Infectious Diseases of Poverty

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.

Introduction Globally and in Africa, HIV mortality is reported to have decreased over the years. Cameroon's national mortality rate was 1.7% in 2023, and there exist regional disparities and underreporting. We assessed the mortality and associated factors among People Living with HIV(PLHIV) initiated into HIV care from January 2021 to December 2023 at the Bamenda regional hospital (BRH) Methods A retrospective cohort study was conducted from June 2024 to December 2024 at the BRH. Using a non-probabilistic consecutive sampling technique, 331 newly initiated participants on ART were included. Data was collected from medical records using a questionnaire and analyzed using R software version 4.3.1. A multivariable Cox regression model included variables that showed statistical significance and assessed their relationship with mortality while adjusting for potential confounders. Significant predictors of mortality were identified. Results The mean age of participants was 41.6 {+/-} 11.7 years, and females constituted 57.7%. Opportunistic diseases were present in 19.0% of cases, with tuberculosis (8.2%) being the most common. Key comorbidities included hypertension (8.8%), diabetes (3.9%), and hepatitis B (3.0%). Blood tests showed elevated liver enzymes (ALAT/ASAT: 41.7{+/-}23.6 U/L) and high blood sugar (144.4{+/-}7.4 mg/dL). In contrast, kidney function (Creatinine: 0.9{+/-}0.2 mg/dL) and immune cell counts (Lymphocytes: 1.8{+/-}0.7 x103/L) appeared normal overall. A cumulative mortality rate of 7.6% over three years (approximately 2.5% per year) was observed. Male sex (AHR=7.83, 95% CI:1.44-42.5, p=0.017), opportunistic diseases (AHR=5.66, 95% CI:1.71-18.7, p=0.004), comorbidities (AHR=6.04, 95% CI:2.02-18.1, p=0.001), Abnormal ALAT/ASAT (p=0.005), and WHO clinical stage III (AHR: 1.1, 95%CI: 1.01 -1.5, p < 0.001), were identified as predictors of mortality. Whereas, BMI and ART adherence showed no significance. Conclusion Mortality among PLHIV in this study was associated with advanced disease, opportunistic diseases, commorbidities and abnormal laboratory findings. Strengthening early diagnosis, management of opportunistic infections, and monitoring of clinical and laboratory indicators may help reduce mortality in this population.

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.

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 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.

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.

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.

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.

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.

We aimed to assess the burden and correlates of late diagnosis of cervical cancer among women attending care at a public health facility in Coastal Kenya. A retrospective cross-sectional design was used. Data extracted from medical records of women already diagnosed with cervical cancer at Kilifi County Referral Hospital (KCRH) were used. Logistic regression was used to assess independent predictors of late diagnosis of cervical cancer. A total of 126 patients were included in this analysis. Out of the 126 participants, 67.5% (n=85) were 50 years and older with a mean age of 54 years. Among the 126 participants whose records were included in analysis, 73.0% (n=92; [95% CI: 64.3 - 80.5]) were diagnosed with late-stage cervical cancer. In multivariable analysis, none of the variables included in the model showed an association with the outcome. In conclusion, we found a high burden of late diagnosis of cervical cancer in this setting. Targeted interventions are warranted to reverse this trend.

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.

ABSTRACT Background: Vaccination coverage in Brazil declined between 2015 and 2022, followed by a recovery in 2023 and 2024. Given this instability, driven by multiple determinants, we sought to identify factors associated with childhood vaccination and group Brazilian municipalities into scenarios that could guide interventions to improve coverage. Methods: In this ecological study of 5,274 Brazilian municipalities, we assessed the rate of children under 1 year unvaccinated with the third dose of the Inactivated Poliovirus Vaccine (IPV) in 2024, chosen for its high correlation with other tracer vaccines such as Diphtheria, Tetanus and Pertussis (DTP) and Measles, Mumps and Rubella (MMR). We applied a hierarchical model with three levels of determinants (socioeconomic, health service structure, and operational), using Poisson regression to estimate standardized Rate Ratios (RR), followed by a K-means cluster analysis to identify municipal profiles. Results: Several determinants were associated with higher rates of unvaccinated children, most notably the proportion of the population not covered by Community Health Workers (CHW) (RR = 1.15; 95% CI 1.14-1.15) and inequality measured by the Gini Index (RR = 1.33; 95% CI 1.32-1.34). We identified six municipal profiles that differed in tracer-vaccine coverage up to four years of age and in the composite Vaccination Needs Index (VNI). Conclusion: Multiple socioeconomic, structural and operational factors were associated with unvaccinated rates, highlighting the relevance of healthcare service organization even in favorable social contexts. Classifying municipalities into risk profiles may support more targeted interventions aligned with local needs. Keywords: Vaccination coverage, Childhood vaccination, Primary Health Care, Determinants, Scenarios, Profiles.

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 [&ge;] 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.

Red blood cell (RBC) disorders arose as an advantageous evolutionary response to malaria infections. In a heterozygous condition, such as in Southeast Asian Ovalocytosis (SAO), hosts are protected against severe malaria. In malaria-endemic regions, RBC disorders are presumed to be highly prevalent. Tanjung Leidong, a moderately endemic area in North Sumatra (API 1.13 in 2024), lacks comprehensive data on RBC disorder prevalence beyond G6PD deficiency. Therefore, this study aims to characterize the RBC disorders in this region as well as to characterize the anemia status in children living in Tanjung Leidong. Schoolers attending D. I. Panjaitan elementary to high school were recruited and screened for malaria by microscopy and G6PD deficiency using the STANDARD G6PD Assay. The DNA of the participants was also extracted to be genotyped for SAO, Hemoglobin E (HbE), and -thalassemia. Exclusively, G6PD-deficient DNA samples were genotyped further to determine variants. The proportion of G6PD deficiency, SAO, HbE, -thalassemia one-gene deletion, and two-gene deletion were 0.90%, 0.90%, 2.40%, 6.26%, and 0.30%, respectively. Anemia prevalence was approximately 14%, and RBC disorders were observed across children with normal to obese BMI. No malaria infections were detected by microscopy. The predominance of asymptomatic RBC disorders highlights that they are protective against malaria infection, although their protective role against malaria could not be directly assessed in this study. Both nutritional and genetic factors are found to contribute to anemia in this cohort. These findings underscore the importance of integrated screening strategies for RBC disorders and anemia in malaria-endemic settings.

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: 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.

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.

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.

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.