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Journal articleThapa S, Shrestha B, Joshi DR, et al., 2025,
Draft genome sequence of carbapenem-resistant Klebsiella pneumoniae ST6260 isolated from the catheter tip of a female patient in Nepal
, Microbiology Resource Announcements, Vol: 14Klebsiella pneumoniae is an opportunistic human pathogen, particularly associated with nosocomial infections and multidrug resistance. Here, we present a draft genome sequence of a carbapenem-resistant K. pneumoniae ST6260 isolated from the catheter tip of a female patient in a referral case received at Kathmandu Model Hospital, Kathmandu, Nepal.
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Journal articleMellor J, Tang ML, Jones O, et al., 2025,
Forecasting COVID-19, influenza, and RSV hospitalizations over winter 2023-4 in England
, International Journal of Epidemiology, Vol: 54, ISSN: 0300-5771Background Seasonal respiratory viruses cause substantial pressure on healthcare systems, particularly over winter. System managers can mitigate the impact on patient care when they anticipate hospital admissions due to these viruses. Hospitalization forecasts were used widely during the SARS-CoV-2 pandemic. Now, resurgent seasonal respiratory pathogens add complexity to system planning. We describe how a suite of forecasts for respiratory pathogens, embedded in national and regional decision-making structures, were used to mitigate the impact on hospital systems and patient care. Methods We developed forecasting models to predict hospital admissions and bed occupancy 2 weeks ahead for COVID-19, influenza, and respiratory syncytial virus (RSV) in England over winter 2023-4. Bed occupancy forecasts were informed by the ensemble admissions models. Forecasts were delivered in real time at multiple scales. The use of sample-based forecasting allowed effective reconciliation and trend interpretation. Results Admission forecasts, particularly RSV and influenza, showed high efficacy at regional levels. Bed occupancy forecasts had well-calibrated coverage owing to informative admissions forecasts and slower moving trends. National admissions forecasts had mean absolute percentage errors of 27.3%, 30.9%, and 15.7% for COVID-19, influenza, and RSV, respectively, with corresponding 90% coverages of 0.439, 0.807, and 0.779. Conclusion These real-time winter infectious disease forecasts produced by the UK Health Security Agency for healthcare system managers played an informative role in mitigating seasonal pressures. The models were delivered regularly and shared widely across the system to key users. This was achieved by producing reliable, fast, and epidemiologically informed ensembles of models, though a higher diversity of model approaches could have improved forecast accuracy.
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OtherBates KA, Rosa GM, Garner TWJ, 2025,
Ranavirus
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Journal articleBroshkevitch CJ, Zhou S, Greifinger A, et al., 2025,
Sequencing HIV Diagnostic Samples to Detect Genetic Clusters and Assess Sequence Coverage Gaps
, Open Forum Infectious Diseases, Vol: 12Background HIV molecular cluster detection in the United States relies on HIV sequences obtained from drug resistance testing during clinical care ("routine care sequences"). This approach misses people who are not linked to care or who receive care but have uncollected or unreported sequences. Methods We collected "HIV test sequences"from remnant serum samples of people testing newly positive from 2018 through 2021 by a large public health laboratory in North Carolina. We incorporated the HIV test sequences into a statewide molecular cluster analysis and assessed impact on "active cluster"detection (≥5 members newly diagnosed). We described data gaps filled by HIV test sequences, comparing (1) the extent of care sequence missingness due to gaps in care linkage vs sequence collection or reporting and (2) the characteristics of people with an HIV test sequence who had a care sequence, care but no care sequence, or no evidence of care. Results Of 19 770 people included in the cluster analysis, 847 had an HIV test sequence, one-third of whom had no routine care sequence. We identified 13 additional active clusters (a 33% relative increase) and 40 larger active clusters after incorporating HIV test sequences. Most people with an HIV test sequence but no care sequence (78%) had another care indicator, suggesting sequence undercollection or underreporting, but a fifth (22%) had no evidence of care. Conclusions Higher sequence coverage can improve cluster detection. While increased routine care sequence collection and reporting could fill many data gaps, sequencing remnant HIV test samples could include people without care linkage.
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Journal articleJahn S, Gaythorpe KAM, Wainwright CM, et al., 2025,
Evaluation of the Performance and Utility of Global Gridded Precipitation Products for Health Applications and Impact Assessments in South America
, Geohealth, Vol: 9Globally gridded precipitation products (GGPPs) are commonly used in impact assessments as substitutes for weather station data, each with unique strengths and limitations. Reanalysis products are among the most widely used for driving impact models, evaluating climate models, or bias-correcting and downscaling model outputs to generate climate change projections. However, they are often outperformed in accuracy by other GGPPs, particularly in tropical regions, including areas of the Global South. Therefore, we assessed the utility and suitability of GGPPs for climate and health research by examining how differences and uncertainties in these products affect area-level precipitation estimates, often used in health studies when epidemiological data are linked to administrative units. We compared reanalysis (ERA5/-Land) with satellite-based (CHIRPS, PERSIANN-CDR) and interpolated gauge-based products (CRUTS, GPCC), each a viable candidate to serve as reference climatology in climate change impact assessments. We focused on seasonal patterns, disease-related bioclimatic variables, and climate change-relevant indices, such as the number of wet or dry periods. Our findings revealed substantial variation in the accuracy of local precipitation estimates across GGPPs, with differences in maximum pixel precipitation values exceeding 75% between ERA5-Land and CHIRPS. These differences in GGPPs translated into area-level precipitation and, consequently, in vector carrying capacity estimates, demonstrating their impact on health assessments. Our analysis focused on Brazil and Colombia, two diverse countries differing for example, in orography, climate, and size. Each product was evaluated against national station data. Our results indicate that estimating tropical precipitation is particularly challenging for reanalysis, while CHIRPS demonstrated the best overall performance.
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Journal articleJahn S, Fraser K, Gaythorpe KAM, et al., 2025,
Evaluating the role of observational uncertainty in climate impact assessments: Temperature-driven yellow fever risk in South America
, Plos Climate, Vol: 4Global gridded temperature data sets (GGTDs) differ in data sources, quality control, generation methods, and spatial-temporal resolution, introducing observational uncertainty. This uncertainty is critical not only for studies on current climate conditions but also for future climate change projections, where observational data sets are used for bias correction and downscaling of global climate model (GCM) outputs. It is hence essential to ensure that reference data sets accurately represent the true climate state and span a sufficiently long period to filter out internal variability. The selection of appropriate GGTDs is hence a crucial yet often overlooked factor in research that examines the impact of climate variability and change on vector-borne diseases such as yellow fever (YF), a climate-sensitive arboviral disease endemic to tropical regions of Africa and South America. In this study, we evaluated four GGTDs, namely the Berkeley Earth Surface Temperatures (BEST), the Climatic Research Unit Time-Series (CRUTS), the fifth-generation atmospheric reanalysis of the global climate from the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA5, and its land-focused derivative, ERA5Land, for health-related impact research, specifically examining YF transmission in South America. Each data set was evaluated via grid-based analysis and validated against national weather station data, focusing on Brazil and Colombia, where YF outbreak risk remains. While reanalysis generally outperformed lower-resolution products, ERA5 demonstrated a slight advantage over ERA5Land despite the latter’s higher spatial resolution. Most importantly, our findings show that substantial differences among GGTDs affected the spatial representation of climate change indices, bioclimatic variables, and spatially aggregated temperature estimates at the administrative (AD) unit level, with substantial variations in the latter translating into markedly different estimates of key d
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Journal articleDelight EA, Brunn AA, Ruiz F, et al., 2025,
Gaps and opportunities for data systems and economics to support priority setting for climate-sensitive infectious diseases in sub-Saharan Africa: A rapid scoping review
, Plos Global Public Health, Vol: 5Climate change alters risks associated with climate-sensitive infectious diseases (CSIDs) with pandemic potential. This poses additional threats to already vulnerable populations, further amplified by social factors such as gender inequalities. Currently, critical evidence gaps, along with inadequate institutional and governance mechanisms, hinder African states’ ability to prevent, detect and respond to CSIDs. Effective responses require transparent and evidence-based decision-making processes, supported by fit-for-purpose data systems and robust economic analyses. The aim of this study was to explore the role of data systems and economics in priority setting for CSID pandemic preparedness in sub-Saharan Africa. We conducted a rapid scoping review following PRISMA-ScR guidelines. A literature search was performed across six bibliographic databases in November 2023. A list of 14 target CSIDs was produced, informed by the World Health Organization’s Public Health Emergencies of International Concern and R&D Blueprint Pathogen lists, and a database of CSIDs. Studies were included if published between 2010 and 2023, were relevant to sub-Saharan Africa, pandemic preparedness, and a target CSID, and applied or assessed economic evaluations or data systems. Extracted data were synthesised using bibliometric analysis, topic categorisation, and a narrative synthesis including the application of a gender lens. We identified 68 relevant studies. Data system studies (n = 50) showed broad coverage across target CSIDs and the WHO AFRO region but also a high degree of heterogeneity, which may indicate a lack of clearly defined standards or research priorities. Economic studies (n = 18) primarily focused on COVID-19 or Ebola and mostly originated from South Africa. Both data system and economic studies identified limited interoperability across sectors and showed a notable absence of gendered considerations. These gaps present important opportunities to strengthen
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Journal articleMohan V, Strepis N, Mitsakakis K, et al., 2025,
Antimicrobial resistance in Campylobacter spp. focussing on C. jejuni and C. coli – A narrative review
, Journal of Global Antimicrobial Resistance, Vol: 43, Pages: 372-389, ISSN: 2213-7165Objectives: Campylobacter species represent one of the leading causes of human foodborne infections, including gastroenteritis and bloody diarrhoea. Overuse of antibiotics in veterinary, agriculture, and humans has led to an increase in multidrug antimicrobial resistance (AMR). Fluoroquinolones and macrolides resistant Campylobacters are WHO and CDC priority pathogens, with fluoroquinolone resistance doubling in the past 20 years, complicating treatment. Methods: Published studies relating to AMR and associated molecular mechanisms in both Campylobacter jejuni (C. jejuni) and C. coli from animals, humans and environment (1981–2024), were retrieved from PubMed and Google Scholar using relevant keywords. In addition, genomic analyses of publicly available C. jejuni and C. coli genomes along with multilocus sequence typing results from the PubMLST database were used to analyse these AMR determinants and their phylogenomic relationships. Review articles were excluded from the analyses. Results: A total of 429 research papers were reviewed to get insights into multidrug resistance in C. jejuni and C. coli. Fluroquinolone resistance has been predominantly associated with international travel. The gyrA subunits were associated with ecological niches and overall, it is suggestive that C. coli might be the donor. A positive synergism was observed between cmeA gene expression and quinolone resistance. Additionally, the results speculated the possibility of horizontal gene transfers in chromosomal resistance clusters between C. coli and C. jejuni. Conclusions: This review indicated significant concern of multidrug resistance in C. jejuni and C. coli. This requires continent-wide surveillance and research for standard practices to achieve effective antimicrobial stewardship.
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Journal articleDay KP, Tan MH, He Q, et al., 2025,
Var genes, strain hyperdiversity, and malaria transmission dynamics
, Trends in Parasitology, Vol: 41, Pages: 471-485, ISSN: 0169-4758The microbiological paradigm for surveillance of diverse pathogens requires knowledge of the variation of the major surface antigen under the most intense immune selection as immune responses to these antigens drive transmission dynamics. This creates a pathway for population genetics/genomics to be combined with mathematical modelling to describe transmission dynamics to inform public health policy. Here we consider how we can bring population genetics and population dynamics together for a highly recombining pathogen like Plasmodium falciparum. We do this through the lens of what has been recently learnt about the population genetics of the var multigene family encoding the major surface antigen of the blood stages of Plasmodium falciparum, known as PfEMP1.
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Journal articleFairbairn TA, Mullen L, Nicol E, et al., 2025,
Implementation of a national AI technology program on cardiovascular outcomes and the health system
, Nature Medicine, Vol: 31, Pages: 1903-1910, ISSN: 1078-8956Coronary artery disease (CAD) is a major cause of ill health and death worldwide. Coronary computed tomographic angiography (CCTA) is the first-line investigation to detect CAD in symptomatic patients. This diagnostic approach risks greater second-line heart tests and treatments at a cost to the patient and health system. The National Health Service funded use of an artificial intelligence (AI) diagnostic tool, computed tomography (CT)-derived fractional flow reserve (FFR-CT), in patients with chest pain to improve physician decision-making and reduce downstream tests. This observational cohort study assessed the impact of FFR-CT on cardiovascular outcomes by including all patients investigated with CCTA during the national AI implementation program at 27 hospitals (CCTA n = 90,553 and FFR-CT n = 7,863). FFR-CT was safe, with no difference in all-cause (n = 1,134 (3.2%) versus 1,612 (2.9%), adjusted-hazard ratio (aHR) 1.00 (0.93–1.08), P = 0.97) or cardiovascular mortality (n = 465 (1.3%) versus 617 (1.1%), aHR 0.96 (0.85–1.08), P = 0.48), while reducing invasive coronary angiograms (n = 5,720 (16%) versus 8,183 (14.9%), aHR 0.93 (0.90–0.97), P < 0.001) and noninvasive cardiac tests (189/1,000 patients versus 167/1,000), P < 0.001). Implementation of an AI-diagnostic tool as part of a health intervention program was safe and beneficial to the patient pathway and health system with fewer cardiac tests at 2 years.
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