Infectious Diseases of Poverty

Wolbachia-mediated incompatible-insect technique (IIT) via wAlbB, wMel or wPip/wAlbA/wAlbB strains are promising approaches for suppressing wildtype Aedes mosquitoes and therefore Aedes-borne diseases. Yet, the effectiveness of this technique under climate change remains uncertain. Here, we evaluate the long-term robustness of male Wolbachia-infected mosquito releases to suppress wildtype Aedes aegypti and Ae. albopictus populations across future climate scenarios across diverse geographical regions. We compiled large publicly available datasets on Aedes abundance across Singapore, China, the European Union and the United States, historical and projected climatic conditions in these regions and conducted experiments to test the thermal stability of cytoplasmic incompatibility in Wolbachia-infected male Aedes aegypti and albopictus. A climatically-driven entomological model was developed and calibrated using a Bayesian approach to model observed Aedes population dynamics and infer area-specific climate-driven variation in mosquito life-history traits. We back-inferred historical mosquito abundance and projected mosquito abundance in future climate change scenarios incorporating experimental and locally inferred entomological parameters and then simulated the counterfactual implementation of IIT in these regions. We find that Aedes populations are projected to increase in most regions across all climate change scenarios from 2050-2100 even under high heat conditions in the absence of interventions. While we found that IIT can suppress wild-type populations effectively across all future scenarios and in high heat conditions, effectiveness was found to depend heavily on mosquito emigration rates, overflooding ratios, release intervals and release strategies Extensive robustness checks confirmed that the model reproduced historical temporal trends, captured the influence of individual parameters on outcome and was sensitive to changes in values of inferred parameters and implement policy. These findings demonstrate that IIT may be a robust vector control tool under future climate conditions.

Background Brucellosis is a severe zoonotic disease with pronounced seasonality and regional heterogeneity in high-incidence areas of China. Reliable forecasting tools are needed to inform prevention strategies, but the optimal modeling approach across different regions remains unclear. Principal Findings We collected monthly brucellosis incidence and 17 environmental variables from 2014 to 2024 across five high-incidence provinces: Inner Mongolia, Xinjiang, Shanxi, Heilongjiang, and Hebei. A three-step procedure--cross-correlation analysis, multicollinearity diagnostics, and stepwise regression--was used to select exogenous predictors. We then compared four time-series models: seasonal autoregressive integrated moving average (SARIMA), SARIMA with exogenous variables (SARIMAX), long short-term memory (LSTM), and LSTM with exogenous variables (LSTMX). All five provinces showed a unimodal seasonal pattern with peaks between April and July, though environmental drivers and optimal lag periods varied substantially by region, ranging from 1 to 6 months. In forecasting performance, LSTM achieved the highest accuracy in Shanxi (R2=0.925), Hebei (R2=0.876), and Xinjiang (R2=0.829), outperforming SARIMA and SARIMAX. LSTMX performed best in Inner Mongolia (R2=0.759) and Heilongjiang (R2=0.772) but showed weaker performance than LSTM in Shanxi and Hebei. Overall, adding exogenous variables did not consistently improve predictions across provinces. Conclusions Our findings demonstrate that LSTM-based models offer clear advantages for brucellosis forecasting in most high-incidence provinces, but the value of incorporating environmental predictors is region-dependent. These results support the development of tailored early warning systems and precision prevention strategies for brucellosis in high-risk areas of China.

The mosquito Aedes albopictus is a competent vector for the transmission of several arboviruses and is currently spreading across many continents. Since conventional control methods, like insecticides, often lead to environmental problems and the emergence of resistance, scientists developed alternative mosquito control strategies. One of the most used is the Sterile Insect Technique (SIT), which involves the mass release of males sterilized through irradiation. The Toxic Male Technique (TMT) is instead based on the release of genetically modified males expressing toxic proteins that kill females when they mate. Control strategies are often intended as methods to eradicate mosquito populations, yet a less ambitious and more cost-effective task is to reduce them such that the probability of transmission of viruses to humans becomes negligible. To compare the efficacy of these control strategies, we develop a mathematical model with two communicating compartments: a mosquito population and epidemiological model coupled with a human epidemiological model. As a proof-of-concept, we test the model using meteorological and entomological data for the Emilia-Romagna region. Our results indicate that the TMT strategy is more effective in lowering the probability of transmission and provides indication for the deployment of control strategies.

Background: Dirofilaria repens is a zoonotic parasite expanding unnoticed across Europe due to climate change. We hypothesised that in this process, the Carpathian Basin has a facilitating effect. Methods: Using 426 georeferenced European cases, the probability of infection occurrence was determined in relation to climatic factors, surface water availability, regional social deprivation, and stray dog population density. To analyse the potential impacts of ecological and social factors (deprivation and stray dog population density), the MaxEnt algorithm, and spatial Empirical Bayes smoothing and Bivariate Local Indicators of Spatial Association (BiLISA) index calculation were employed, respectively. Results: MaxEnt analysis revealed that the mean warmest month temperature (22.8 - 25.1 oC), winter mean minimum temperature (> -2.1 oC), and summer precipitation (28.6 - 231 mm) have the strongest impact on the probability of the parasite's occurrence in Europe. Social factors have significance in the eastern Balkans and the Carpathian Basin, but not in Western Europe. The Carpathian Basin appears to be a hotspot, similar to Mediterranean coastal areas. Furthermore, the Danube Valley acts as an ecological corridor for subtropical vector-borne parasites. Conclusions: Our findings confirm that summer warmth is the primary ecological driver of the parasite's range expansion, which is facilitated by the Carpathian Basin due to climatic and socioeconomic conditions.

Conventional mosquito surveillance typically relies on contemporaneous data, making it challenging to anticipate future vector surges. To support proactive vector management, this study evaluates a multi-model forecasting framework designed to generate probabilistic 1- to 4-week-ahead forecasts of Aedes aegypti relative abundance per trap night. The framework was validated using multi-year surveillance data across four US jurisdictions spanning varied environments (from subtropical to temperate and arid). We found that an ensemble approach aggregating statistical and machine learning models generally achieved the best performance across all locations and forecast horizons. Relative forecast performance improved as the forecast horizon extended from 1 to 4 weeks ahead. The most challenging data to forecast were primarily restricted to low mosquito activity periods or atypical population peaks with unusual timing or magnitude. While full integration into routine vector management workflows represents a long-term process requiring operational adaptation, this work advances forecasting research and establishes a baseline for translating these approaches into real-time applications for public health authorities, with downstream effects in mitigating the risks of mosquito-borne diseases.

Entomological surveillance is essential for the control of lymphatic filariasis (LF). This xenomonitoring study, conducted in 2022-2023, evaluated the effectiveness of three mosquito trapping methods to identify the most suitable tool for surveillance following the discontinuation of mass drug administration. The surveys took place in two Malian villages: Konfra (seasonal watercourse) and Siradjouba (permanent watercourse). Three techniques were compared: Pyrethrum spray catch (PSC) conducted at the end of each visit inside 30 randomly selected houses, and different collection points were chosen based on the characteristics of the study area to place the Ifakara Type C tent (Ifakara) and the gravid trap (GT). Collections were conducted simultaneously at both sites. All Anopheles gambiae and Culex spp. collected in 2022-2023 were morphologically identified and then analyzed in the laboratory for their infectious status. Data was processed using SPSS v25; Fishers exact test was used to compare proportions, with a significance threshold of p < 0.05. A total of 4,732 mosquitoes were captured (95.05% in 2022). In 2022, the Anopheles were predominant in Konfra (91.38%), while Culex predominated in Siradjouba (63.41%). In 2023, Anopheles was found only in Konfra (3 specimens), while Culex was predominant in Siradjouba (64.07%). In 2022, PSC collected 90.57% of Anopheles, Ifakara 9.43%, and GT 0%. For Culex, GT collected 53.67%, PSC 36.62%, and Ifakara 9.71%. In 2023, the few Anopheles (3) came from PSC; Culex were mainly collected by the Ifakara tent (43.29%). For FL xenomonitoring, the combination of PSC and the GT appear to be effective collection methods.

Objective: In Japan, antiretroviral therapy (ART) for individuals living with human immunodeficiency virus (HIV) is financially supported through the Physical Disability Certification System for Immunological Impairment. However, certification requires multiple laboratory assessments after diagnosis, possibly delaying ART initiation. This study examined the impact of these eligibility requirements on ART initiation using real-world clinical data. Design: Single-center retrospective cohort study. Setting: Nagoya Medical Center, Japan. Subjects, participants: A total of 568 patients who attended their first consultation between 2015 and 2019 were included. Of these, 434 were ART-naive, and 134 had already initiated ART at the first visit. Main outcome measures: ART initiation rate, time to treatment initiation, factors associated with treatment delay, and utilization of the Physical Disability Certificate system. Results: Among the 434 untreated patients, the median time to ART initiation was 42 days. Seven patients (1.6%) did not meet the Grade 4 certification requirements and remained untreated. Overall, 13 of the 568 patients (2.3%) were affected by the certification system, including those importing ART from overseas or using alternative financial support mechanisms. Non-Japanese nationality, lack of health insurance, unstable employment, and low CD4 cell counts were significantly associated with failure to initiate treatment. Among the 134 previously treated patients, 108 (80.5%) had obtained a Physical Disability Certificate. Conclusions: Although relatively few patients were affected, certification requirements may delay ART initiation among socioeconomically vulnerable populations. Further multi-center and cost-effectiveness studies are needed to improve compatibility between long-term financial support systems and rapid ART initiation strategies after diagnosis.

Locally acquired arboviral infections are an increasing public health concern in the United States. Aedes aegypti and Culex quinquefasciatus, vectors of dengue virus and West Nile virus, respectively, are established in regions where local transmission has been reported. Seasonal variation in mosquito abundance affects vector density, human-vector contact, and arbovirus transmission risk. The aim of this study is to investigate seasonal variations in Ae. aegypti and Cx. quinquefasciatus population dynamics in Miami-Dade County, Florida; Maricopa County, Arizona; and Clark County, Nevada. Monthly relative abundance, average mosquitoes collected per trap-night, normalized abundance ratios, and seasonal-trend decomposition were used to evaluate species- and location-specific seasonal patterns. Mosquito population dynamics differed by species and location. In Miami-Dade County, the two species showed seasonal turnover, with Cx. quinquefasciatus peaking during winter and spring and Ae. aegypti peaking during summer. In Maricopa and Clark counties, both species peaked primarily between August and September. Species dominance also differed by site, with Ae. aegypti more abundant than Cx. quinquefasciatus in Maricopa County and Cx. quinquefasciatus more abundant than Ae. aegypti in Clark and Miami-Dade counties. Seasonal decomposition showed that Ae. aegypti peaked earlier in Miami-Dade County than in Maricopa and Clark counties, whereas Cx. quinquefasciatus showed a spring peak in Miami-Dade County and bimodal seasonal patterns in Maricopa and Clark counties. These results suggest that mosquito population dynamics are species- and location-specific and support the use of local surveillance data to guide the timing of mosquito control and arbovirus preparedness.

Dengue fever risk and burden has increased globally in the past decade, with record-breaking outbreaks driving high case numbers, outbreaks increasing in existing transmission suitable regions, and occurring in new locations. A combination of global change processes, including climate change, have provided the environmental backdrop for introductions and resurgences of mosquito-transmitted dengue virus. Understanding shifts in exposure risk is integral to public health preparedness. This study provides global mapping of the thermal suitability of dengue transmission for CMIP6 climate scenarios, across a range of general circulation models (GCMs), and we created spatially explicit demographic projections of transmission risk using year-matched RCP-SSP frameworks for demographic and emissions scenarios. Globally, poleward shifts in projected distributions of suitability for transmission for both Ae. aegypti and Ae. albopictus suitability are shown in both the near term (2030s) and longer term (2050). Under a 'middle of the road' climate scenario (CMIP6 SSP2-4.5), regions in Africa and Asia are the major areas driving increases in year-round (12 months) population at risk (PAR) through 2050, with an anticipated net gain in 932 million people at risk for Ae. aegypti transmission and 24 million for Ae. albopictus, which includes multiple regions losing areas of year-round suitability as temperatures exceed the higher thermal boundary for transmission. In contrast, the estimated net increase in PAR for one or more months of transmission suitability at a global scale by 2050 is 3.29 billion people for Ae. aegypti transmission and 3.30 billion for Ae. albopictus transmission. This snapshot of a 'middle-of-the-road' combination of climate and demographic driven increases in potential dengue transmission exposure emphasizes the importance of both expanding suitability in new areas, and growing populations in areas approaching and becoming exposed year-round. Globalization, urbanization, and shipping will continue to provide the potential for introductions into newly suitable areas as season lengths increase, sparking outbreaks in unexposed populations. This is compounded and becomes ever more probable as the number of people and places at year-round risk also increases. This project provides all global gridded outputs for onward mapping and reuse, to add to the toolkit to anticipate and prepare for prevention and response to dengue in a changing world.

Dengue virus is a severe threat to global health. Novel vaccine and Wolbachia technologies offer a potential path to dengue control; however, it remains unclear how to use these approaches in tandem. Using metapopulation transmission models, we simulated future dengue burden in Brazil. We estimated that wMel releases in 300 municipalities could avert 12-22% of cases over the next 10 years, while a national vaccination campaign could avert 8-10% of cases in the total population and 39-45% within the vaccinated cohort. Projecting forward 40 years, we found wMel releases would drive up the mean age of cases beyond increases due to the ageing population and increase population susceptibility to dengue. Finally, wMel releases can help mitigate the future burden in southern Brazil where climate change is rapidly increasing dengue virus risk. These findings highlight the need to consider the two technologies in parallel to optimise efforts to combat future dengue burden.

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.

Bangladesh is facing a major resurgence of measles, with more than 60,000 suspected cases and over 600 deaths reported between March and May 2026. Despite the growing outbreak, hospital-based evidence in Bangladesh remains limited regarding measles vaccination status and its association with clinical complications. To address this critical gap, our study aimed to assess the vaccination status and its relationship with the development of clinical complications. A total of 260 children admitted to the measles ward were enrolled in this cross-sectional study. They were aged 2-72 months, had clinically confirmed measles, and were admitted to four dedicated measles treatment hospitals in Dhaka, Bangladesh, between 15 and 25 April 2026. Data on vaccination status, sociodemographic characteristics, feeding practices, Nutritional status, clinical symptoms, and complications were collected through caregiver interviews and hospital records. Adjusted odds ratios (AOR) with a corresponding 95% confidence interval (CI), and a p-value of <0.05 were considered statistically significant. Among enrolled children, 74.6% were unvaccinated, 18.8% were partially vaccinated, and only 6.5% were fully vaccinated. In the multivariable model, age below 9 months (aOR 0.077, 95% CI 0.025-0.236,p<0.001) was independently associated with lower odds of vaccination, while household income at or above the median (aOR 3.480, 95% CI 1.493-8.110,p=0.004) was associated with higher odds. Complications developed in 31.1% of cases, with respiratory involvement being most common. Absence of exclusive breastfeeding (aOR 2.336, 95% CI 1.027-5.313,p=0.043) and presenting with exactly three symptoms at admission (aOR 3.106, 95% CI 1.274-7.572,p=0.013) were independently associated with complications. Unvaccinated individuals exhibited markedly elevated odds of complications compared to those who were vaccinated (aOR 5.729,95% CI: 2.363-13.889, p<0.001). The overwhelming burden of measles in unvaccinated children, shaped by socioeconomic disadvantage and suboptimal feeding practices, underscores the urgent need to restore immunization coverage and strengthen equitable health services in Bangladesh.

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.

Background: Public health initiatives increasingly target multiple overlapping high-risk groups to maximize impact. However, a common challenge in modelling these initiatives is to capture these overlapping risk factors, leading to potential misallocation of resources and biased effectiveness estimates. Using China's tuberculosis (TB) control program as an example, this study explores different possible frameworks to account for population heterogeneity and risk overlap. Methods: We examined four risk allocation frameworks: (i) Direct Summation (DS), a simple additive benchmark; (ii) Probabilistic Union Deduplication (PUD), using inclusion-exclusion principles; (iii) Risk population combination (RPC), modeling interaction effects; and (iv) Agent-Based Framework (ABF), a granular microsimulation. To show how these frameworks could be used in epidemiological modelling, we embedded each within a deterministic transmission model of TB epidemiology in China, to simulate the impact of China's National Tuberculosis Strategic Plan (NTSP). We explored each framework when implemented in both static and dynamic versions. We compared them using methodological principles and indicators of intervention cost (screening volume) and benefits (cases/deaths averted). Results: Under the static version, the detection yield of active cases followed a consistent hierarchy: DS > PUD > RPC {approx} ABF. The DS method systematically overestimated yields by double-counting overlapping populations, while PUD corrected for overlap but ignored interaction. The RPC and ABF methods provided the most granular estimates by incorporating Risk population combinations. Additionally, comparing static versus dynamic versions revealed that for the same multi-risk screening framework, mortality reductions remained stable and incidence reductions varied significantly. Conclusion: This study presents potential screening frameworks for overlapping risk populations. The RPC method offers optimal balance of real-world plausibility and computational efficiency. We propose the dynamic RPC method as the preferred tool for routine analysis where multimorbidity and intersectional risks exist, providing a robust evidence base for optimizing resource allocation in heterogeneous populations.

The 7 1 7 framework (detection 7 days, notification & 1 day, response & 7 days) is a global target for epidemic preparedness, but its prospective value during an active cross border outbreak has not been quantified. Using a stochastic SEIR model parameterised for Uganda with the Bundibugyo Ebola strain and three daily importation probabilities (10%, 30%, and the observed 56%), we compared a rapid 3 1 5 response (detection 3 days, notification 1 day, response 5 days) against a delayed counterfactual (detection 11 days, notification 10 days, response 12 days). The rapid response reduced median cumulative cases by 60 to 66% (26 to 31 cases vs. 76 to 80 cases) and deaths by 62 to 63% (3 deaths vs. 8 deaths) across all import levels, with total costs of USD 29.1 to 29.9 million compared to USD 37.4 to 38.1 million for the delayed scenario. The rapid response was strictly dominant (cost saving and life saving). Variance based Sobol sensitivity analysis identified the case fatality rate, import probability, and basic reproduction number as the most influential parameters, with detection and response delays contributing through interactions. Institutionalising the 7 1 7 framework in Uganda is projected to be highly cost effective and should be supported with sustainable domestic financing, community based surveillance at unofficial border points, three consecutive PCR laboratory capacity, and multilingual risk communication.

Background In people living with Human Immunodeficiency Virus (PLWH), tuberculosis (TB) is the leading cause of death and is often associated with substantial morbidity. Better identifying PLWH with severe forms of TB could help target early interventions to reduce mortality and severe morbidity. Existing TB severity assessment tools may be sub-optimal for assessing disease severity in PLWH, since they incompletely integrate key determinants of disease severity. We aimed to develop a consensus-based TB severity score tailored to PLWH. Methods We developed a multifactorial TB severity score (TBSS) for PLWH using a modified Delphi process with a multidisciplinary group of international TB experts as the second part of a RAND/UCLA Appropriateness Method, following a previously published systematic review. Results Eight of 15 invited experts (53%) participated in both Delphi rounds. Of 62 candidate factors, 15 reflecting TB-related characteristics, host-related characteristics as well as characteristics related to both TB and host were rated as having high appropriateness for inclusion in the final TBSS. The total score ranges from 0 (no severity) to 61 (highest severity). Conclusion This study represents a first step towards the development of a multidimensional TB severity assessment tool for PLWH. However, its clinical usefulness, feasibility, and added value compared with existing severity scores remain to be demonstrated through validation studies before routine implementation can be considered. Key words: tuberculosis, HIV, severity.

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.