospital mortality.ResultsLUS demonstrated higher sensitivity than CXR (96.0% (95% CI 90.0% to 99.0%) vs 82.8% (95% CI 73.9% to 89.7%)). LUS specificity was 64.9% (95% CI 47.5% to 80.0%), compared with 54.1% (95% CI 36.9% to 70.5%) for CXR. The moderate specificity for LUS was due to sonographic-similar conditions, notably TB in 5.1% of patients. Consolidation size and numbers showed marginal resolution, while LUSS showed more pronounced decreases over time. The baseline LUSS showed limited discriminative ability for predicting mortality (area under the curve, AUC 0.65, 95% CI 0.55 to 0.75), while follow-up LUSS and changes in LUSS (ΔLUSS) demonstrated higher levels of discrimination (AUC 0.81 (95% CI 0.71 to 0.89) and 0.89 (95% CI 0.80 to 0.95), respectively). For each one-point increase in ΔLUSS, the odds of in-hospital mortality went up by 70% (p=0.002). An improved LUSS effectively ruled out mortality (negative predictive value 97.4%).ConclusionAlthough LUS is highly sensitive for diagnosing CAP, its specificity in TB-endemic regions warrants further caution. Serial LUS assessments, particularly monitoring LUSS changes, are valuable for tracking disease progression and prognostication, with increasing LUSS indicating potential clinical deterioration.
Suitability of low and middle-income country data-derived prognostics models for benchmarking mortality in a multinational Asia critical care registry network: a multicentre study
Background: This study evaluates the predictive performance of prognostic models derived from low- and middle-income country (LMIC) data using a multinational Asian critical care dataset. The research also seeks to identify opportunities for improving these models' accuracy and utility in clinical research and for international benchmarking of critical care outcomes Methods This retrospective multicenter study evaluated the performance of four prognostic models: e-Tropical Intensive Care Score (e-TropICS), Tropical Intensive Care Score (TropICS), Simplified Mortality Score for the Intensive Care Unit (SMS-ICU), and Rwanda Mortality Probability Model (R-MPM) using a dataset of 64,327 ICU admissions from 109 ICUs across six Asian countries. The models' discriminative abilities were assessed using ROC curves, and calibration was evaluated with Hosmer-Lemeshow C-statistics and calibration curves. Recalibration was performed to improve model accuracy, and the impact of the COVID-19 pandemic on model performance was also analysed. Results The e-TropICS and R-MPM models showed relatively good discriminative power, with AUCs of 0.71 and 0.69, respectively. However, all models exhibited significant calibration issues, particularly at higher predicted probabilities, even after recalibration. The study also revealed variability in model performance across different countries, with India's data demonstrating the highest discriminative power. Conclusions The study highlights the challenges of applying existing prognostic models in diverse ICU settings, particularly in LMICs. While the e-TropICS and R-MPM models performed relatively well, significant calibration issues indicate a need for further refinement. Future efforts should focus on developing adaptable models that can effectively accommodate the diverse and dynamic nature of ICU populations worldwide, ensuring their utility in global healthcare benchmarking and decision-making.
An All-in-One Nanoheater and Optical Thermometer Fabricated from Fractal Nanoparticle Assemblies.
We designed and optimized a dual-functional photothermal agent that performs as a nanoheater and real-time optical thermometer by leveraging gold nanoparticle (AuNP) self-assembly and anti-Stokes thermometry. We engineered colloidally stable fractal AuNP clusters with well-defined nanogaps to absorb strongly in the near-infrared and enhance anti-Stokes vibrational modes via surface-enhanced Raman scattering (SERS) for electromagnetic (EM) hotspot-localized thermometry during plasmonic heating. Photothermal characterization and simulations of a range of AuNP building block sizes demonstrated that 40 nm AuNPs are optimum for combined plasmonic heating and SERS due to the high probability of in resonance chains within assemblies. We explored the relationship between the far-field of our AuNP clusters and the near-field enhancement of anti-Stokes modes in the context of SERS thermometry, setting out design considerations for applying SERS thermometry. Finally, using a single near-infrared (NIR) laser source, we demonstrated plasmonic heating of a colloidal system with simultaneous accurate temperature measurement from EM hotspots via the thermal information encoded in the anti-Stokes mode of surface-bound Raman reporter molecules. Ultimately, our approach could enable real-time noninvasive temperature feedback from plasmonic nanoparticles within tumor tissue environments to guide safe and effective temperature increases during cancer photothermal therapy.
Epidemiology of Burkholderia pseudomallei, Streptococcus suis, Salmonella spp., Shigella spp. and Vibrio spp. infections in 111 hospitals in Thailand, 2022
The information on notifiable diseases in low- and middle-income countries is often incomplete, limiting our understanding of their epidemiology. Our study addresses this knowledge gap by analyzing microbiology laboratory and hospital admission data from 111 of 127 public referral hospitals in Thailand, excluding Bangkok, from January to December 2022. We evaluated factors associated with the incidence of notifiable bacterial diseases (NBDs) caused by 11 pathogens; including Brucella spp., Burkholderia pseudomallei, Corynebacterium diphtheriae, Neisseria gonorrhoeae, Neisseria meningitidis, non-typhoidal Salmonella spp. (NTS), Salmonella enterica serovar Paratyphi, Salmonella enterica serovar Typhi, Shigella spp., Streptococcus suis, and Vibrio spp.. We used multivariable Poisson random-effects regression models. Additionally, we compared their yearly incidence rates in 2022 with those from 2012-2015 in hospitals where paired data were available. In 2022, the NBD associated with the highest total number of deaths was B. pseudomallei (4,407 patients; 1,219 deaths) infection, followed by NTS (4,501 patients; 461 deaths), S. suis (867 patients, 134 deaths) and Vibrio spp. (809 patients, 122 deaths) infection. The incidence rates of B. pseudomallei, S. suis and Vibrio spp. infections were highest in the northeast, upper central and west, respectively. The incidence rate of NTS infection was generally high across all geographical regions. The yearly incidence rates of B. pseudomallei and S. suis infections in 2022 were higher than those between 2012-2015, while those of fecal-oral transmitted NBDs including NTS infection, typhoid, shigellosis and vibriosis were lower. Overall, B. pseudomallei and S. suis infections are emerging and associated with a very high number of deaths in Thailand. Although the incidence of NTS infection and vibriosis are decreasing, they are still associated with a high number of cases and deaths. Specific public health interventions are warranted.
Why the growth of arboviral diseases necessitates a new generation of global risk maps and future projections.
Global risk maps are an important tool for assessing the global threat of mosquito and tick-transmitted arboviral diseases. Public health officials increasingly rely on risk maps to understand the drivers of transmission, forecast spread, identify gaps in surveillance, estimate disease burden, and target and evaluate the impact of interventions. Here, we describe how current approaches to mapping arboviral diseases have become unnecessarily siloed, ignoring the strengths and weaknesses of different data types and methods. This places limits on data and model output comparability, uncertainty estimation and generalisation that limit the answers they can provide to some of the most pressing questions in arbovirus control. We argue for a new generation of risk mapping models that jointly infer risk from multiple data types. We outline how this can be achieved conceptually and show how this new framework creates opportunities to better integrate epidemiological understanding and uncertainty quantification. We advocate for more co-development of risk maps among modellers and end-users to better enable risk maps to inform public health decisions. Prospective validation of risk maps for specific applications can inform further targeted data collection and subsequent model refinement in an iterative manner. If the expanding use of arbovirus risk maps for control is to continue, methods must develop and adapt to changing questions, interventions and data availability.