Transboundary and Emerging Diseases

Background Nipah virus (NiV) is a priority zoonotic pathogen causing high-fatality outbreaks. Early NiV outbreaks in Malaysia and Singapore had limited transmission beyond spillover events. However, since 2001, NiV outbreaks with person-to-person transmission have occurred in Bangladesh and India, driven by the NiV-Bangladesh genotype and NiV-India genotype. Our study aims to estimate the reproduction number, offspring dispersion, and serial interval governing NiV transmission in Bangladesh and India during 2001-2026. Methods We conducted a systematic review of NiV outbreak investigations in Bangladesh and India, searching PubMed, Embase, Web of Science, and grey literature through 28 February 2026. Case-level offspring counts from 27 eligible sources (323 cases across 67 outbreaks) were used as input to a hierarchical Bayesian negative binomial offspring distribution model. The serial interval was estimated by parametric distribution fitting to 137 transmission pairs. Country-stratified and sensitivity analyses were performed to evaluate the robustness of estimates. Results Pooling across 67 outbreaks, we estimated a median reproduction number of 0.46 (95% CrI: 0.28-0.73), an offspring dispersion parameter of 0.07 (0.05-0.10), and a serial interval of 13.3 days (95% CI: 12.8-13.8). Country-stratified median reproduction numbers were 0.48 (0.23-0.97) for India and 0.35 (0.19-0.59) for Bangladesh, and dispersion parameters were 0.04 (0.02-0.07) and 0.11 (0.06-0.18), respectively, indicating marked overdispersion in both settings. Conclusion NiV transmission is self-limiting on average and highly overdispersed, suggesting that a disproportionate share of onward transmission arises from a small number of cases. This epidemiological profile supports targeted containment measures, including contact tracing and quarantine, for effective NiV outbreak control.

Background: Leptospirosis causes around 1 million cases and 60,000 deaths globally annually, predominantly affecting flood-prone tropical regions. Transmitted through contact with water or soil contaminated by animal urine infected with Leptospira spp., this bacterial zoonosis is classified as a high-risk Group B infectious disease in Vietnam. However, epidemiological and clinical data are scarce, particularly in pediatric populations. This study evaluated clinical and laboratory characteristics of leptospirosis cases at the National Children's Hospital, Hanoi, from January 2023 to August 2025. Methodology : All children admitted with probable or confirmed leptospirosis were enrolled. Clinical and laboratory data were analyzed to characterize disease manifestations and identify risk factors for severe leptospirosis. This was defined by the presence of organ dysfunction, including liver or renal failure, hemorrhage (particularly pulmonary), aseptic meningitis, cardiac arrhythmias, pulmonary insufficiency, or hemodynamic collapse. Principal Findings : Of 84 patients (37 confirmed, 47 probable), the mean age was 9.4 years, with 52.4% male and over half aged [≥] 10 years. Fever was the most common presenting symptom (85.7%); gastrointestinal and renal manifestations were frequent, including oliguria in 26.2% of cases. Key laboratory abnormalities included elevated D-dimer (81.8%), elevated C-reactive protein (75.6%), hypoalbuminemia (74.3%), increased liver enzymes (AST 63.3%, ALT 53.2%), and renal impairment ({approx} 46%). Severe disease developed in 48.8% of patients, most frequently as acute kidney injury. Hematuria was independently associated with increased severity (OR = 4.89). Conversely, fever, higher baseline albumin, and longer symptom duration prior to hospitalization were associated with a significantly reduced risk of severe disease. Conclusions : Pediatric leptospirosis in this cohort frequently presented with systemic inflammation and multi-organ involvement, particularly renal impairment. Nearly half the patients developed severe disease. Early recognition of renal signs, especially hematuria, and careful monitoring of albumin levels are critical to identifying children at risk for severe progression and optimizing clinical management.

Objectives: In some resource-limited settings the case-fatality rate of severe leptospirosis can exceed 50%. Early recognition of severe disease can expedite transfer to referral centres for advanced supportive care. The entirely clinical, 3-point SPiRO score can be calculated rapidly at presentation to predict a patients subsequent clinical course. In its derivation study, a SPiRO score of 0 had a negative predictive value (NPV) for intensive care unit (ICU) admission of 98% (95% confidence interval (CI): 96-99). In this validation cohort we sought to confirm the clinical utility of the SPiRO score and to compare its prognostic utility with other leptospirosis-specific and general disease severity scores. Methods: We examined consecutive adults presenting to high-caseload hospitals in tropical Australia with laboratory-confirmed leptospirosis between June 2016 and April 2026. The ability of the SPiRO score to predict requirement for ICU admission before hospital discharge was compared with that of the leptospirosis-specific QuickLepto score and commonly used disease severity scores, namely the SOFA, qSOFA, qSOFA-lactate, NEWS-2, qNEWS, UVA and the SIRS scores. Results: ICU admission was required in 62/309 (20%) episodes of leptospirosis. The SPiRO score performed as well as - or better than - all the other scores in predicting ICU admission. The Area Under the Receiver Operating Characteristic curve for the SPiRO score was 0.83 (95% CI: 0.77-0.89); only the SOFA score had a higher value: 0.84 (0.79-0.90), although the difference was not statistically significant (p=0.08). The SPiRO score had the highest NPV for ICU admission of any of the scores: 95 (95% CI: 91-97)%. Conclusions: The SPiRO score can be calculated easily at the bedside at presentation to expedite the recognition of patients with leptospirosis who are most likely to deteriorate. In resource-limited settings this entirely clinical score can also help reduce unnecessary escalation of care, optimising the use of finite health resources.

Background. In 2026, the Democratic Republic of the Congo (DRC) experienced the largest recorded outbreak of Ebola disease caused by Bundibugyo virus, with epidemiologically linked importations and secondary transmission in Uganda. This study analysed the publicly reported trajectory and assessed the risk of introduction and onward transmission in North Africa and Europe. Methods. Public surveillance reports from the World Health Organization (WHO), European Centre for Disease Prevention and Control (ECDC), Africa CDC, national ministries of health, and peer-reviewed sources were synthesised through 15-17 July 2026. Headline counts and crude case-fatality ratios were restricted to laboratory-confirmed cases. Average notification rates were calculated from cumulative DRC counts. Exact Poisson intervals used the Garwood method, and the June-July rate ratio was estimated on the log scale. Risk was assessed across introduction likelihood, conditional onward-transmission likelihood, impact, and confidence. Results. By 15 July, the DRC had reported 2,124 confirmed cases and 828 deaths (crude confirmed-case fatality ratio, 39.0%) across 46 health zones in five provinces. Uganda had reported 20 confirmed cases and two confirmed deaths: 15 imported infections and five secondary cases, with no documented community transmission. DRC notifications averaged 47.4 per day during 1-15 July versus 35.9 per day during 2-29 June (rate ratio 1.32; counting-model 95% interval 1.20-1.46). WHO reported that more than 80% of new cases were detected outside known contact lists, while 119 confirmed healthcare-worker infections and 36 deaths had occurred. Introduction likelihood was assessed as very low to low for North Africa and very low for the general European population; delayed recognition in routine healthcare was the principal scenario for limited secondary transmission. Interpretation. Available indicators were inconsistent with effective control in eastern DRC at the data cut-off. Public reporting-date series cannot separate transmission from changing ascertainment, but they showed no sustained decline. Preparedness in North Africa and Europe should prioritise complete exposure histories, rapid isolation, validated diagnostics, protected clinical care, and contact management rather than reliance on border screening. Keywords: Bundibugyo virus; Ebola disease; outbreak surveillance; rapid risk assessment; importation; North Africa; Europe; Algeria; International Health Regulations.

Dengue is a mosquito-borne, viral disease of increasing public health significance. Currently, most public health interventions target the vector, with efficacy dependent on timing within the season. Whilst seasonal profiles have been characterised in some endemic settings a global assessment is lacking. Here, we develop and apply a proportion-based measure of dengue seasonality to reported case time series from 1990 to 2024 across 106 countries and territories, the largest assessment of this phenomenon to date. We identify regional differences in seasonality such that every month of the year saw cases peak in at least one country or territory. Latitude was identified as influencing seasonality, with cases peaking between March and April in the southern hemisphere and July and October in the northern hemisphere. Equatorial locations displayed flat seasonality, and amplitude increased with distance from the equator. K-means clustering identified three seasonal profile types: two with pronounced seasonal outbreaks (with distinct peak timing and shape) and one with flatter, more endemic transmission. Peak month timing covaried among locations within the same seasonality cluster, with phase differences meaning that information on shifts in peak timing may be available several months in advance in some settings, of potential significance for prediction and intervention planning. Beyond aiding public health planning, identification of seasonal clusters suggests that information on dynamics in one location could be leveraged to improve forecasting power in others with similar seasonal dynamics.

The World Health Organization (WHO) validated Sri Lanka had eliminated lymphatic filariasis as a public health problem in 2016, the second country in Southeast Asia to attain this status. However, post-validation surveillance has identified sporadic cases of brugian filariasis. The reemergence of Brugia malayi infections in Sri Lanka warrants urgent investigations. Recent studies have shown that the parasite responsible for the reemergence is a novel zoonotic Brugia sp. maintained among dogs that is closely related but distinct to the human-infecting B. malayi species. The current study employed morphological and morphometric assessments, revealing that this novel zoonotic Brugia sp. is within the B. malayi morphological range. Molecular characterization of three genomic regions, the nuclear genomic region SLXI, the non-coding region HhaI, and the mitochondrial genomic region COXI confirmed it as a genetic variant more closely related to B. malayi than to B. pahangi. Phylogenetic analysis further indicated it as a distinct genomic variant, closely related to a B. malayi-like parasite reported from India. Notably, that same parasite was identified in infected humans, animals, and potential vector mosquitoes. This, together with the detection of both human and animal blood within the same brugian infective mosquitoes, and delineating the canine origin of the parasites in human infections, provides compelling evidence supporting zoonotic transmission of this parasite. To our knowledge, this is the first report demonstrating the presence of the same brugian parasite in humans, domestic animals, and potentially infective mosquitoes in Sri Lanka, supported by multi-genomic evidence. The recent identification of multiple potential mosquito vector species suggests that this parasite may have undergone adaptive changes, facilitating its ability to overcome the species barrier. These findings substantiate the long-held hypothesis of zoonotic transmission of the reemerged brugian parasite, highlighting significant implications for ongoing surveillance and control strategies.

In this paper, we propose a new model to estimate the impact of an intervention on human hosts of a vector-borne infection, such as dengue, which occurs in yearly outbreaks of different magnitudes. The model applies to these outbreaks and, in fact, is independent of their intensity, that is, it does not require the steady-state assumption. The model takes as input the officially reported age-dependent number of cases of a vector-borne infection. It is deterministic and does not account for stochasticity. Our objective is to estimate the impact of the intervention (the efficacy), and we rely on the observed fact that the age distribution of the proportion of cases of the infections transmitted by the same vector is independent of both the intensity of transmission and the geographic area studied, at least for Brazilian regions. This finding is highlighted in the main text and forms the basis of our calculations. A hypothetical intervention is simulated using a dengue vaccine, which allows the determination of the optimal strategy for a vaccination campaign.

Background: Travellers visiting friends and relatives (VFRs) experience a disproportionate burden of travel-associated infectious diseases, yet little is known about the complexity of pre-travel consultations required to support their care. We compared enquiries relating to VFR travellers and tourists received by the UK National Travel Health Network and Centre (NaTHNaC) specialist Advice Line to identify differences in traveller characteristics, destinations and clinical complexity. Methods: We conducted a retrospective observational study of enquiries to the NaTHNaC Advice Line between 1 January 2019 and 31 December 2025. Enquiries relating to VFR travellers and tourists were compared using descriptive statistics and appropriate statistical tests. Traveller demographics, travel characteristics, destinations and enquiry management were analysed. Results: Of 16,367 enquiries relating to specific travellers, 3,090 (18.9%) concerned VFR travellers and 7,237 (44.2%) concerned tourists. Compared with tourists, VFR travellers were younger (median age 24 vs 52 years, P<0.001), more likely to undertake long-stay (8.4% vs 1.8%, P<0.001) and last-minute travel (5.0% vs 1.1%, P<0.001), and more frequently travelled to the WHO African Region (56.6% vs 29.2%, P<0.001) and Eastern Mediterranean Region (12.7% vs 2.8%, P<0.001). Pregnancy was substantially more common among VFR travellers (11.6% vs 4.3%, P<0.001). Enquiries concerning VFR travellers were more likely to require a call-back (16.1% vs 13.8%, P=0.012) and escalation to a specialist doctor (13.1% vs 10.5%, P<0.001), indicating greater consultation complexity. General practice generated a higher proportion of VFR-related enquiries than tourist enquiries (69.5% vs 63.9%, P<0.001). Conclusions: VFR travellers generate disproportionately complex pre-travel consultations characterised by higher rates of specialist escalation, distinct travel patterns and travel to destinations associated with the greatest burden of imported infectious diseases. These findings highlight the importance of specialist travel medicine support for healthcare professionals managing VFR travellers and reinforce the need for equitable access to timely, high-quality pre-travel healthcare for this high-risk population.

Background Dengue is intensifying globally due to climate change, urbanization, and land use changes. In Nepal, dengue has expanded from lowland regions to higher altitudes, with record outbreaks in 2022 and 2023. However, reliance on passive surveillance and hospital-based studies may underestimate community level infection burden. Methods We conducted a population-based serologic cohort study in Kathmandu and Kavrepalanchok districts, Nepal, enrolling a geographically representative, age stratified random sample of residents aged 0 to 25 years from pre-defined hospital catchment areas. Enrollment occurred in two phases: Phase I (February 2019 to April 2021) with follow-up visits at approximately 3, 6, and 12 months, and Phase II (February to June 2023) revisiting the original cohort. At each household visit, we collected capillary blood samples by finger-prick onto filter paper and tested the samples for IgG responses against dengue-derived recombinant antigen using InBios DENV DetectTM ELISA. Serostatus was classified using the manufacturer's recommended immune status ratio (ISR) cutoffs. We calculated seroprevalence at each time point and estimated seroincidence rates by identifying seroconversion events per 1,000 person-years. We assessed risk factors using multivariable regression models. Results Between 2019 and 2023, we enrolled 840 participants and collected 2,082 blood samples. The overall seroincidence rate was 33.8 per 1,000 person-years (95% CI [24.9 to 45.0]), with the highest rates in urban Kathmandu ([105.7], 95% CI [75.1 to 144.4]). Seroincidence increased with age and over time from 46.1 in 2019 to 51.0 in 2023. Participants living with a dengue-positive individual in the same household (adjusted RR [4.65], 95% CI [2.72 to 8.0]) and households with water-filled flower basins (adjusted RR [2.53], 95% CI [1.28 to 5.74]) had significantly higher risk of seroconversion. Conclusions This study reveals a significant and increasing burden of dengue infection in the Kathmandu Valley between 2019 and 2023. highlighting an urgent need for immediate public health interventions to mitigate dengue's rise in Nepal's higher-altitude regions.

Respiratory diseases cause considerable morbidity in autumn and winter and are a priority in public health monitoring. In Germany, they are subject to a number of surveillance systems, including both pathogen-specific and syndromic indicators. In this paper we present a collaborative multi-target and multi-model real-time forecasting system rolled out during the 2024/25 season, and discuss differences to earlier efforts carried out during the COVID-19 pandemic. A total of nine models were run to generate forecasts of general practitioner consultations for acute respiratory infections (ARI), hospitalizations for severe acute respiratory infections (SARI) and confirmed cases of seasonal influenza and RSV. As all indicators were subject to retrospective revisions, forecasting models were combined with a nowcasting step. Whenever multiple models were available for the same indicator, we combined them into an ensemble. Nowcasts showed convincing performance, even though for some models Christmas break effects led to an upward bias in early January. Forecasts were overall well-calibrated and most models outperformed simple benchmark models. These improvements were generally more substantial for age-stratified than pooled targets, and concentrated at lead times of two to three weeks. Anticipating the peak timing and magnitude proved to be challenging, with many models predicting too flat curves with a too early turnaround (e.g. already in late January rather than mid-February for SARI). The combined ensemble forecast was among the best-performing approaches, but unlike in previous related projects did not consistently outperform individual models. We conclude by discussing learnings on the organization of collaborative forecasting projects in post-COVID-19 times and the potential of AI-supported modelling.

We develop a mathematical model of Rift Valley Fever integrating mosquito vectors, ruminants, and humans, based on an SEIR-type structure with vertical transmission in vectors. Local data from the Sudanian and especially the Sahelian zones are used to capture the impact of climatic variations on mosquito population dynamics. The mathematical analysis establishes the models positivity, determines the basic reproduction number R0, and demonstrates the local and global stability of the disease-free equilibrium. Sensitivity analysis (PRCC) highlights the most influential parameters, while the stochastic approach using a continuous-time Markov chain confirms the major role of seasonal rainfall. Numerical simulations reveal a peak in animal and human infections around the 9th month, correlating with periods of heavy rainfall. This model provides a relevant tool for surveillance and prevention within a "One Health" approach in Chad.

Background. The 2026 Bundibugyo virus disease (BVD) epidemic in the Democratic Republic of the Congo (DRC) was declared on 15 May 2026 and determined a public health emergency of international concern on 17 May 2026. Public surveillance reporting consists of cumulative counts by report date; no line list with symptom-onset dates is available. Widely circulated characterisations - that this is the fastest-growing Ebola outbreak on record, that reported cases are doubling every 22 days, and that the case fatality ratio (CFR) is 37.5% - rest on these aggregates. We examined what the published data actually support. Methods. We assembled twelve published anchor points from 15 May to 13 July 2026 from WHO, WHO AFRO, NICD and the DRC National Institute of Public Health; one was recovered by back-calculation and checked against the directly reported subsequent total. We computed mean daily incidence between anchors and the within-interval death-to-case ratio. We reconstructed symptom-onset dates by Richardson-Lucy deconvolution with right-truncation correction under assumed onset-to-report delays with means of 5, 7 and 9 days, estimated the instantaneous reproduction number using the Cori method, and computed three CFR estimators: crude, resolved-case and outcome-delay-adjusted. Provincial CFRs used exact binomial intervals. Results. Confirmed cases plateaued at 40-52 per day for eighteen days, from 25 June to 13 July. Over the same period, the within-interval death-to-case ratio rose from 0.28 to 0.58. Reconstructed Rt was 1.28, with a 95% credible interval of 1.15-1.41, on 7 July, having fallen from approximately 2.9 in mid-May. Growth on the reconstructed onset curve corresponded to a doubling time of approximately 90 days, compared with 22 days computed from cumulative counts. CFR estimates were 37.5% for the crude estimator, 50.2% for the outcome-delay-adjusted estimator and 67.3% for the resolved-case estimator. Crude provincial CFR was 34.9% with a 95% confidence interval of 32.7-37.1 in Ituri, 58.2% with a 95% confidence interval of 50.7-65.5 in North Kivu, and 81.0% with a 95% confidence interval of 58.1-94.6 in newly affected provinces. Conclusions. A flat case count accompanied by a rising death-to-case ratio is difficult to reconcile with a transmission plateau and is consistent with saturated case detection. Reported case counts appear to have substantially decoupled from transmission and cannot presently distinguish control from detection failure. Doubling times computed from cumulative totals are artefacts. Test volume and positivity by health zone are the critical missing denominators.

Aim: To assess temporal trends in incidence and mortality and project the future burden of five major gastrointestinal cancers in Jiangsu Province, China. Methods: Population-based cancer registry data from Jiangsu Province between 2010 and 2021 were used to analyze the burden of esophageal, gastric, colon, rectal, and liver cancers. Age-standardized incidence and mortality rates were calculated and compared by cancer type, sex, and urban-rural residence. Joinpoint regression was used to estimate annual percentage changes (APC) and average annual percentage changes (AAPC). The APC from the most recent Joinpoint segment was used to project incidence and mortality rates to 2030. Results: In 2021, gastric cancer had the highest age-standardized incidence and mortality among the five cancers. Incidence and mortality were consistently higher in males than in females and increased markedly after 50 years of age. From 2010 to 2021, age-standardized incidence and mortality declined for esophageal, gastric, and liver cancer, but increased for colon and rectal cancer. Colon cancer showed the steepest increase in both incidence and mortality. Rural areas experienced faster increases in colon and rectal cancer burden than urban areas. Projections to 2030 suggest continued declines in esophageal, gastric, and liver cancer, while colon cancer incidence and mortality are expected to rise further. Conclusion: Jiangsu Province is experiencing a transition in gastrointestinal cancer burden, with continued declines in esophageal, gastric, and liver cancers but an emerging and growing burden of colorectal cancer, especially colon cancer. Prevention strategies should focus on expanding colorectal cancer screening and early diagnosis, particularly in rural areas, while sustaining control of esophageal, gastric, and liver cancers.

Background: Zoonotic infectious disease risk arises at human-animal-environment interfaces where pathogen spillover can occur. Rural communities living in biodiverse settings may experience frequent contact with wildlife and shared environments through livelihoods, food practices, and economic activities. Reducing spillover risk and strengthening pandemic prevention requires both structural and individual-level change. Community-based interventions that promote awareness, risk perception, self-efficacy, pro-environmental behaviour, and safe coexistence with wildlife may support prevention by shifting behavioural determinants of zoonotic disease risk. The Saan Suk intervention was co-developed with rural communities in Thailand using a Human-Centred Design approach and is grounded in the Health Belief Model and One Health principles. The intervention is intended to be feasible, acceptable, and deliverable through Thailands established Village Health Volunteer (VHV) system. Methods: This protocol describes a parallel-arm, cluster-randomised controlled superiority trial that will be conducted during July - October 2026, in Chanthaburi Province, Thailand. 24 villages will be equally randomised to the Saan Suk intervention or the current practice (control). In intervention villages, trained VHVs will deliver, once a week over four weeks, a multimodal One Health educational intervention designed to improve knowledge of zoonotic spillover, promote protective behaviours, reduce risky wildlife-related contacts, and support respectful coexistence with wildlife. Trained outcome assessment teams will conduct structured interviews with 42 adult participants per village, yielding a total sample size of 1,008 participants. The sample size was calculated for the primary outcome, accounting for clustering, with 90% power to detect a medium effect size (6 points on the 0-100 knowledge scale) at a significance level of 0.05, accounting for a design effect with an ICC of 0.028. The primary outcome is knowledge of zoonotic spillover, transmission pathways, risk factors, protective and risky behaviours, and safe coexistence with wildlife. Secondary outcomes include attitudes, self-efficacy, preventive and risky behaviours, and reported contacts with major local reservoir hosts. A structured questionnaire was developed, expert-reviewed, and piloted for the outcome assessment. Outcomes will be analysed using mixed-effects regression models with random effects for village and adjustment for relevant pre-specified confounders. Primary analyses will follow the intention-to-treat principle. Discussion: This trial will evaluate whether a co-designed, VHV-delivered One Health educational programme can improve knowledge of zoonotic disease prevention and behavioural determinants in rural communities living in close contact with wildlife and shared ecosystems. If effective and feasible, Saan Suk could inform integration into routine VHV training and community-based zoonotic disease and pandemic prevention strategies. Trial Registration: The Saan Suk trial is registered with the German Clinical Trials Register (DRKS). Registration ID: DRKS00038582; date of registration: 11 May 2026.

Estimating dengue force of infection (FOI) is essential for understanding transmission dynamics and targeting intervention programmes, yet surveillance data in endemic settings required for estimations are often incomplete, with varying formats. We developed a Bayesian hierarchical catalytic model that jointly fits age-stratified case data, aggregate case data, and seroprevalence surveys within a single framework, incorporating external covariates to improve parameter identifiability. Synthetic validation showed that covariates alone recovered accurate FOI point estimates even when most districts contributed only aggregate data, but did so with poorly calibrated uncertainty; anchoring the model with a single seroprevalence survey was necessary to bring credible interval coverage close to nominal. Applied to 128 districts across Java and Bali, Indonesia (2016-2024), the model revealed substantial spatial heterogeneity in FOI and reporting rates. Many districts in Java exceeded the WHO-suggested seroprevalence threshold for vaccine introduction, yet were classified as low-priority when using reported incidence as prioritisation criterion, particularly in areas with weak surveillance. Model-based seroprevalence estimation, integrating multiple data sources, offers a more consistent basis for identifying high-priority districts for vaccine introduction, and is less susceptible to surveillance bias than reported incidence.

Background Serosurveillance can estimate the prevalence of antibodies (Ab) acquired through vaccination or current and/or past infection. Multi-pathogen serosurveillance that measures multiple Ab simultaneously, can enable identification of vulnerable sub-populations with immunity gaps to vaccine preventable diseases (VPD) and concurrent burden of neglected tropical disease (NTD), including those nearing elimination (lymphatic filariasis [LF], trachoma) and eradication (yaws). This study aimed to estimate seroprevalence and identify temporal trends of selected VPDs and NTDs in Samoa to inform targeted public health action. Methodology/Principal Findings Dried blood spots were collected from four repeated community-based surveys in eight primary sampling units (PSU) in Samoa in 2018, 2019, 2023 and 2024. Multiplex bead assays were used to detect Abs against antigens (Ag) for diphtheria, measles, rubella, tetanus, LF [Wb123 or Bm14], yaws [both Rp17 and TmpA; <14 years only], and trachoma [Pgp3; <14 years only]. Seroprevalence estimates were adjusted for sampling design and standardised for age and sex. Overall, 2,871 participants were included in this analysis. Seroprevalence of measles increased from 42% in 2018 to 95% in 2024, whereas diphtheria decreased from 79% in 2018 to 65% in 2024. Seroprevalence to yaws remained <1% for all years, whereas trachoma decreased from 21% to 7% (2018-2024). LF seroprevalence decreased between 2018 and 2024 for Bm14 (37% to 9%) and increased for Wb123 (10% to 22%). This study identified 15 (0.5%) individuals who were seronegative to all VPDs (7 in 2018; 8 in 2019); of these, five were seronegative to all VPDs and seropositive to at least one NTD. Conclusions/Significance Identification of sub-populations with concurrent seronegativity to VPDs and seropositivity to NTDs underscores the potential role of multi-pathogen serosurveillance in directing public health interventions to those at greatest risk. Examination of temporal patterns offer a valuable tool for measuring intervention impacts and progress towards elimination goals.

Background. The 2018-2020 Ebola virus disease outbreak in the Democratic Republic of the Congo (DRC) was the country's largest, and the second largest globally, amid armed conflict and community mistrust. Transmission heterogeneity (superspreading) is recognised in Ebola epidemics, but empirical estimates of its extent and determinants remain scarce for DRC outbreaks. We quantified transmission heterogeneity and its determinants during this outbreak. Methods. In this retrospective observational study, we reconstructed transmission chains for confirmed and probable cases (Aug 1, 2018, to June 25, 2020) using routinely collected Ministry of Health and Medecins Sans Frontieres surveillance data. We modelled the offspring distribution with a Bayesian negative binomial framework, correcting for incomplete contact tracing, to estimate the effective reproduction number (Reff), dispersion parameter (k), and proportion of cases responsible for 80% of transmission (prop80), overall, by subgroup, and over time. Individual-level determinants were assessed with a regression extension, adjusting for covariates. Findings. Among 3481 cases, 2008 transmission events linked 2402 (69%) individuals into 415 chains (median size 3, range 2-102). Overall Reff was 1.00 (95% CI 0.92-1.08) with k 0.29 (0.26-0.32); 17.8% of cases generated 80% of transmission. Overdispersion stayed stable despite fluctuating Reff. Non-isolation (IRR 1.79), death outside a treatment centre (IRR 4.34), and unfollowed contact status (IRR up to 4.48) predicted more secondary cases; vaccination cut transmission by about 60%. Interpretation. Epidemiological investigations linked 67.7% (2356/3481) of cases into 415 transmission chains (median size 3, range 2-102); linkage to a known infector fell to 10% during the November 2018-February 2019 period of peak insecurity. Transmission was heterogeneous overall, with dispersion parameter k of 0.29 (0.26-0.32), such that 17.8% (16.8-18.9) of cases generated 80% of onward transmission confirming superspreading as a stable, structural feature of Ebola dynamics. Critically, k remained stable throughout the outbreak, including during periods of elevated Reff, indicating that transmission surges reflected intensification of the same underlying process rather than new superspreading contexts, and that Reff alone is an insufficient summary of epidemic potential. Regression analyses identified predominantly modifiable determinants: cases not isolated in an Ebola treatment centre (IRR 1.79 [1.54-2.06]) or who died outside one (IRR 4.34 [3.47-5.31]) generated substantially more secondary cases, as did those registered as contacts but not followed up (IRR 3.01 [2.39-3.70]) or unregistered altogether (IRR 4.48 [3.67-5.38]) relative to actively followed-up contacts. Vaccination reduced onward transmission by 60-64% (IRR 0.36-0.40). These findings indicate that transmission was shaped less by gaps in epidemiological knowledge than by the operational reach of contact tracing, isolation, and vaccination delivery, particularly during periods of insecurity.

Background: Cholera outbreaks can spread rapidly, which means that the optimal decision-making window for a large, coordinated response is very narrow. Alerts for triggering interventions need to balance tradeoffs between wasting resources on false positives and delaying decisions until they lose effectiveness. A systematic evaluation of such tradeoffs across settings is needed to understand which alerts may have the greatest public health utility and where. Methods: Using weekly suspected cholera surveillance across 4,081 subnational administrative units across 34 countries in Africa from 2010-2023, we evaluated 24 alert definitions (4 alert types with different numeric thresholds) over a 1-year post-alert period on five utility dimensions - potential health impact, potential intervention efficiency, positive predictive value (PPV) for large outbreaks, proportion of missed outbreaks, and timeliness of alert trigger. The dimensions were combined into a utility score, which was used to identify the best alert across the continent and by country. For top-performing alerts, we estimated the reduction in potential health impact for additional delays in response using Bayesian hierarchical models. Results: Fifty suspected cases for three consecutive weeks was the definition with the highest utility score across most contexts. In administrative units with 50,000 to 500,000 people, the year following such an alert experienced a mean of 376 suspected cases (standard deviation: 618.3) and 2 cases per 1000 population (SD: 4.1). Forty percent of such alerts (N alerts: 265) were followed by a 1-year period with over 300 cases, yet the definition missed 40% of outbreaks with over 300 cases (N outbreaks: 278) and was triggered 5.3 weeks (SD: 5) after outbreak start. Each week of delay was estimated to result in an additional 20% reduction (95% CrI: -23 to -17) of potential health impact in the outbreak response. One hundred cases over a three-week period was another definition that had high utility, particularly in administrative units with smaller populations and country-specific evaluations. Conclusion: We present a decision analytic framework that can be deployed in a short decision-making window using case-based surveillance to trigger large-scale cholera response activities with moderately high utility across most African transmission contexts. Future work should consider adaptations based on local data availability and priorities and examine the generalizability of early case-based signals outside Africa.

CRISPR-Cas12a nucleases are classically activated through CRISPR RNA (crRNA) guided and PAM-dependent target recognition, which together establish a canonical heteroduplex associated with nuclease activation. Here we identify a crRNA- and PAM-independent activation pathway for Cas12a that reveals previously unrecognized conformational plasticity within its nucleic acid recognition interface. We show that short RNAs can directly occupy the canonical crRNA-binding channel and trigger a catalytically competent trans cleavage state in the absence of PAM recognition or canonical R-loop formation. Biochemical assays indicate that short RNAs bind the crRNA-binding channel and are competitively displaced by cognate crRNA, consistent with binding at a conserved nucleic acid-binding interface. Cryo-electron microscopy (cryo-EM) further reveals that Cas12a maintains its global catalytic architecture while exhibiting loss of canonical PAM-dependent stabilization and increased flexibility of the RuvC lid, alongside accommodation of a noncanonical RNA-DNA hybrid with inverted polarity relative to the crRNA-target duplex. This crRNA-independent activation pathway enables programmable, amplification-free detection of DNA and RNA targets independent of canonical guide-mediated recognition. Together, these findings define an alternative activation geometry for Cas12a and expand models of Class 2 CRISPR-Cas effector activation beyond crRNA- and PAM-directed recognition.

Background and Aims The optimal treatment for first episodes and first recurrences of Clostridioides difficile infections (CDI) is unknown and there is emerging evidence for pulse and taper (P-T) regimens. Therefore, we sought to estimate the relative efficacy of treatment options. Methods MEDLINE and CENTRAL were searched from database inception to May 21, 2025 and unpublished conference abstracts were searched from recent infectious disease conferences. RCTs on the treatment of first episodes or first recurrences of CDI comparing fixed-dose or P-T regimens of fidaxomicin or vancomycin were included. The primary and secondary outcomes were 40- and 56-day CDI recurrence, respectively. A random-effects network meta-analysis on the risk ratio (RR) scale was conducted using a standard regimen (10-14 days) of vancomycin as the comparator. Treatments were ranked using the surface under the cumulative ranking curve (SUCRA). Results 8 RCTs were included comprising a total of 2181 patients. For 40-day recurrence, fidaxomicin P-T had the highest probability of ranking best (RR=0.10, 95%Confidence Interval [95%CI]=0.10-0.49, SUCRA=1.00), followed by vancomycin P-T (RR=0.49, 95%CI=0.32-0.76, SUCRA=0.61), fixed-dose fidaxomicin (RR=0.61, 95%CI=0.49-0.76, SUCRA=0.39), and, finally, fixed-dose of vancomycin (SUCRA=0.00). The treatments ranked in the same order for 56-day recurrence, though only 3 RCTs reported on this timepoint. Conclusion Vancomycin P-T, fidaxomicin P-T, and fixed-dose fidaxomicin were all superior to a fixed-dose vancomycin. Head-to-head comparative effectiveness RCTs are needed to quantify their relative effect sizes of and impact on long-term prevention of recurrent CDI.