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Journal articleEdiriweera DS, Kasturiratne A, Pathmeswaran A, et al., 2026,
Estimates of global burden of snakebite: A literature review and geostatistical modelling study.
, PLoS Med, Vol: 23BACKGROUND: Snake envenoming (SE) remains an important public health problem, disproportionately affecting impoverished rural communities in tropical and subtropical regions. Although previous attempts have been made to quantify the global burden of SE, accurate, up-to-date data remain scarce. Here we present a comprehensive re-evaluation of the global burden of snakebite, 17 years after our initial estimate. METHODS AND FINDINGS: A new literature review was conducted on snakebites, SE and mortality published in any language, up to March 31, 2025, to update the knowledge accumulated since our first global burden estimate. Based on country- and region-level aggregated data, and hospital and community-based survey data, we modelled SE and mortality burden in relation to geographic location. Explanatory variables were selected to reflect the underlying social and natural environmental conditions. Low and high estimates of the global snakebite burden were calculated using geostatistical models that produced individual-country estimates, accounting for possible underreporting of data when appropriate. We estimate that at least 2.1 million envenomings and 274,000 deaths occur globally each year due to snakebites, and our high estimates suggest up to 7 million envenomings and 513,000 deaths annually. Low-income countries exhibit the highest incidence and mortality rates, with sub-Saharan Africa accounting for 45% of global envenomings and deaths, nearly three times the incidence observed in South Asia. These estimates suggest that previous burden estimates could substantially underestimate the scale of the problem. The main limitations of this study are the scarcity and heterogeneity of empirical data in many countries and the reliance on modelling assumptions to estimate burden in settings with limited or no direct observations. CONCLUSIONS: Snake envenoming is a significant cause of morbidity and mortality globally, with sub-Saharan Africa, South Asia, and Southeast Asia
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Journal articleKennedy J, Ferguson W, Jones O, et al., 2026,
Evaluation of short-term multi-target respiratory forecasts over winter 2024-25 in England using sub-ensemble contribution analyses.
, PLoS Comput Biol, Vol: 22BACKGROUND: Epidemic forecasting research often assesses ensembles and their component models using probabilistic scoring rules. Quantifying how individual models affect ensemble performance is challenging, particularly across multiple targets and spatial scales. METHODS: We present Winter 2024-25 forecasts of Influenza and COVID-19 hospital admissions in England and conduct a retrospective simulation using the operational component models. Forecasts were scored using the per capita weighted interval score (pcWIS) for counts and the ranked probability score (RPS) for ordinal trend direction. We compared retrospective forecasts, used generalised additive models (GAMs) to estimate the expected change in score from the inclusion of a model in a sub-ensemble (an ensemble formed from a subset of available models), and used Pareto analysis to understand which sub-ensembles were Pareto-optimal across scoring rules. RESULTS: Nationally, there was a 47% improvement in Influenza pcWIS versus sub-ensembles. However, Influenza operational ensembles were on average 22% worse than sub-ensembles, when measured by RPS. For COVID-19, operational ensembles were 43% and 280% worse on average, than retrospective sub-ensembles by pcWIS and RPS, respectively. However, COVID-19 operational ensembles were on average 2% (pcWIS) and 13% (RPS) better than individual operational models. For influenza, operational ensembles were, on average, 58% (pcWIS) and 41% (RPS) better than individual models. The sub-ensemble simulation showed how individual models influenced the ensemble scores during different epidemic phases. The Pareto analysis demonstrated that there can be a trade-off between relative direction and absolute count score optimisation.
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Journal articlePrice JR, Otter JA, Snell LB, et al., 2026,
From potential to practice: a UK national roadmap to implement pathogen whole-genome sequencing in infection prevention and control.
, Lancet MicrobeWhole-genome sequencing has substantially advanced the understanding of infection transmission but remains underused in everyday infection prevention and control. The UK pioneered genomic medicine through the 100 000 Genomes Project, tuberculosis surveillance, and foodborne disease programmes; yet, a sustainable framework for routine use of genomic medicine in infection prevention and control has not been realised. In June, 2025, the Genomics to Optimise Infection Prevention (GENOTIPE) Network convened clinicians, academics, public health leaders, and the industry to address this implementation gap. A central challenge is not sequencing capacity alone, but ascertaining when and where genomic information is actionable, and how this information can be delivered in a clinically useful and cost-effective way within operational timeframes. In this Personal View, we outline a national implementation roadmap that emphasises prioritised use-cases, coordinated delivery models, and embedded evaluation of clinical, economic, and system-wide impact. Progress will depend on linking targeted implementation with real-world evidence generation to support sustainable adoption across health-care systems.
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Journal articleRamani A, Dixon-Zegeye M, Walker M, et al., 2026,
Identifying implementation units that would benefit from alternative treatment strategies to accelerate the elimination of onchocerciasis transmission in Africa
, Frontiers in Tropical Diseases, ISSN: 2673-7515Background: The World Health Organization proposes that elimination of onchocerciasis transmission (EOT) be verified in 12 endemic countries by 2030. In sub-Saharan Africa (SSA), where most cases occur, Niger is the only country that has been verified to date. Despite decades of ivermectin mass drug administration (MDA), infection persists in West and Central Africa. Alternative treatment strategies (ATS) are necessary to accelerate progress towards EOT by 2030 and beyond. Methods: We used the EPIONCHO-IBM transmission model to project the number of years, from 2026, to reduce microfilarial (mf) prevalence below 1% across 1,634 implementation units (IUs) in 19 SSA countries. We fitted the model to geostatistically-derived mf prevalence in 1975, 2000 and 2018, and projected mf prevalence through to 2025. We classified IUs according to their baseline endemicity, intervention history programmatic performance, and current (2025) MDA frequency (annual or biannual). For those IUs that would not reach < 1% mf prevalence by 2030 if current strategies were continued, we simulated ATS (increasing treatment frequency, improving coverage, and adopting moxidectin MDA) from 2026 to 2040. Results: Of the 1,486 IUs currently under annual ivermectin MDA, 45% would require ATS. In those low-moderate endemicity IUs, biannual ivermectin would have a comparable impact to that of switching to annual moxidectin; in those with high endemicity, adopting biannual moxidectin would be more impactful. Of the 148 IUs currently receiving biannual ivermectin, 24% would benefit from ATS, switching to biannual moxidectin being the best option. Conclusion: This work brings into sharper focus which IU profiles are most likely to require ATS across SSA. In highly-endemic IUs with long intervention histories, biannual moxidectin MDA may be required under our modelling assumptions, with substantial uncertainty surrounding the permanent sterilising effect, of the two drugs under comparison, upon adult
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Journal articleBotwright S, Munira SL, Megiddo I, et al., 2026,
Uncertainty in economic evaluation: a pragmatic guide for health technology assessment (HTA) agencies in resource-constrained settings
, PharmacoEconomics, ISSN: 1170-7690Understanding the financial and health consequences if economic evaluation assumptions prove incorrect is essential for managing the risk associated with benefit package decisions, particularly in resource-constrained and overburdened healthcare systems. Yet these are also the settings that face the greatest challenges in conducting comprehensive uncertainty analysis, owing to a range of factors including limited skilled staff, data constraints, and short timelines to generate evidence in time to influence policy. This paper takes a pragmatic approach to support health technology assessment agencies in these settings to generate policy-relevant uncertainty analysis, drawing on good practice literature and the authors’ collective experience conducting economic evaluation for policy across resource-constrained settings. For each step of the economic evaluation process, we outline the main sources of uncertainty, principles for deciding which uncertainty analysis to prioritise, and approaches to overcome some of the common challenges faced when dealing with constrained timelines, data, and skilled staff. The overarching goal is to support better-informed decisions, by targeting uncertainty analysis to factors that actually affect decisions and by effectively communicating this decision-relevant uncertainty to policymakers.
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Journal articleOdufuwa OG, Sheppard RJ, Ngonyani S, et al., 2026,
House modifications using insecticide-treated screening of eave and window as a vector control tool: evidence from a semi-field system in Tanzania and simulated epidemiological impact.
, BMC Public HealthBACKGROUND: Gaps in unimproved house structures, especially in eaves and windows, allow mosquito entry, increasing indoor vector-borne disease transmission. Simple modifications to such houses may reduce human exposure, and insecticide treatment may kill mosquitoes, benefiting all community members. This study evaluated insecticide-treated screening (ITS) for eaves and windows, incorporated with deltamethrin and piperonyl butoxide (PBO), compared to a permethrin and PBO-treated bednet in Tanzania. METHOD: A randomised Latin-square design (4 × 4) was used in four experimental huts within a large netting cage to allow mosquito recapture inside and outside of huts. Four treatments were evaluated: (1) new (12-month stored) ITS; (2) 12-month naturally-aged ITS; (3) 12-month field-used pyrethroid-PBO bednet (standard of care in Tanzania), and (4) no treatment. The study was performed for 32 nights using 30 mosquitoes per strain, per hut per night. Four laboratory-reared strains were used: malaria vectors (Anopheles arabiensis and An. funestus), dengue vector (Aedes aegypti), and nuisance biting (Culex quinquefasciatus). Recaptured mosquitoes were assessed for mortality at 72 h, blood-feeding, and hut entry. A simulation with a modified mechanistic model tracking Plasmodium falciparum malaria was used to illustrate potential epidemiological impact from these products. RESULTS: Against all mosquito species compared to 12-month aged pyrethroid-PBO-treated bednet, new ITS induced higher mortality [Odds Ratio:2.25(95%Confidence Interval:1.65-3.06),p < 0.0001], and aged-ITS was similar [OR:0.80(95%CI:0.59-1.08),p = 0.141]. Both new and aged ITS significantly (p < 0.0001) reduced mosquito blood-feeding [new OR:0.02(95% CI:0.01-0.03); aged OR:0.09(95%CI:0.05-0.14)] and hut entry [new IRR:0.10(95%CI:0.08-0.13); aged IRR:0.25(95%CI:0.21-0.31)]. Transmission model estimates indicate epidemiological impacts of I
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Journal articleKim Y, Mills C, Donnelly CA, 2026,
Cross-border travel patterns affect magnitude estimates for the Ebola Bundibugyo epidemic
, Nature Health<jats:title>Abstract</jats:title> <jats:p>A geographic spread approach is often used to estimate the true burden of infectious disease cases in a source population by leveraging statistical signals generated by cases exported and reported elsewhere. Here we estimated an upper bound on the likely burden of Bundibugyo virus disease cases in the Democratic Republic of Congo early in the unfolding 2026 epidemic based on the number of cases imported and confirmed in Uganda. We expanded a geographic spread approach to account for its specific epidemiological contexts: most cross-border movements between the Democratic Republic of Congo and Uganda are short-duration trips, and, at the time of this analysis, all cases imported and confirmed in Uganda were individuals who travelled specifically to seek healthcare. Incorporating these factors substantially affected burden estimates, highlighting both the potential severity of the epidemic in its early phase and the critical need to consider local epidemiological contexts when applying geographic spread approaches to reduce and be aware of potential biases in estimates for early epidemic responses.</jats:p>
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Journal articleHicks J, Munsey A, Mousa A, et al., 2026,
Disentangling patterns of community malaria transmission and burden using malaria prevalence among pregnant women attending antenatal care: a modelling study
, The Lancet Microbe, ISSN: 2666-5247BackgroundMalaria prevalence measured among pregnant women at the first antenatal care (ANC1) visit provides longitudinal estimates of malaria burden in pregnancy and correlates well with cross-sectional community prevalence, but additional analysis is required to estimate community incidence. We aimed to test whether ANC1-based malaria prevalence can, via an open-source, mechanistic, model-based framework, recover seasonal patterns of clinical incidence suitable for subnational programmatic decision making.MethodsWe conducted a modelling study using monthly ANC1 malaria prevalence data from six previously published studies of malaria in pregnancy in six sub-Saharan African countries between May, 2010, and August, 2014. An extended, validated, age-structured malaria transmission model was fitted to monthly ANC1 malaria prevalence using particle Markov chain Monte Carlo (pMCMC) to infer monthly clinical incidence and seasonality metrics. Agreement between model-derived incidence and independently observed time series was assessed using the Markham Seasonality Index (MSI) and peak timing with concordance correlation coefficients (CCCs) and 95% CIs.FindingsAcross the six intermittent screening and treatment in pregnancy (ISTp) datasets, total ANC1 sample sizes and positivity were Ghana, 622 (47·9%) of 1298; Burkina Faso, 592 (41·9%) of 1413; Mali, 284 (21·7%) of 1308; The Gambia, 105 (8·8%) of 1194; Kenya, 323 (21·1%) of 1528; and Malawi, 291 (15·9%) of 1825. Strong agreement was observed between model-derived incidence and independent cohort data for MSI (CCC 0·82 [95% CI 0·31–0·97]) and for peak timing (CCC 0·98 [95% CI 0·87–1·00]).InterpretationA mechanistic pMCMC framework applied to routine ANC1 data can recover clinically relevant seasonality in incidence for the broader community, enabling subnational timing of seasonal interventions (such as seasonal malaria chemopre
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Journal articleNaidoo T, Morgenstern C, Doohan P, et al., 2026,
A systematic review of Nipah virus disease epidemiological parameters, outbreaks and mathematical models
, The Lancet Infectious Diseases, ISSN: 1473-3099We conducted a systematic review, following PRISMA guidelines (PROSPERO CRD42023393345), characterising the epidemiology, outbreaks and mathematical models of Nipah virus (NiV), an important public health threat in South and Southeast Asia. We searched PubMed and Web of Science from database inception through to 14 March 2025, and extracted 243 parameters, 89 risk factors, 39 models and 23 distinct outbreaks from 119 papers. IgG seroprevalence estimates in the general population ranged from 0% to 12.5%. NiV causes severe disease, with pooled case-fatality ratio estimates ranging widely from 9.1% (95%CI: 0.2%-41.3%) in Singapore to 81.9% (95%CI: 71.9%-88.9%) in Bangladesh. NiV's infection timeline and clinical course remain poorly characterised; we estimated a median incubation period of 8.77 days (n=165, 95%CI: 7.53-10.02) from 8 estimates in 7 articles with sufficient information. Transmission parameter estimates were scarce, and all but one of five central estimates of the basic reproduction number were below 1. NiV mathematical models (n=39) were rarely fitted to data (n=8). All extracted information is accessible via our R package, epireview.
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Journal articleDennis TPW, Sulieman JE, Nouredayem M, et al., 2026,
The origin, history, and resistance architecture of an invasive urban malaria mosquito in Africa.
, Science, Vol: 393The invasive urban malaria vector Anopheles stephensi threatens 126 million city dwellers in Africa. Controlling An. stephensi requires greater understanding of its origin, invasion dynamics, and insecticide resistance mechanisms. Analysis of 645 whole genomes sampled across Africa, the Middle East, and Asia supports an invasion scenario in which an initial South Asian introduction established a bridgehead population in Djibouti, which seeded distinct invasion fronts in Sudan, Ethiopia/Kenya, and Yemen. These incursions show contrasting rates and routes of spread shaped by landscape topology. Insecticide resistance is predominantly mediated by metabolic detoxification genes, with resistance haplotypes and copy-number amplifications introduced from South Asia. These findings, alongside a companion genomic resource, enable genomic surveillance of An. stephensi spread and resistance to aid control strategies.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.
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