Parasites & Vectors

Larval source management (LSM) is a complementary malaria control intervention, yet evidence to guide context-specific implementation remains limited. Nigeria's recent national commitment to LSM scale-up makes the need for operational evidence particularly urgent. Informal settlements embedded within wards of differing dominant settlement archetypes may present distinct Anopheles larval habitat profiles with implications for how LSM strategies should be tailored. We evaluated Anopheles larval habitats within informal settlement areas across wards with contrasting settlement archetypes in Ibadan metropolis, Nigeria, to inform targeted larval source management. Potential breeding habitats were surveyed in dry and wet seasons within informal settlement areas across three wards -- Olopomewa, Challenge, and Agugu -- representing formal, informal, and slum settlement-dominant archetypes respectively. Habitats were characterized and assessed for Anopheles larval presence. Pareto analysis identified habitats accounting for 80% of larval abundance. Breeding habitat density per km{superscript 2} was estimated using a simulated pathway technique. Associations between mosquito dispersal scale and household malaria infections identified through Rapid Diagnostic Testing were evaluated using kernel-based distance-decay weighting. Environmental drivers of habitat suitability were modeled in MaxEnt. Of 420 potential breeding habitats identified, 31 (7.4%) contained Anopheles larvae, predominantly during the wet season (26, 83.9%). Puddles, dug wells, drainages/gutters/ditches and canals accounted for 80% of site-level larval abundance when standardized by sampling effort. Larval and breeding habitat density were highest in Agugu, the slum-dominant ward, across both seasons. Modeled mosquito dispersal scale showed best fit at 30-32m in Challenge (OR 1.41, 95% CI: 1.05-1.89) during the wet season and 16-18m in Agugu (OR 1.29, 95% CI: 1.04-1.60) during the dry season. Habitat suitability in Agugu was higher farther from large water bodies and in areas with higher population density and positive Normalized Difference Water Index values. In Challenge, suitability was higher in areas with lower nighttime light levels, positive Normalized Difference Water Index values, and negative Normalized Difference Moisture Index values. Further studies incorporating multiple wards across diverse urban settings are needed to determine whether differences in larval ecology between settlement archetypes provide a reliable basis for planning larval source management.

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.

Objectives: Although HIV incidence has declined in some settings, the overall global burden of sexually transmitted infections remains a major public health concern. In the context of the World Health Organization's call for people-centred STI prevention and care, identifying the shared geographic pattern of multiple STIs using data-driven analysis may help detect vulnerable areas and inform integrated prevention strategies. Methods: We analysed country-level incidence counts from the Global Burden of Disease 2023 study for 204 countries and territories over 1990-2023. A Bayesian shared-component spatiotemporal model was fitted, decomposing each disease's log-rate into a shared spatial component (scaled intrinsic conditional autoregressive prior), disease-specific spatial deviations, disease-specific first-order random walk temporal effects, and five socioeconomic covariates, with a negative binomial likelihood to accommodate overdispersion. The shared spatial score - the posterior mean of the shared spatial component - was used as a continuous index of STI co-occurrence burden. Posterior exceedance probabilities quantified directional stability. External validity was assessed via Spearman correlation with the Socio-demographic Index and generalised estimating equation regression of HIV/AIDS mortality on the shared score. Results: The shared spatial score exhibited marked geographic heterogeneity. The five highest-scoring countries were Eswatini (2.25), Lesotho (2.13), Malawi (1.90), Mozambique (1.89), and South Africa (1.85), all in southern Africa. Fifty-seven countries had high directional stability (posterior exceedance probability >0.95), concentrated in sub-Saharan Africa and the Caribbean. The score correlated negatively with SDI (Spearman rho = -0.619, p = 6.4 x 10^-23) and positively with HIV/AIDS mortality (incidence rate ratio = 14.64 per standard deviation, 95% CI: 11.90-18.01). Prior sensitivity analysis confirmed near-perfect ranking stability (rho >= 0.9999). Conclusions: STI co-occurrence is geographically concentrated, with the highest shared burden in sub-Saharan Africa and persistently elevated shared spatial signals also observed in parts of mainland Southeast Asia and the Caribbean. The shared spatial score provides a data-driven tool for prioritising integrated STI screening and prevention resources across countries.

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.

Snakebite envenoming is a major neglected tropical disease disproportionately affecting rural populations in sub-Saharan Africa. In Ghana, evidence on the spatial and temporal distribution of risk remains limited, constraining targeted prevention and resource allocation. This study quantified district-level snakebite risk across Ghana, identified persistent hotspots and environmental drivers, and evaluated the relationship between snakebite burden and geographic access to treatment. Monthly district-level snakebite cases from Ghana's District Health Information Management System (2020 to 2025) were analyzed across all 261 districts using a Bayesian spatio-temporal model incorporating spatial effects, a temporal random effect, and a space-time interaction, fitted via Integrated Nested Laplace Approximation. Environmental covariates including rainfall, temperature, humidity, and NDVI quantified associations with risk. Relative risks, exceedance probabilities, Local Indicators of Spatial Association, and geographic accessibility identified priority districts. Snakebite risk showed strong spatial clustering and temporal variation. Persistent high risk districts were concentrated in Upper West (Daffiama Bussie Issa, Wa East, Wa West, Sissala East), Savannah (Bole, Gonja), North East (Mamprugu Moagduri), Western North (Bia East), Bono (Banda), Oti (Krachi Nchumuru), Western (Wassa East), and Eastern Region (Nsawam Adoagyiri, Fanteakwa North), though patterns evolved. Fanteakwa North emerged as the highest risk district nationally in 2025. Humidity and temperature were associated with increased risk, while rainfall and NDVI showed no significant effect. High risk districts often had poor treatment access, revealing inequities. This first nationwide Bayesian spatio temporal assessment provides an evidence base for surveillance, antivenom distribution, and interventions supporting WHO's 2030 snakebite reduction goals.

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.

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.

Histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) are central to malaria case management in Africa but fail when Plasmodium falciparum parasites lack the pfhrp2 or pfhrp3 genes. Widespread deletions have been reported in Eritrea, Ethiopia, and Djibouti, yet no systematic data have been available from Somalia. Between May and October 2023, we collected 7148 dried blood spot (DBS) samples from patients with suspected malaria attending eight health facilities across seven regions in Somalia. Field HRP2/pan-lactate dehydrogenase (LDH) RDTs and microscopy were performed, and DNA was extracted from 301 RDT-positive and 173 RDT-negative DBS samples. A multiplex quantitative PCR assay targeting pfldh, pfhrp2, and pfhrp3 was used to identify deletions in pfldh-positive samples lacking pfhrp2 or pfhrp3 amplification, with mixed infections inferred from delta cycle threshold ({Delta}Ct) differences. Of 474 analysed samples, 301 (4.2%, 95% CI 3.7-4.7) were RDT or microscopy positive, and 159 (33.5%) were confirmed pfldh-positive by qPCR. Among these, six (3.8%, 95% CI 1.4-8.1) carried pfhrp2 deletions and 59 (37.1%, 95% CI 29.6-45.1) carried pfhrp3 deletions. Eleven infections (6.9%, 95% CI 3.5-12.1) produced discordant RDT outcomes, HRP-/LDH+ or RDT-negative despite pfldh positivity. Deletions were most frequent in Dolow, Luq, and Bosaso. A single isolate carried the pfk13 R622I mutation, confirming the first report of the emergence of an artemisinin partial resistance-associated in Dolow, Gedo region, Somalia. Pfhrp2/3 deletions causing false RDT results remain low in Somalia and the confidence interval overlaps with the 5% policy threshold for changing RDTs, indicating uncertainty that warrants larger-scale assessment. Pfhrp3 deletions are widespread and compromise the diagnostic redundancy of HRP2-based tests. Most deletion-carrying parasites remain detectable through the pan-LDH line, minimising immediate clinical risk but leading to systematic misclassification of P. falciparum as non-falciparum malaria. These findings support the continued use of HRP2/Pan-LDH RDTs but highlight high risk areas and emphasise the need for periodic and expanded molecular surveillance for prevalence trends to guide timely future diagnostic policy.

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.

Malaria remains a severe health problem in endemic regions because people lack adequate diagnostic tools, leading to delayed medical care and elevated death rates. This research introduces a dual-mode artificial intelligence system that uses two complementary models to enhance malaria pre-screening and diagnosis. The patient-centered model uses multivariate logistic regression to analyze biosignals, including heart rate, body temperature, and oxygen saturation, collected through a wearable sensor prototype and a mobile interface for symptom analysis. The system enables patients to begin self-assessment to determine their level of need before scheduling a doctor's appointment. The clinician-centered model represents a customized convolutional neural network that uses annotated microscopy images of red blood cells to achieve 94.84% accuracy, 95.71% precision, 93.87% recall, 94.78% F1 score, and 0.84 Area Under Curve (AUC). The patient model achieved 94.6% accuracy and an AUC of 0.985 using a 70/30 train-test split. These systems work together to create a layered diagnostic system that can operate independently or together to detect malaria at an early stage, especially in areas with limited resources. The findings demonstrate that wearable biosignal data integration with image-based deep learning can produce dependable, scalable, and user-friendly systems for malaria pre-screening. Keywords - malaria diagnosis, artificial intelligence (AI), convolutional neural networks (CNN), wearable biosensors, multivariate logistic regression

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: 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.

Background Coccidioidomycosis is an emerging fungal disease across the arid Americas and a frequent cause of community-acquired pneumonia. Understanding where Coccidioides populations originate, how they move across space, and whether they are expanding is important for interpreting changing patterns of Valley fever and anticipating future infection risk. Methods We prospectively collected and whole-genome sequenced 186 Coccidioides-positive clinical isolates submitted to a national diagnostic laboratory, and included 126 previously sequenced genomes. We applied genomic clustering, time-calibrated phylogenetic reconstruction, ancestral area reconstruction, mating-type assignment, and demographic inference to identify major populations, infer dispersal patterns, assess evidence for recombination and clonality, and reconstruct historical population dynamics. Findings We analyzed 312 genomes (139 C. immitis; 173 C. posadasii) and identified three major genetic populations within each species. C. immitis included two California-centered populations and one Pacific Northwest population, whereas C. posadasii included two Arizona-centered populations and one Texas-centered population. The most recent common ancestor was estimated at approximately 127,000 years for C. immitis and 234,000 years for C. posadasii. Most populations were not fully monophyletic, consistent with retained ancestral variation and/or ongoing gene flow. Inferred dispersal was largely asymmetric, with most movement originating from California in C. immitis and from Arizona and Texas in C. posadasii. Most populations contained both mating types, but one C. immitis population and a Brazilian subgroup of C. posadasii were clonal. All populations showed recent demographic expansion. Interpretation The evolutionary history of Coccidioides is characterized by strong geographic structure, ongoing gene flow, and recent demographic expansion. These processes are likely to influence future patterns of Valley fever endemicity and supports the use of genomic surveillance to detect shifts in disease risk as environmental conditions change.

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.

Snakebite envenoming remains a neglected tropical disease and an important public health challenge in Zambia. Effective management of snakebite patients requires healthcare workers who are adequately trained, familiar with treatment protocols, and aware of national management guidelines. However, evidence regarding healthcare worker preparedness for snakebite management in Zambia remains limited. This study explored healthcare worker preparedness for snakebite management in selected hospitals in Zambia. An exploratory cross-sectional study was conducted in seven hospitals in Zambia between collected between May and July 2025. Twenty-one healthcare workers, comprising senior clinicians, junior clinicians, and nurses, were purposively selected to participate. Data were collected using a structured questionnaire assessing training in snakebite management, clinical exposure to snakebite cases, confidence in management, use of local treatment protocols, and awareness of national snakebite management guidelines. Data were analysed using descriptive statistics and presented as frequencies and percentages. Twenty-one healthcare workers participated in the study. Eight participants (38.1%) reported having received no training in snakebite management, while six (28.6%) reported receiving bedside training. Most participants had recent experience managing snakebite patients, with 66.7% reporting management of at least one snakebite case within the preceding year. Fifteen participants (71.4%) reported being very or exceptionally confident in managing snakebite patients. However, only six participants (28.6%) reported using local snakebite treatment protocols, while eight (38.1%) had seen the latest national snakebite management guidelines. Nearly half of participants reported not using local protocols and had never seen national guidelines. The study identified important gaps in healthcare worker preparedness for snakebite management despite high levels of self-reported confidence. Limited formal training, poor guideline awareness, and low utilization of treatment protocols may affect the quality of snakebite care. Strengthening healthcare worker training and improving dissemination of national management guidelines should be prioritized as part of Zambia's snakebite control efforts.

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.

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.

Each year, over 50 million children receive preventive malaria treatment. However, to date there has been no consensus on the most effective antimalarial drugs to use, especially given geographic differences in drug resistance. Here, we conduct a systematic review comparing the effectiveness of the most commonly used antimalarial chemopreventive regimen, sulfadoxine-pyrimethamine plus amodiaquine (SP+AQ), with other antimalarial drugs in preventing new infections. We searched MEDLINE, Embase, Global Health, PubMed and WWARN clinical trial databases until 06 December 2025 for studies satisfying the inclusion criteria. Studies were included if they were peer-reviewed, randomised-controlled studies in Africa, measuring incidence of infection or clinical episodes of Plasmodium falciparum malaria for at least 28 days post-treatment. We also compiled data on the prevalence of markers of resistance in the parasite dhfr, dhps and mdr1 genes in the study areas. We conducted meta-analyses of incidence rates, with subgroup analyses by drug resistance levels. This review is registered on PROSPERO (CRD42024577149). We identified 27 studies representing 38,252 participants in 32 sites across 13 countries. In pooled analysis, SP+AQ reduced incidence of malaria by 54.6% (95% CI: 33.8-68.8%) compared to SP alone, including significantly outperforming SP even in areas with low SP resistance. These findings suggest that countries currently using SP alone for chemoprevention should consider switching to SP+AQ. Where AQ resistance remains low, available evidence suggests SP+AQ remains efficacious for malaria chemoprevention. SP+AQ was comparable to the artemisinin-based treatment, dihydroartemisinin-piperaquine across all studies (incidence rate ratio 0.93; 95% CI 0.78-1.11). By resistance levels, SP+AQ had slightly higher efficacy in areas with low SP and AQ resistance but had comparable or slightly lower efficacy in areas with higher resistance. Using artemisinin-based treatments for chemoprevention must be balanced against the risk of worsening artemisinin resistance in Eastern and Southern Africa. This study was funded by the UK Royal Society.

Introduction: Uganda has the highest number of Malaria cases in East and Southern Africa and accounted for 3% of deaths in 2020. This calls for prevention, early diagnosis and treatment of Malaria most especially among children whose condition can progress to severe Malaria within 24 hours. While numerous interventions have been put into place to prevent malaria transmission, delays in diagnosis and treatment of Malaria when ill can lead to further mortality. Therefore, factors associated with delayed access of care among children under five with malaria and their outcomes need to be explored. Methods: A cross sectional study was carried out. The target population was parents/caretakers to children under five with malaria at Mbale Regional Referral Hospital. A consecutive sampling technique was used on the target population. Quantitative data was collected using researcher administered questionnaires designed consistent with the research objectives. Collected data was analyzed using STATA version 15. Results: Among the 216 children under five admitted at Mbale regional referral hospital with Malaria, 59.26% received care from a health facility 24 hours after symptom onset. The most significant predictors of delay in seeking care were the caregiver/ parent having attained tertiary education (AOR=7.1, p value=0.02) and initially implementing other measures other than giving medication/herbs before taking a child to the health center (AOR=4.1, p value=0.00). Conclusion: Despite the numerous interventions put into place to curb the spread of malaria and to manage malaria, delayed access of care remains a significant contributor to the adverse effects of malaria among children under five. Health education on the impact of delayed access of care should be intensified at all levels of healthcare.