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Journal articleHowes A, Stringer A, Flaxman SR, et al., 2026,
Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature
, Journal of Theoretical Biology, Vol: 618, ISSN: 0022-5193Naomi is a spatial evidence synthesis model used to produce district-level HIV epidemic indicators in sub-Saharan Africa. Multiple outcomes of policy interest, including HIV prevalence, HIV incidence, and antiretroviral therapy treatment coverage are jointly modelled using both household survey data and routinely reported health system data. The model is provided as a tool for countries to input their data to and generate estimates with during a yearly process supported by UNAIDS. Previously, inference has been conducted using empirical Bayes and a Gaussian approximation, implemented via the TMB R package. We propose a new inference method based on an extension of adaptive Gauss-Hermite quadrature to deal with more than 20 hyperparameters. Using data from Malawi, our method improves the accuracy of inferences for model parameters, while being substantially faster to run than Hamiltonian Monte Carlo with the No-U-Turn sampler. Our implementation leverages the existing TMB C++ template for the model’s log-posterior, and is compatible with any model with such a template.
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Journal articleLamberte LE, Darby EM, Kiu R, et al., 2025,
<i>Staphylococcus haemolyticus</i> is a reservoir of antibiotic resistance genes in the preterm infant gut
, GUT MICROBES, Vol: 17, ISSN: 1949-0976 -
Journal articleTapsoba M, Guelbeogo WM, Sanou A, et al., 2025,
Three-year trends in malaria transmission parameters under deployment of Interceptor®G1, Interceptor®G2 and PermaNet®3.0 insecticide-treated bed nets in South-Western Burkina Faso
, Malaria Journal -
Journal articleBouchali R, Sentenac H, Bates KA, et al., 2025,
Unraveling the disease pyramid: the role of environmental micro-eukaryotes in amphibian resistance to the deadly fungal pathogen <i>Batrachochytrium dendrobatidis</i>
, mSystems<jats:title>ABSTRACT</jats:title> <jats:sec> <jats:title/> <jats:p> The disease pyramid conceptualizes the predictors of host infection risk, linking the host, the pathogen, environmental conditions, and both host and environmental microbiomes. However, the importance of the interaction between environmental and host-associated microbiomes in shaping infectious disease dynamics remains poorly understood. While the majority of studies have focused on bacteria, the role of micro-eukaryotes has been seldom investigated. Here, we explore three axes of the disease pyramid using an 18S rRNA gene metabarcoding approach to analyze the micro-eukaryotic assemblages of biofilm, water, and skin samples from three European amphibian species. Skin bacterial communities of the investigated amphibian populations have already been shown to be impacted by the presence of the lethal fungal pathogen <jats:italic toggle="yes">Batrachochytrium dendrobatidis</jats:italic> ( <jats:italic toggle="yes">Bd</jats:italic> ), with a higher abundance of protective bacteria in infected populations and a greater environmental microbial contribution to the skin microbiota in <jats:italic toggle="yes">Bd</jats:italic> -positive lakes. Here, we explored the relationships between the micro-eukaryotic skin communities of these tadpole populations with their surrounding environment. Tadpoles were sampled at 22 mountain lakes located in the Pyrenees (France), 8 of which harbored amphibian populations infected by <jats:italic toggle="yes">Bd</jats:italic> . We found that biofilms from <jats:italic toggle="yes">Bd&l
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Journal articleStapley JN, Basanez M-G, Ramani A, et al., 2025,
Modelling the effects of immigration on the re-introduction of onchocerciasis
, Parasites and Vectors, ISSN: 1756-3305Background Onchocerciasis is a filarial neglected tropical disease targeted by the World Health Organization for elimination (interruption) of transmission (EOT), principally by mass drug administration (MDA) with ivermectin. Variable effectiveness and success of MDA, among other factors, has led to a markedly heterogeneous contemporary spatial landscape of endemicity and transmission, with some foci having achieved or nearing EOT, while in others, transmission persists despite decades of MDA or has only recently been identified. Communities reaching EOT or free from infection are thus vulnerable to re-introduction of infection imported by immigrants from areas with ongoing transmission.Methods We use the stochastic, individual-based EPIONCHO-IBM transmission model to quantify the risk of transmission persistence resulting from importation events and characterise the dynamics of ensuing onchocerciasis outbreaks in terms of microfilarial prevalence (in all ages) and anti-Ov16 seroprevalence (in children aged 5-9 years) in infection-free communities with local populations of blackfly vectors.Results We show how the vulnerability of infection-free communities depends on their population size, the local annual biting rate (ABR, number bites/person/year) and on the magnitude of importation events, defined by the number of immigrants arriving in the community and their worm burdens. We show that small communities with modest ABRs are particularly vulnerable to transmission persistence following importation, with risk exacerbated by the magnitude of infection importation. We illustrate that onchocerciasis outbreak dynamics can be protracted, with seroprevalence in children often taking substantially longer than the currently recommended 3-5 years of post-treatment surveillance(PTS) to exceed 5%. Conclusions Our findings highlight the vulnerability of infection-free communities to introduction/re-introduction of infection and suggest that proposed PTS durations may need to
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Journal articleBooth G, Hadjichrysanthou C, Rice KL, et al., 2025,
Preventing SARS-CoV-2 superspreading events with antiviral intranasal sprays
, JOURNAL OF THEORETICAL BIOLOGY, Vol: 615, ISSN: 0022-5193 -
Journal articleCalvo-Urbano B, Kaushik M, Cheng A-C, et al., 2025,
The role of parasite-produced dopamine in Toxoplasma gondii-altered host behaviour.
, Nat Commun, Vol: 16Certain parasites can manipulate host behaviour for their own benefit, but the mechanisms remain largely unknown. Toxoplasma gondii, the agent of the toxoplasmosis, is a canonical example, altering behaviour in rodents and other hosts, including humans. Dopamine dysregulation has been suggested as a mechanism, with parasite-encoded tyrosine hydroxylases (TgTH) proposed as a direct source of dopamine, though their role is debated. Here, using Rattus norvegicus as a model, with subtle and specific behavioural and biostatistical assays and analyses, we examine the contribution of TgTH to behavioural change. Two engineered T. gondii Prugniaud lines with moderate and high TgTH overexpression (OE) are compared to wild-type and recombinant wild-type parasites, alongside uninfected controls. All genetically modified lines induce weaker behavioural changes than true wild-type, but changes correlate with TgTH expression levels. Our findings provide empirical support that TgTH contributes to T. gondii-associated behavioural alterations, highlighting both theoretical significance and applied implications.
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Journal articleBasanez M-G, Amaral LJTDMD, Walker M, et al., 2025,
Reaching elimination of onchocerciasis transmission with long-term vector control and ivermectin treatment in togo
, Nature Communications, ISSN: 2041-1723The Onchocerciasis Control Programme in West Africa implemented vector control (VC) and ivermectin mass drug administration (MDA) to eliminate blindness, intensifying efforts in Special Intervention Zones (SIZ). Togo aims to eliminate onchocerciasis transmission (EOT) by 2030. We use the EPIONCHO-IBM model to project microfilarial prevalence trends across Togo’s five regions by SIZ status, MDA coverage (65%-80%) and VC efficacy (60%-100%). We compare projections with prevalence surveys (400 villages, 1970-2017) stratified by hypoendemic, mesoendemic, hyperendemic, and holoendemic baseline endemicity, and calculate EOT probabilities for 2024, 2027, and 2030. Combined VC and MDA reduced prevalence nationwide. After cessation of VC, prevalence continued to decline in hypo-to mesoendemic areas under annual MDA, while hyperendemic areas required biannual MDA. In holoendemic areas, prevalence rebounded even with biannual MDA, indicating that alternative strategies are needed. EPIONCHO-IBM reproduces Togo’s onchocerciasis trends throughout five decades of intervention and provides a transferable framework to guide policy towards 2030 goals.
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Journal articleRiley S, Wang H, Wang H, 2025,
Forecasting regional COVID‐19 regional COVID-19 hospitalisation in England using ordinal machine learning method
, Epidemics, Vol: 53, ISSN: 1755-4365BackgroundThe COVID-19 pandemic caused substantial pressure on healthcare, with many systems needing to prepare for and mitigate the consequences of surges in demand caused by multiple overlapping waves of infections. Therefore, public health agencies and health system managers also benefitted from short-term forecasts for respiratory infections that allowed them to manage services. While quantitative forecasts treating hospital admissions as continuous variables existed, many health managers prefer discrete levels of demand, similar to approaches used in weather and flooding. However, effective tools for generating precise sub-national forecasts remained limited.MethodsWe forecast regional COVID-19 hospitalisations in England, using the period from March 2020 to December 2021 for training and evaluating predictions using data from January to December 2022. We transform regional admission counts into an ordinal variable using n-tile and n-uniform methods. We further developed a method based on XGBoost, and used previously for influenza, to enable it to exploit the ordering information in ordinal hospital admission levels. We incorporated different types of data as predictors: epidemiological data including weekly region COVID-19 cases and hospital admissions, weather conditions and mobility data for multiple categories of locations. The impact of different discretisation methods and the number of ordinal levels was also considered.ResultsWe found that mobility data brings about a more substantial improvement in predictive performance than relying only on epidemiological data and the inclusion of weather data. When both weather and mobility data are used in addition to epidemiological data, the results are very similar to models with only epidemiological data and mobility data. These results are robust in terms of the number of levels chosen for the forecast target.ConclusionAccurate ordinal forecasts of COVID-19 hospitalisations were obtained using XGBoost and mobil
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Journal articleAgostinho A, Chalot E, Teixeira D, et al., 2025,
Author Correction: Semi-automated surveillance of surgical site infections using machine learning and rule-based classification models(npj Digital Medicine, 10.1038/s41746-025-01989-1)
, Npj Digital Medicine, Vol: 8Correction to: npj Digital Medicinehttps://doi.org/10.1038/s41746-025-01989-1, published online 17 October 2025 In the original version of this Article, several numerical values were incorrectly reported: In the Results section, the proportion of male patients was stated as 52%. The correct value is 59%, consistent with Table 1. In Table 1, two patients were inadvertently omitted from the ASA score category rows. The corrected counts and percentages are:ASA 1-2: 737 (55.9%), 48 (5.7%), 1,360 (77.0%), 2,145 (54.6%)ASA ≥3: 581 (44.1%), 799 (94.3%), 406 (23.0%), 1,786 (45.4%) For the rule-based model in the validation set, performance metrics were inconsistent across sections. The correct values are: Sensitivity: 1.000 (95% CI 0.954–1.000) False Negative Rate (FNR): 0.00% (95% CI 0.00–4.60) Negative Predictive Value (NPV): 1.000 (95% CI 0.998–1.000) In the Results section, the proportion of male patients was stated as 52%. The correct value is 59%, consistent with Table 1. In Table 1, two patients were inadvertently omitted from the ASA score category rows. The corrected counts and percentages are: ASA 1-2: 737 (55.9%), 48 (5.7%), 1,360 (77.0%), 2,145 (54.6%) ASA ≥3: 581 (44.1%), 799 (94.3%), 406 (23.0%), 1,786 (45.4%) ASA 1-2: 737 (55.9%), 48 (5.7%), 1,360 (77.0%), 2,145 (54.6%) ASA ≥3: 581 (44.1%), 799 (94.3%), 406 (23.0%), 1,786 (45.4%) For the rule-based model in the validation set, performance metrics were inconsistent across sections. The correct values are: Sensitivity: 1.000 (95% CI 0.954–1.000) False Negative Rate (FNR): 0.00% (95% CI 0.00–4.60) Negative Predictive Value (NPV): 1.000 (95% CI 0.998–1.000) These corrections apply to the Abstract, Results, and Table 3, where the originally reported values were: Sensitivity in Abstract: 0.954 (corrected to 1.000) FNR in main text: 4.6% (95% CI 0.00–12.3) (corrected to 0.00% [95% CI 0.00–4.60]) Sensitivity in Table 3: 0.977 (95% CI 0.954–1.00) (correcte
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