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Interventions to Support People With HIV Following Hospital Discharge: A Systematic Review.
Get PDFBACKGROUND: Individuals hospitalized with HIV-related complications face high post-discharge mortality and morbidity, particularly in resource-limited settings. This systematic review evaluated the impact of interventions to reduce post-hospital mortality, lower readmissions, and improve linkage to care. METHODS: We searched the PubMed, Embase, and Cochrane databases up to 1 October 2024 for studies reporting outcomes of post-discharge interventions. Two independent reviewers performed study selection, extracted data, and assessed risk of bias. We pooled data using random effects meta-analysis. RESULTS: We included 4 randomized controlled trials (conducted in Spain, South Africa, Tanzania, and the United States) and 6 observational studies (Canada, Thailand, Zambia, and the United States). Interventions included pre-discharge counseling, medication review, referral to care, and goal setting, as well as post-discharge follow-up via home visits, telephone calls, and support from social workers or community health workers. Pooled data from randomized controlled trials showed no difference between post-discharge interventions and usual care in mortality, but the estimate was imprecise (relative risk [RR], 0.98; 95% CI, .59-1.63). However, interventions may reduce readmissions (RR, 0.82; 95% CI, .52-1.30) and may slightly improve linkage/retention in care (RR, 1.10; 95% CI, .95-1.27). Observational studies reported similar results, with no mortality effect but potential reductions in readmissions (RR, 0.77; 95% CI, .48-1.25) and improved linkage/retention (RR, 1.42; 95% CI, 1.11-1.81). Interventions were largely feasible, acceptable, and low cost. CONCLUSIONS: Interventions that include pre-discharge care planning and post-discharge follow-up, such as telephone contact and home visits, may improve linkage to care and reduce readmissions. However, interventions were not associated with reduced post-discharge mortality
Developing a named entity framework for thyroid cancer staging and risk level classification using large language models.
Get PDFWe developed a named entity (NE) framework for information extraction from semi-structured clinical notes retrieved from The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) database and examined Large Language Models (LLMs) strategies to classify the 8th edition of American Joint Committee on Cancer (AJCC) staging and American Thyroid Association (ATA) risk category for patients with well-differentiated thyroid cancer. The NE framework consisted of annotation guidelines development, ground truth labelling, prompting approaches, and evaluation codes. Four LLMs (Mistral-7B-Instruct, Llama-3.1-8B-Instruct, Gemma-2-9B-Instruct, and Qwen2.5-7B-Instruct) were offline utilised for information extraction, comparing with expert-curated ground truth. Our framework was developed using 50 TCGA-THCA pathology notes. 289 TCGA-THCA notes and 35 pseudo-clinical cases were used for validation. Taking an ensemble-like majority-vote strategy achieved satisfactory performance for AJCC and ATA in both development and validation sets. Our framework and ensemble classifier optimised efficiency and accuracy of classifying stage and risk category in thyroid cancer patients
Trust, Information and Vaccine Aonfidence in Crisis Settings: A Scoping Review.
Get PDFBACKGROUND: In humanitarian crises, reliable and accurate information about health, security and humanitarian aid can be a tool for survival. At the same time, existing social structures and information systems are often disrupted, leading to uncertainty and challenges in interpreting information, including information that may guide individual public health decisions, particularly as part of vaccination programmes. This study aims to systematically explore the existing literature on these dynamics. METHODS: A scoping review was conducted using the key themes: misinformation, infodemic, vaccine confidence and trust with relevant synonyms and subheadings included to build the search strategy. Initial searching was conducted through MEDLINE (Ovid), Embase (Ovid), Global Health (Ovid), PsycINFO (Ovid), Web of Science and SCOPUS, and through hand searching reference lists. Articles were screened and data extracted using Covidence software. A content analysis was used to elucidate common and overlapping themes. FINDINGS: Forty-one studies from 14 country contexts as well as 4 from regional and global analyses met the inclusion criteria. The themes identified were (1) the drivers of mistrust, (2) the complexity of misinformation and vaccine confidence and (3) equity and programming with communities. CONCLUSION: The scoping review concluded that trust is essential for vaccine confidence in crisis contexts, and intentionally cultivating trust means engaging with historical injustices, politics, power dynamics and information. Vaccine equity, culturally sensitive communication strategies and ensuring interventions are community-driven should also be central to vaccine programming. Critical knowledge gaps remain about the interplay of trust, information and vaccine confidence in crisis settings and the best strategies that should be adopted to support humanitarian response
Addressing the emerging threat of Oropouche virus: implications and public health responses for healthcare systems.
Get PDFOropouche fever is an increasingly significant health concern in tropical and subtropical areas of South and Central America, and is primarily spread by midge vectors. The Oropouche virus (OROV) was first identified in 1955 and has been responsible for numerous outbreaks, particularly in urban environments. Despite its prevalence, the disease is often under-reported, making it difficult to fully understand its impact. OROV typically causes febrile illness characterized by symptoms such as headaches, muscle pain, and, occasionally, neurological issues such as meningitis. The ability of the virus to thrive in both forested and urban areas has raised concerns regarding its potential spread to new regions, particularly in the context of climate change. This paper delves into the epidemiology, clinical features, and transmission patterns of OROV, shedding light on the difficulties in diagnosing and managing the disease. The absence of specific treatments and vaccines highlights the urgent need for continued research and development of targeted public health strategies. Advancements in molecular diagnostics and vector control strategies can mitigate Oropouche fever's impact. However, a comprehensive public health approach involving increased surveillance, public education, and cross-border collaboration is needed, especially as the global climate crisis may expand vector habitats, posing risks to previously unaffected regions
Complete and draft genome sequences of clinical Mycobacterium tuberculosis isolates from the Philippines.
Get PDFThis study reports the complete and draft genomes of 71 Mycobacterium tuberculosis isolates from the Philippines. Hybrid assembly using Illumina and Nanopore sequencing produced six complete genomes, while others had 2-422 contigs. These data enhance understanding of M. tuberculosis diversity and drug resistance, supporting targeted treatment strategies
Rapid bacterial identification and resistance detection using a low complexity molecular diagnostic platform in Zimbabwe.
Get PDFBACKGROUND: Sepsis is a major cause of mortality in low-resource settings. Effective microbiological culture services are a bottleneck in diagnosis and surveillance. AIM: We aimed to evaluate the performance of the BIOFIRE FILMARRAY Blood Culture Identification 2 (BCID2, bioMérieux) assay in a low-resource setting laboratory in comparison to standard practice. METHODS: This five month prospective validation study included all positive blood cultures collected at Sally Mugabe Central Hospital, Harare, Zimbabwe. BCID2 testing was done in parallel to standard phenotypic procedures and resistance testing. Reference identification was performed using mass spectrometry or whole genome sequencing. Only samples with available reference standard results were included in the analysis. Data captured on paper-based forms was entered into electronic case report forms (ODK Collect). Specificity and sensitivity for BCID2 were calculated in comparison to the reference standards, with performance measures calculated using the Wilson score. Biomedical scientists using BCID2 completed a system usability survey (SUS). RESULTS: Positive results were recorded in 780/2,023 (38.5%) blood cultures, within which 377 (48.3%) had reference results and so were included in analysis. Neonatal samples were most frequent (182, 48.3%), then paediatric (150, 39.8%), then adults (18, 4.8%) and unknown (27, 7.2%). Specificity exceeded 95% throughout. Sensitivity ranged from 50% (A. calcoaceticus-baumanii complex, Proteus spp.) to 100% (S. pneumoniae, Salmonella spp). Using BCID2, CTX-M was detected in 111/175 (74.5%) Enterobacterales, from which 5/111 also had NDM and VIM detected. NDM-5 was detected in 2/5 NDM samples using sequencing. In total 3/23 S. aureus isolates were methicillin resistant, from which one was confirmed using phenotypic antimicrobial susceptibility testing. Usability was good (SUS score = 79.5). CONCLUSION: Rapid molecular tests have potential to improve turn-around time and quality of sepsis diagnostics. However, specific work-flows are critical to supplement molecular tests with minimal phenotypic tests for optimal clinical decision-making
Yellow fever in South America - A plea for action and call for prevention also in travelers from SLAMVI, ESGITM, EVASG, ALEIMC, GEPI-SEIMC, SEMEVI, and CMTZMV-ACIN.
Get PDFThe origin of yellow fever (YF) is believed to be in Africa, with the disease arriving in the Caribbean and Brazil on slave ships during the 1500s. Then, it spread from the Caribbean to the United States of America (USA), reaching the cities of New Orleans and Philadelphia. It was identified on European soil, arriving via conquistador ships and causing major outbreaks in the French port city of Marseille. Since then, the YF virus has easily adapted to naïve vectors and reservoirs in the tropical Americas, where it is endemic [[1], [2], [3], [4]], and intermittently epidemic (https://www.cdc.gov/yellow-book/hcp/travel-associated-infections-diseases/yellow-fever.html). YF, caused by the YF virus (YFV) (Flaviviridae family) (Orthoflavivirus flavi) (ICTV 2022/2024) (http://bit.ly/4kTkS9z) [5], a mosquito-borne viral disease and one of the most critical hemorrhagic fevers endemic to tropical and subtropical regions of Africa and South America, continues to pose significant challenges to public health, particularly in low and middle-income countries of the latter [1,6]. Globally, about 1.54 billion individuals live in regions conducive to YF transmission [7]. In recent years, South America has experienced a resurgence in YFV and geographical expansion of transmission in some countries, affecting both human and non-human primate (NHP) populations [8,9]. More than 300 cases of YF have been reported in six South American countries during the outbreaks initiated in 2024 and ongoing in 2025, representing up to July 6 2025 a fourfold increase compared to the cases reported in 2024 (61 in 2024 and 255 in half of 2025) (https://www.who.int/emergencies/disease-outbreak-news/item/2025-DON570), with more than 40% resulting in a fatal outcome (Table 1). Such a staggering case fatality rate, in a vaccine-preventable disease, not only highlights the urgency to improve coverage rates and traveler awareness but also underscores YF's standing as one of the deadliest vaccine-preventable viral infections
Opportunities to Optimize Outcomes of Diagnosis and Treatment of HIV and Syphilis in Pregnancy: the Quest to Eliminate Maternal and Vertical Transmission.
Get PDFBACKGROUND: There is an urgent need to improve interventions for HIV and syphilis in pregnancy to achieve elimination. RESULTS: The tenets of vertical transmission strategies for HIV and syphilis overlap but have varying success due to differences in their transmission dynamics, diagnoses, and treatment. Key principles include prevention of maternal infection, screening and diagnosis early and throughout antenatal care, curative treatment (syphilis), viral load suppression (HIV), early infant diagnosis and treatment (HIV and congenital syphilis). We recommend improved guidelines, provider training and focused research and surveillance, including implementation studies to align HIV and syphilis screening and treatment during pregnancy. Opportunities to integrate syphilis screening and treatment into antenatal and HIV care enable providers to offer comprehensive maternal care. CONCLUSION: Integrated HIV/syphilis services ensure a cohesive and person-centered approach, improving health outcomes through streamlined, efficient, and family-centered care pathways. We recommend key interventions to reduce HIV and syphilis in pregnancy and prevent vertical transmission
The potential impact of reductions in international donor funding on tuberculosis in low-income and middle-income countries: a modelling study.
Get PDFBACKGROUND: Tuberculosis programmes in many settings rely heavily on international donor funding. In 2025, the United States Agency for International Development (USAID) was dismantled, and other countries announced cuts to overseas development assistance. We quantified the potential epidemiological impacts on the tuberculosis burden attributable to these reductions in funding. METHODS: We calibrated a deterministic tuberculosis model of Mycobacterium tuberculosis transmission, progression, and care to epidemiological indicators in selected low-income and middle-income countries. Calibration was done with the history matching with emulation method, implemented with the hmer package in R and the Approximate Bayesian computation Markov Chain Monte Carlo method. We projected three future scenarios with the following assumptions: that levels of funding in 2024 would continue, that USAID funding would be terminated from 2025, and that additional reductions in funding through The Global Fund to Fight AIDS, Tuberculosis and Malaria would occur (alongside termination of funding from USAID) in line with current donor announcements from 2025. We assumed a reduction in tuberculosis treatment initiation rates proportional to budget reductions for each scenario, estimating cumulative excess episodes of symptomatic tuberculosis and tuberculosis deaths for each scenario. FINDINGS: We modelled 79 countries, representing 91% of global tuberculosis incidence and 90% of global tuberculosis mortality in 2023. Our modelling suggested that termination of USAID funding might lead to 1·4 million (95% uncertainty interval 1·1-1·7) excess tuberculosis episodes and 537 700 (451 900-662 300) excess deaths by 2035. Further reductions in funding in line with current announcements by the USA, France, the UK, and Germany could lead to 2·8 million (2·1-3·7), 257 600 (192 500-332 900), 206 000 (153 900-266 100), and 124 700 (93 200-161 000), additional episodes, respectively, of symptomatic tuberculosis and 1·0 million (0·8-1·3), 90 500 (72 400-112 800), 72 400 (57 900-90 100), and 43 800 (35 000-54 500) additional tuberculosis deaths, respectively, in the same period, relative to the scenario of termination of USAID funding. INTERPRETATION: We estimate substantial potential impacts on tuberculosis morbidity and mortality due to reductions in international donor funding. Expanded support from domestic and international donors is essential to address immediate gaps in services for prevention, diagnosis, and treatment. FUNDING: None
Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data.
Get PDFWhen estimating heterogeneous treatment effects, missing outcome data can complicate treatment effect estimation, causing certain subgroups of the population to be poorly represented. In this work, we discuss this commonly overlooked problem and consider the impact that missing at random outcome data has on causal machine learning estimators for the conditional average treatment effect (CATE). We propose 2 de-biased machine learning estimators for the CATE, the mDR-learner, and mEP-learner, which address the issue of under-representation by integrating inverse probability of censoring weights into the DR-learner and EP-learner, respectively. We show that under reasonable conditions, these estimators are oracle efficient and illustrate their favorable performance through simulated data settings, comparing them to existing CATE estimators, including comparison to estimators that use common missing data techniques. We present an example of their application using the GBSG2 trial, exploring treatment effect heterogeneity when comparing hormonal therapies to non-hormonal therapies among breast cancer patients post surgery, and offer guidance on the decisions a practitioner must make when implementing these estimators