Search Results (128)

Cervical cancer remains the leading cause of cancer-related mortality among women in Nepal, where national screening coverage is approximately 16%. This study evaluated the feasibility of a community-based, door-to-door self-sampling strategy for high-risk human papillomavirus (hrHPV) detection in an urban municipality of central Nepal and assessed hrHPV prevalence, genotype distribution, screening outcomes, and associated demographic factors. A cross-sectional study was conducted between September 2023 and May 2024 in Ward No. 3 of Lalitpur Metropolitan City. Women aged 30–60 years were recruited through trained community health workers, provided education and home-based self-sampling kits, and completed a demographic questionnaire. Dry cervical swabs from 418 participants were tested for hrHPV. Women with positive results underwent visual inspection with acetic acid (VIA), followed by colposcopy, biopsy when indicated, and thermal ablation for confirmed precancerous lesions. Overall participation was 64.1%, and hrHPV prevalence was 10.3%. Non-16/18 hrHPV genotypes predominated (55.8%), followed by HPV16 (20.9%). Women aged > 50 years were more likely to be hrHPV- and VIA-positive (OR = 7.39, p = 0.02). Six pre-cancer cases were identified: five cervical intraepithelial neoplasia (CIN1) and one CIN3 case. Community-based hrHPV self-sampling was found to be feasible and achieved effective linkage to triage and treatment, supporting its consideration for strengthening cervical cancer screening in Nepal. Full article

Nepal is a small, landlocked country with marked elevational variation from the Terai plains to the Himalayas. Here, four indigenous goat populations (Chyangra, Sinhal, Khari, and Terai) are raised at different elevations. This study aimed to clarify the genetic structure of these populations and how they are formed and propagated across the Himalayan region. We analyzed 136 Nepalese goats using mitochondrial (mt) DNA D-loop and sex-determining region Y (SRY) 3′-untranslated region (UTR) sequences, as well as 50 K SNP array data. The mtDNA haplogroups D (0.162) and G (0.03) were detected only in Chyangra, whereas haplogroup B was predominant in Sinhal (0.42), followed by Khari (0.260). Regarding SRY haplotypes, Y2B was detected in all populations, whereas Y1AB (0.42) was found only in Chyangra. Genome-wide SNP analysis showed that Chyangra was genetically related to Tibetan and Central Asian goats, while Terai resembled South Asian goats. Interestingly, Sinhal formed a distinct cluster, whereas Khari exhibited an admixed genetic structure. These findings suggest that Nepalese goats originate from at least three ancestral lineages and that an additional migration route may have existed through the southern Himalayas. Full article

Drawing on 13 women’s struggles in Bangladesh, India, Nepal and Pakistan, this paper conceptualises care as social love underpinning the everyday work of organising and movement-building. The paper explores who provides social love, for whom, and under what conditions, revealing infrastructures that sustain collective action. Moving beyond care as a unidirectional or dyadic relationship between giver and receiver, the paper shows how care as social love reveals fluid, nested dynamics, with actors continuously shifting roles and often occupying both positions. Engaging with Tronto’s phases of care, the paper highlights that these phases rarely unfold sequentially; instead, they overlap, collapse into one another, or reappear in response to changing needs. The paper also demonstrates how care is spatially dispersed within movements, across digital platforms, informal gatherings and interpersonal relationships. These three dimensions (fluidity of care roles; non-linearity of care; spatially dispersed care) constitute the ‘webs of care’, which function as ongoing, overlapping networks that build and sustain movements in times of backlash, fragmentation, or fatigue. In so doing, the paper argues that care as social love brings out messy, fluid and collectively situated processes. It contributes to feminist social movement theory by positioning social love as central to organising and sustainability and to care ethics by expanding the temporal, spatial and relational dimensions through which it is practised. Full article

This paper examines the vulnerability and adaptive capacity of mountain communities in South and Central Asia, with specific reference to the Himalayas and the Central Asian highlands. Using a comparative framework, the study combines the Livelihood Vulnerability Index (LVI), LVI-IPCC, and the Livelihood Equity/Endowment Index (LEI) to measure multidimensional vulnerability. A mixed-methods approach combining household surveys and qualitative field evidence is used to analyze primary data from 600 households across four mountain regions: Leh (India), Sindhupalchok (Nepal), Batken (Kyrgyzstan), and Urgut (Uzbekistan). The results show that vulnerability is not explained only by climatic exposure; it is also associated with socio-economic conditions, institutional access, and livelihood assets. Leh and Sindhupalchok show higher vulnerability associated with water insecurity, food dependence, weak infrastructure, and climate variability, whereas Batken’s vulnerability is mainly linked to limited adaptive capacity. Urgut shows greater resilience associated with stronger adaptive capacity, despite persistent structural inequalities. The paper identifies financial access, social networks, and knowledge systems as important factors in strengthening resilience. It concludes that context-specific, inclusive, and asset-based policy interventions may help strengthen adaptive capacity and reduce vulnerability in fragile mountain ecosystems. Full article

Under the intensifying impacts of global climate change, high-altitude linear cultural landscapes are increasingly threatened by natural hazards such as extreme precipitation and glacier-fed runoff. Taking the cultural landscape of the Tibet–Nepal Route as the study object, it employs an integrated methodology combining spatial analysis, adaptive assessment, field investigation, and case studies to systematically identify levels of hazard exposure and explore pathways for adaptive governance. This study makes two key contributions. It develops an interdisciplinary framework that combines spatial exposure analysis, barrier diagnosis, and multi-criteria evaluation. It also proposes a governance shift from external interventions to internally driven approaches, underscoring the central role of traditional community institutions system in building landscape resilience. The findings provide a scientific basis for the coordinated governance of cross-border high-altitude linear cultural landscapes between China and Nepal, and offer transferable insights for advancing the World Heritage nomination research of the Silk Road: the routes network of the Qinghai–Tibet Plateau to South Asia Corridor. Full article

Mountain treelines are among the most climate-sensitive ecosystems on Earth, yet their fine-scale structural and species level dynamics remain poorly resolved in the Himalayas. In particular, the absence of three-dimensional, crown level measurements have hindered the detection of structural thresholds and species turnover that often precede treeline shifts. To bridge this gap, we introduce UAV LiDAR—applied for the first time in the Hindu Kush Himalayas—to quantify canopy structure and tree species distributions across a steep treeline ecotone in the Manang Valley of central Nepal. High-density UAV-LiDAR data acquired over elevations of 3504–4119 m was used to quantify elevation-dependent changes in canopy stature and cover from a canopy height model derived from the 3D point cloud, while individual tree segmentation and species classification were performed directly on the 3D, height-normalized point cloud at the crown level. Individual trees were delineated using a watershed-based segmentation algorithm while tree species were classified using a random forest model trained on LiDAR-derived structural and intensity metrics, supported by field-validated reference data. Results reveal a sharply defined treeline characterized by an abrupt collapse in canopy height and cover within a narrow ~60–80 m vertical interval. Treeline “threshold” was quantified as a breakpoint elevation from a piecewise model of tree cover versus elevation, and the elevation span over which modeled cover and height distributions rapidly declined from forest values to near-zero. Segmented regression identified a distinct structural breakpoint near 3995 m elevation. Crown-level species predictions aggregated by elevation quantified an ordered turnover in dominance, with Pinus wallichiana most frequent at lower elevations, Abies spectabilis peaking mid-slope, and Betula utilis concentrated near the upper treeline. Species classification achieved high overall accuracy (>85%), although performance varied among taxa, with broadleaf Betula more difficult to discriminate than conifers. These findings underscore UAV LiDAR’s value for resolving sharp ecological thresholds, identifying elevation-driven simplification in forest structure, and bridging observation gaps in remote, rugged mountain ecosystems. Full article

Nepal is highly vulnerable to severe soil erosion driven by monsoonal rainfall and rugged terrains. Limitations in ground observation networks have hindered comprehensive, high-resolution national assessment of precipitation and rainfall-runoff erosivity (R-factor) across Nepal. This study systematically evaluated eight global gridded precipitation datasets (GPDs) against data from 152 weather stations, identifying the optimal precipitation dataset (TPHiPr) representing Nepal’s complex topography. Based on this high-quality dataset, we provided the first independent, long-term (1979–2020), high-resolution national-scale assessment of precipitation and the R-factor for Nepal. Our analysis reveals that 1996 marked a turning point in nationwide precipitation trends: annual precipitation shifted from a decreasing to an increasing one in the humid eastern and central regions, while the drier western region transitioned from an increasing to a decreasing trend, particularly during the dry season. A clear spatial divergence was observed between total precipitation and the R-factor, highlighting the dominant role of precipitation frequency and intensity. Extreme precipitation events intensified significantly (e.g., days with ≥25 mm rainfall increased by 0.2 days yr⁻¹, and the 95th percentile precipitation threshold increased by 0.4 mm yr⁻¹, p < 0.01), driving a nationwide increase in the R-factor (6.3 MJ mm ha⁻¹ h⁻¹ yr⁻², p < 0.01), with high-altitude areas experiencing the most pronounced effects. We conclude that soil erosion risk has intensified nationwide due to increasing precipitation extremes. Watershed management must develop elevation-specific adaptation strategies that integrate climate science with practical solutions to address the dual challenges of intensified monsoon-driven erosion and growing dry-season water scarcity. Full article

Farmland abandonment is increasingly prevalent, especially in the Central Himalaya. Precise mapping of abandoned areas is crucial for understanding their status and socioecological impacts. However, distinguishing abandoned farmland from transitional classes like fallow land and barren land is challenging without high-resolution satellite imagery and field verification. In this context, this work analyzes farmland abandonment in three ecological villages of the Nepal Himalaya using high-resolution satellite imagery and a people-to-pixel approach. First, the study villages were divided into grids based on their areas, and satellite imagery was printed for ground truthing. Second, ground truthing was conducted to identify active and abandoned farmland areas using the Field Area Measure App and satellite imagery. We measured the extent of abandoned farmland and assessed its current conditions. Third, the measured abandoned farmland shapefiles were exported for precise on-screen mapping using the Geographic Information System, alongside detailed land-cover mapping. Next, the accuracy assessment was performed using Google Earth satellite imagery, and the overall mapping accuracy was found to be 95.8%. Mapping results show that the highest areas of abandoned farmland were found in the Mountain region with 19.2% of total farmland, followed by the Hill region (12.7%) and the Tarai region (2.6%). Out of the total abandoned farmland, 49.2% is currently covered with bushes and shrubs, 42.9% with weeds and grasses, and the remaining 7.9% with woodlands. The findings emphasize the importance of integrating satellite technology with people engagement to address complex land-use challenges and offer critical insights for sustainable land management in the Nepal Himalaya and similar regions worldwide. Full article

Samples collected from two avian influenza outbreaks in Bagmati Province in central Nepal between January and March 2023 were positive for H5N1. Full genomes were generated for both viruses, which revealed that one of the viruses was very similar to clade 2.3.4.4b H5N1 identified in Bangladesh in 2021/2022. The second virus was a reassortant H5N1 virus consisting of four genes (HA, NA, NP, and M) originating from a clade 2.3.2.1a H5N1 and the remaining four genes (NS, PB1, PB2, and PA) originating from a 2.3.4.4b H5N1. Notably, this second virus had a high identity with 2.3.2.1a clade viruses identified in humans and cats in India in 2024–2025. These are the first full genome sequences of H5N1 avian influenza viruses from Nepal and given the recent human infections by 2.3.2.1a H5N1 viruses in the region, these data will be of interest to both public health and veterinary authorities. Full article

South Asia’s worsening air pollution crisis represents one of the most urgent public health and environmental challenges of the 21st century. Nearly two billion people—over one-quarter of the global population—reside in this region, where air quality levels routinely exceed World Health Organization (WHO) guidelines by factors of 10 to 15. This has translated into an unprecedented health burden, with approximately two million premature deaths annually, widespread chronic respiratory and cardiovascular disease, and rising economic losses. According to recent World Bank estimates, welfare losses amount to over 5% of regional GDP, a figure far exceeding the projected costs of coordinated mitigation. Despite this, South Asia continues to lack a binding regional framework capable of addressing its shared airshed. Existing cooperative efforts—such as the Malé Declaration on Control and Prevention of Air Pollution (1998)—have provided a useful platform for dialog and pilot monitoring, but they remain voluntary, under-resourced, and insufficient to manage the transboundary nature of the crisis. National-level programs, including India’s National Clean Air Programme (NCAP), Bangladesh’s National Air Quality Management Plan (NAQMP), and Nepal’s National Air Quality Management Action Plan (AQMAP), demonstrate domestic commitment but are constrained by fragmentation, limited financing, and lack of regional integration. This gap represents the central knowledge and governance challenge that prompted the present commentary. To address it, we propose a dual-track architecture designed to institutionalize binding regional cooperation. Track A would establish a United Nations-anchored South Asian Transboundary Air Pollution Protocol, under the auspices of the United Nations Environment Programme, the World Health Organization (WHO), and the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP). This protocol would codify legally enforceable emission standards, compliance committees, financial mechanisms, and harmonized monitoring. Track B would establish a South Asian Association for Regional Cooperation (SAARC) Prime Ministers’ Council on Air Quality (SPMCAQ) to provide political leadership, align domestic implementation, and authorize rapid responses to cross-border haze events. Lessons from the Indian Ocean Experiment, the ASEAN Agreement on Transboundary Haze Pollution, and Europe’s Convention on Long-Range Transboundary Air Pollution demonstrate that legally binding agreements combined with high-level political ownership can achieve durable reductions in pollution despite geopolitical tensions. By situating South Asia within these global precedents, the proposed framework provides a pragmatic, enforceable, and politically resilient pathway to protect health, reduce economic losses, and deliver cleaner air for nearly one-quarter of humanity. Full article

In this study, a statistical analysis of ground geomagnetic data has been attempted to extract the seismo-electromagnetic (SEM) signatures associated with moderate earthquakes in the region of the seismic gap in the Kumaun Himalaya, Uttarakhand, India. We applied the discrete wavelet transform (DWT) method to the geomagnetic data to identify the ULF energy of the signal. The ULF energy obtained in the central frequency range of 0.01 Hz was further filtered to extract the anomalous ULF energy, which is associated with pre-earthquake processes. We also applied multifractal analysis to the geomagnetic data to classify the complexities in the signal, which are indicative of the seismotectonic environment. We observed enhancements in the ULF energy anomalies associated with large-magnitude earthquakes occurring in the western part of Nepal, even over large epicentral distances (~120 km). The multifractal analysis shows the overlap of anomalies in the Hwp and Hwn signatures in most cases, which suggests that multiple mechanisms generate low- and high-frequency components in the anomalous data. This reflects the complex nature of seismicity in this region of the Main Central Thrust (MCT). Full article

The production and transport of dissolved inorganic carbon (DIC) is central to weathering reactions and the global carbon cycle. We investigated the spatiotemporal variability and export of inorganic carbon species along the rapidly weathering Langtang–Narayani river system in the central Nepal Himalaya. Over the course of one year, surface water samples were collected from sixteen stations spanning a wide range of elevations. DIC concentrations generally declined with increasing elevation, except in mid-mountain sites influenced by hot springs. Bicarbonate (HCO₃⁻) was identified as the dominant inorganic carbon species, contributing approximately 85% to the total DIC and with a similar dominant export rate of bicarbonate to total DIC export rate, followed by carbon dioxide (CO₂) and carbonate (CO₃²⁻). The river water exhibited a strong altitudinal gradient in carbonate chemistry, with CO₂ supersaturation in the lowlands and undersaturation at higher elevations. Metamorphic activities in the lower mid-mountain sites significantly influenced CO₂ concentrations and inorganic carbon dynamics. The partial pressure of CO₂ (pCO₂) varied widely (56 to 33,869 μatm), reflecting distinct geochemical and seasonal controls. The estimated DIC export rates were 93.66, 37.81, and 12.59 tons km⁻² yr⁻¹ from the Narayani River in the lowlands, the Trisuli River in the mid-mountains, and the Langtang River in the high Himalaya region, respectively. These findings highlight the critical role of elevation, seasonality, and geological processes in regulating carbon dynamics in Himalayan river systems, providing new insights into their contribution to regional carbon fluxes. A comprehensive array of significant univariate and multivariate predictive models is presented here, offering versatile applications, including the interpretation of full and partial derivatives explaining inorganic carbon dynamics within the Himalayan basin. Full article

The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article

Gynecological cancers pose a significant threat to women’s health. This study aimed to investigate the disease burden of cervical, uterine, and ovarian cancers in Asia from 1980 to 2021. The Global Burden of Disease 2021 database (GBD 2021) was used to conduct a cross-sectional study. The incidence, mortality rates, and disability-adjusted life years (DALYs) were obtained as indicators to estimate the burden. The effects of age, period, and cohort on the incidence of gynecological cancers were analyzed via the age-period-cohort web tool (APC-Web). The future trends of the gynecological cancer burden in Asia from 2025 to 2050 were predicted via a Bayesian age-period-cohort model. In 2021, cervical cancer exhibited the highest age-standardized mortality burden (3.1 deaths per 100,000; 95% UI: 2.7–3.4), whereas uterine cancer had the lowest (0.7 deaths per 100,000; 95% UI: 0.6–0.9). Geographically, South Asia has experienced the highest cervical cancer burden, with Seychelles, Mongolia, Cambodia, and Nepal ranking among the most affected nations. In contrast, Central Asia had the highest ovarian cancer burden, led by Georgia, followed by the United Arab Emirates, Seychelles, and Brunei Darussalam. Similarly, the uterine cancer burden was most pronounced in Central Asia, with Georgia, Armenia, Mauritius, and the United Arab Emirates exhibiting elevated rates. Finally, increasing trends in the burden of gynecological cancers were predicted across all age groups from 2025 to 2050, with women aged 60 to 64 years being the most affected. In conclusion, gynecological cancers are significant contributors to the disease burden in Asia. Improved early screening methods are essential to mitigate this increasing burden. Full article

Nepal is known for its complex terrain, climate, and vegetation dynamics, resulting in tremendous hydrologic variability and complexity. Accurately quantifying the water balances at the national level in Nepal is extremely challenging and is currently not available. This study constructed long-term (2000–2022) water balances for 358 watersheds across Nepal by integrating watershed hydrometeorological monitoring data, remote sensing products including Leaf Area Index and land use and land cover data, with an existing ecohydrological model, Water Supply Stress Index (WaSSI). The WaSSI model’s performance is assessed at both watershed and national levels using observed water yield (Q) and evapotranspiration (ET) products derived from remote sensing (ETMonitor, PEW, SSEBop) and eddy flux network (i.e., FLUXCOM). We show that the WaSSI model captured the seasonal dynamics of ET and Q, providing new insights about climatic controls on ET and Q across Nepal. At the national scale, the simulated long-term (2000–2020) mean annual Q and ET was about half of the precipitation (1567 mm), but both Q and ET varied tremendously in space and time as influenced by a monsoon climate and mountainous terrain. We found that watersheds in the central Gandaki River basin had the highest Q (up to 1600 mm yr⁻¹) and ET (up to 1000 mm yr⁻¹). This study offers a validated ecohydrological modeling tool for the Himalaya region and a national benchmark dataset of the water balances for Nepal. These products are useful for quantitative assessment of ecosystem services and science-based watershed management at the national scale. Future studies are needed to improve the WaSSI model and remote sensing ET products by conducting ecohydrological research on key hydrologic processes (i.e., forest ET, streamflow generations of small watersheds) across physiographic gradients to better answer emerging questions about the impacts of environmental change in Nepal. Full article