Vulnerable Regions Research Articles

Creating Sustainable Flood Maps Using Machine Learning and Free Remote Sensing Data in Unmapped Areas

This study leverages a Random Forest model to predict flood hazard in Arizona, New Mexico, Colorado, and Utah, focusing on enhancing sustainability in flood management. Utilizing the National Flood Hazard Layer (NFHL), an intricate flood map of Arizona was generated, with the Random Forest Classification algorithm assessing flood hazard for each grid cell. Weather variable predictions from TerraClimate were integrated with NFHL classifications and Digital Elevation Model (DEM) analyses, providing a comprehensive understanding of flood dynamics. The research highlights the model’s capability to predict flood hazard in areas lacking NFHL classifications, thereby supporting sustainable flood management by elucidating weather’s influence on flood hazard. This approach aligns with sustainable development goals by aiding in resilient infrastructure design and informed urban planning, reducing the impact of floods on communities. Despite recognizing constraints such as input data precision and the model’s potential limitations in capturing complex variable interactions, the methodology offers a robust framework for flood hazard evaluation in other regions. Integrating diverse data sources, this study presents a valuable tool for decision-makers, supporting sustainable practices, and enhancing the resilience of vulnerable regions against flood hazards. This integrated approach underscores the potential of advanced modeling techniques in promoting sustainability in environmental hazard management.

Frontiers in attributing climate extremes and associated impacts

The field of extreme event attribution (EEA) has rapidly developed over the last two decades. Various methods have been developed and implemented, physical modelling capabilities have generally improved, the field of impact attribution has emerged, and assessments serve as a popular communication tool for conveying how climate change is influencing weather and climate events in the lived experience. However, a number of non-trivial challenges still remain that must be addressed by the community to secure further advancement of the field whilst ensuring scientific rigour and the appropriate use of attribution findings by stakeholders and associated applications. As part of a concept series commissioned by the World Climate Research Programme, this article discusses contemporary developments and challenges over six key domains relevant to EEA, and provides recommendations of where focus in the EEA field should be concentrated over the coming decade. These six domains are: (1) observations in the context of EEA; (2) extreme event definitions; (3) statistical methods; (4) physical modelling methods; (5) impact attribution; and (6) communication. Broadly, recommendations call for increased EEA assessments and capacity building, particularly for more vulnerable regions; contemporary guidelines for assessing the suitability of physical climate models; establishing best-practice methodologies for EEA on compound and record-shattering extremes; co-ordinated interdisciplinary engagement to develop scaffolding for impact attribution assessments and their suitability for use in broader applications; and increased and ongoing investment in EEA communication. To address these recommendations requires significant developments in multiple fields that either underpin (e.g., observations and monitoring; climate modelling) or are closely related to (e.g., compound and record-shattering events; climate impacts) EEA, as well as working consistently with experts outside of attribution and climate science more generally. However, if approached with investment, dedication, and coordination, tackling these challenges over the next decade will ensure robust EEA analysis, with tangible benefits to the broader global community.

ESTUDO EPIDEMIOLÓGICO DE CASOS NOTIFICADOS POR CHIKUNGUNYA ENTRE OS ANOS DE 2019 A 2023 EM UM MUNICÍPIO DO TOCANTINS

INTRODUCTION: The Chikungunya virus is transmitted by Aedes aegypti and Aedes albopictus, causing fever and joint pain, with potential serious complications. This study aimed to analyze the incidence and epidemiological profile of Chikungunya cases in Porto Nacional, Tocantins, between 2019 and 2023. METHODOLOGY: A quantitative approach was used, based on retrospective data found in the Notifiable Diseases Information System (SINAN). The variables tested included sex, age group, education and disease progression. The incidence calculation was carried out based on population estimates provided by IBGE. RESULTS: The results indicated a significant increase in cases in 2022, representing 58% of the total, followed by a drop in 2023. The majority of cases affected women (65%) and people between 20 and 39 years old. Laboratory classification was the main diagnostic method, responsible for 60% of confirmed cases. DISCUSSION: The discussion of the results highlights the need for more effective public policies to control the spread of the virus, especially in vulnerable regions. FINAL CONSIDERATIONS: Therefore, although there was a reduction in cases in 2023, it is crucial to maintain continuous epidemiological surveillance and vector control actions to prevent future outbreaks and mitigate the impacts of Chikungunya on the population.

Willingness to Pay for Nature Protection: Crowdfunding as a Payment Mechanism

AbstractIn this study, we use a discrete choice experiment to elicit the willingness-to-pay (WTP) for preventing and mitigating the effects of oil spills on marine and coastal ecosystem services, along a particularly vulnerable coastal region of mainland Portugal. We used a split-sample design to analyze the differences between two payment vehicles (PV): a mandatory extra income tax and a voluntary contribution collected by a crowdfunding campaign with a provision point mechanism and a money-back guarantee. The difference between the two PVs is examined in a setting where the local population has a negative perception of the quality of institutions. We find that respondents are more willing to contribute when presented with the crowdfunding version. Also, regardless of the payment vehicle, respondents who express a mistrust in institutions are more likely to choose the status quo. These results suggest the potential of using crowdfunding to support ecosystem services’ conservation initiatives.

RUSSIA’S HYBRID WARFARE IN THE WESTERN BALKANS: GEOPOLITICAL STRATEGIES AND PROXY ACTORS

This paper examines Russia’s hybrid warfare tactics against the Western Balkans, focusing on using direct and indirect methods to exert influence in the region. The study delves into Russia’s strategic use of media manipulation, cyberattacks, and disinformation campaigns, alongside its employment of proxy state and non-state actors such as Serbia, Republika Srpska, and the Serbian Orthodox Church. Leveraging historical, cultural, and religious ties, Russia seeks to destabilize the Western Balkans and prevent closer integration with NATO and the European Union. Special attention is given to the geopolitics of elections, where Russia manipulates electoral processes in countries like Montenegro and North Macedonia to favour pro-Russian or anti-Western political forces. By analyzing key case studies, this paper explores how Russian hybrid warfare exploits regional vulnerabilities—such as ethnic divisions and weak political institutions—while employing tactics of soft power and military cooperation. The findings indicate that Russia’s hybrid warfare, including electoral manipulation, poses a significant threat to regional stability and international security, underscoring the need for strengthened Western engagement to counter Russian influence. This study offers critical insights into the evolving nature of hybrid warfare and its implications for the geopolitical landscape of Southeast Europe.

Storm clouds over innovation: Typhoon shocks and corporate R&D activities

This study investigates the economic impact of typhoon disasters on corporate innovation activities, a critical driver of economic growth and resilience. Utilizing a comprehensive dataset of Chinese public companies from 2010 to 2022 and employing a wind field model to construct a city-level typhoon destruction index, we apply difference-in-differences and instrumental variable methods to analyze the effects on corporate innovation. Our findings reveal that typhoon disasters significantly reduce both patent filings and R&D investment intensity, particularly in coastal areas and technology-intensive industries. The adverse effects are transmitted through financial constraints, human capital loss, and infrastructure damage. This research contributes to understanding the microeconomic implications of extreme weather events on innovation-driven economic growth, offering insights for disaster resilience policies in vulnerable regions.

DINÁMICA Y VULNERABILIDAD ECOLÓGICA DE LA RESERVA ESTATAL SIERRA DEL TENTZO, MÉXICO

<p><strong>Background:</strong> Knowledge and evaluation of ecological changes in Protected Natural Areas is important for their planning and management. The use of tools such as land use change prediction models and satellite image analysis are low-cost and high-precision alternatives that can contribute to this purpose. <strong>Objective:</strong> Estimate the trend of land use change and vulnerability of the ecosystems of the Sierra del Tentzo State Reserve (REST), Mexico. <strong>Methodology:</strong> The REST sites with the highest probability of change in their ecosystems were identified according to phases of the adaptive cycles of the Panarchy theory; the use of Landsat images to classify land use and vegetation types, and the identification of areas of greatest vulnerability with a Markov chain model. <strong>Results:</strong> The trend of change from a state of conservation to a state of growth predominates in the reserve, which indicates a deterioration of the ecosystems with primary vegetation that are being transformed into grasslands and crop areas. While, in the future projection, the areas with greater ecological vulnerability are grouped in a pattern associated with human settlements in population centers. <strong>Implications:</strong> The study was on a regional scale, so changes and vulnerability at the local level were not explored. <strong>Conclusion:</strong> In the Sierra del Tentzo State Reserve there is a process of ecosystem degradation and some areas, particularly those most susceptible to human activities, are more vulnerable to this degradation. These areas should be considered in the reserve management program as priority attention.</p>

Making waves: Harnessing stormwater for resilient water supply - A blueprint for vulnerable continental coasts and oceanic islands

At the forefront of climate change and natural disasters, small islands like Puerto Rico confront immense challenges in sustaining an adaptive water supply. The challenges are further exacerbated when the islands’ constraints, such as geographic isolation, limited resources, aging infrastructure, constrained capacity, and environmental fragility, are compounded. As these issues increasingly impact low-lying continental coasts, home to approximately 40 % of the global population, similar water supply crises have already emerged or are anticipated in these regions. To surmount these widespread challenges, harnessing stormwater as a non-conventional water source presents a promising solution. A stormwater-enabled water supply system, collectively characterized by water source diversification, decentralization, and modularity, can enhance the resilience of water supply in these vulnerable regions, both in routine situations and during emergencies. This article identifies barriers to the implementation of stormwater-to-drinking water (STDW) practices in Puerto Rico and advocates for engineering solutions to utilize stormwater at both community and household scales in vulnerable continental coasts and small oceanic islands. The primary barriers in Puerto Rico include uncertainty in water quality, insufficient data on local stormwater availability and domestic water demand, economic constraints, and the lack of an adaptive power supply. To overcome these obstacles, we emphasize engineering strategies focused on modular system design, assessments of local stormwater capture and demand dynamics, advancements in treatment technologies, and the enhancement of energy resilience. By analyzing the Puerto Rican context, we propose a conceptual framework that outlines pathways to adaptive STDW strategies for other oceanic islands and larger, more complex continental coasts in the face of similar challenges. These pathways encompass enhancing system modularity, understanding the dynamics of local stormwater supply and water consumption, applying tailored treatment technologies, and strengthening the resilience of supporting infrastructures. The insights gained from Puerto Rico's experience can guide current and future efforts for resilient water supply solutions in increasingly vulnerable coastal, island, and other regions.

Mapping coastal resilience: a Gis-based Bayesian network approach to coastal hazard identification for Queensland’s dynamic shorelines

Coastal regions worldwide face increasing threats from climate change-induced hazards, necessitating more accurate and comprehensive vulnerability assessment tools. This study introduces an innovative approach to coastal vulnerability assessment by integrating Bayesian Networks (BN) with the modern coastal vulnerability (CV) framework. The resulting BN-CV model was applied to Queensland's coastal regions, with a particular focus on tide-modified and tide-dominated beaches, which constitute over 85% of the studied area. The research methodology involved beach classification based on morphodynamic characteristics, spatial subdivision of Queensland's coast into 78 sections, and the application of the BN-CV model to analyze interactions between geomorphological features and oceanic dynamics. This approach achieved over 90% accuracy in correlating beach types with vulnerability factors, significantly outperforming traditional CVI applications. Key findings include the identification of vulnerability hotspots and the creation of detailed exposure and sensitivity maps for Gold Coast City, Redland City, Brisbane City, and the Sunshine Coast Regional area. The study revealed spatial variability in coastal vulnerability, providing crucial insights for targeted management strategies. The BN-CV model demonstrates superior precision and customization capabilities, offering a more nuanced understanding of coastal vulnerability in regions with diverse beach typologies. This research advocates for the adoption of the BN-CV approach to inform tailored coastal planning and management strategies, emphasizing the need for regular reassessments and sustained stakeholder engagement to build resilience against climate change impacts.Recommendations include prioritizing adaptive infrastructure in high-exposure areas like the Gold Coast, enhancing flood management in Brisbane, improving socio-economic adaptive capacity in Redland, and maintaining natural defences in Moreton Bay. This study contributes significantly to the field of coastal risk management, providing a robust tool for policymakers and coastal managers to develop more effective strategies for building coastal resilience in the face of climate change.

Effects of pay for performance in primary care in an under-registration scenario.

To propose a method for detecting and analyzing under-registration and highlight its potential financial effect in view of the implementation of the Previne Brasil Program. An ecological study was carried out to analyze cytopathological exams in programmatic area 3.1 in the municipality of Rio de Janeiro. The data was collected from the Departamento de Informática do Sistema Único de Saúde (DATASUS - Department of Informatics of the Unified Health System) database, including information on reports from outsourced cytopathology laboratories and those available in the Sistema de Informação em Saúde para a Atenção Básica (SISAB - Health Information System for Primary Care) and the Sistema de Informação do Câncer do Colo do Útero (SISCOLO - Cervical Cancer Information System) of DATASUS/Ministry of Health. The estimated under-registrations per health unit totaled 108,511 exams in the last two years in the programmatic area 3.1 area, which corresponds to an estimated total of R$ 435,129.00 that would have been foregone if the Previne Brasil Program had been in place during the period studied. The article's main contribution lies in the presentation of empirical evidence of the potential effects of under-registration on Primary Health Care financing. In addition, there are two other significant findings - firstly, it highlights weaknesses in the process of recording health information inherent to vulnerable regions; secondly, it indicates a vicious circle potentially fueled by sudden changes in Primary Health Care funding conditions, in addition to potential consequences for other levels of care.

Simulation of Epidemic Dynamics Using a Multi-Agent Model: Analysis of Social Distancing Strategies and Their Impacts on Public Health and Economy

Infectious disease epidemics have played a crucial role in shaping public health responses, particularly in global health crises. This study emerges as part of the efforts to prepare effective responses to potential future pandemics, leveraging lessons learned during the COVID-19 crisis. The research uses an adapted compartmental epidemiological model and a synthetic multi-agent community to investigate how social variables influence epidemic forecasts in socioeconomically vulnerable regions. Focusing on the simulation of epidemic dynamics in the socio-economically disadvantaged neighbourhood of Ilha Joana Bezerra in Recife, this study examines the impacts of social distancing strategies and other control measures, such as face masks and moderate social isolation. Through the adapted SEPAI3R3O model, which includes compartments for pre-symptomatic and asymptomatic states, this study provides a detailed analysis of disease dynamics in contexts characterised by high social vulnerability. The results underscore the importance of public health policies adapted to socio-economic factors, emphasising the need for continuous preparedness to manage future epidemic threats in vulnerable communities effectively.

Impacts of elevated anthropogenic emissions on physicochemical characteristics of black-carbon-containing particles over the Tibetan Plateau

Abstract. Black carbon (BC) in the Tibetan Plateau (TP) region has distinct climate effects that strongly depend on its mixing state. The aging processes of BC in the TP are subject to emissions from various regions, resulting in considerable variability of its mixing state and physicochemical properties. However, the mechanism and magnitude of this effect are not yet clear. In this study, field observations on physicochemical properties of BC-containing particles (PMBC) were conducted in the northeast (Xihai) and southeast (Lulang) regions of the TP to investigate the impacts of transported emissions from lower-altitude areas on BC characteristics in the TP. Large spatial discrepancies were found in the chemical composition of PMBC. Both sites showed higher concentrations of PMBC when they were affected by transported air masses outside the TP but with diverse chemical composition. Source apportionment for organic aerosol (OA) suggested that primary OA in the northeastern TP was attributed to hydrocarbon OA (HOA) from anthropogenic emissions, while it was dominated by biomass burning OA (BBOA) in the southeastern TP. Regarding secondary aerosol, a marked enhancement in nitrate fraction was observed on aged BC coating in Xihai when the air masses were brought by updrafts and easterly winds from lower-altitude areas. With the development of boundary layer, the enhanced turbulent mixing promoted the elevation of anthropogenic pollutants. In contrast to Xihai, the thickly coated BC in Lulang was mainly caused by elevation and transportation of biomass burning plumes from south Asia, showing a large contribution of secondary organic aerosol (SOA). The distinct transported emissions lead to substantial variations of both chemical composition and light absorption ability of BC across the TP. The thicker coating and higher mass absorption cross-section (MAC) of PMBC in air masses elevated from lower-altitude regions reveal the promoted BC aging processes and their impacts on the mixing state and light absorption of BC in the TP. These findings emphasize the vulnerability of plateau regions to influences of elevated emissions, leading to significant changes in BC concentration, mixing states and light absorption across the TP, all of which need to be considered in the evaluation of BC radiative effects for the TP region.

Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains.

The paramagnetic iron, diamagnetic amyloid beta (Aβ) plaques and their interaction are crucial in Alzheimer's disease (AD) pathogenesis, complicating non-invasive magnetic resonance imaging for prodromal AD detection. We used a state-of-the-art sub-voxel quantitative susceptibility mapping method to simultaneously measure Aβ and iron levels in post mortem human brains, validated by histology. Further transcriptomic analysis using Allen Human Brain Atlas elucidated the underlying biological processes. Regional increased paramagnetic and diamagnetic susceptibility were observed in medial prefrontal, medial parietal, and para-hippocampal cortices associated with iron deposition (R=0.836, p=0.003) and Aβ accumulation (R=0.853, p=0.002) in AD brains. Higher levels of gene expression relating to cell cycle, post-translational protein modifications, and cellular response to stress were observed. These findings provide quantitative insights into the variable vulnerability of cortical regions to higher levels of Aβ aggregation, iron overload, and subsequent neurodegeneration, indicating changes preceding clinical symptoms. The vulnerability of distinct brain regions to amyloid beta (Aβ) and iron accumulation varies. Histological validation was performed on stained sections of ex-vivo human brains. Regional variations in susceptibility were linked to gene expression profiles. Iron and Aβ levels in ex-vivo brains were simultaneously quantified.

Organisms with high dispersal ability as a proxy for biogeographical characterisation of the Mediterranean biome

The Mediterranean biome offers a diverse range of habitats, particularly rocky environments, known for their long-term stability and persistence. Adapted to these rocky surfaces, chasmophytes thrive in this region, benefiting from reduced competition and human interference. The distribution of stress-tolerant cryptogams with generally broad niches represents a significant gap in the biogeography of the region. This study investigates whether complex symbiotic organisms with a potential for long-distance dispersal could serve as biogeographic indicators for delimitation of the Mediterranean biome's boundaries. Through comprehensive chorology data research, saxicolous lichen congeners of the genus Solenopsora were mapped across the Mediterranean Basin as a model area. Environmental predictors (climate and geology) were employed to predict suitable habitats, shedding light on the lichens' ecological niches. Habitat suitability models consistently aligned with the Mediterranean's geographical area, indicating a tight link between lichen distribution and Mediterranean climate classification. While climate change may pose vulnerabilities, no significant range shifts beyond the latitudinal limit of the Mediterranean were predicted. Despite overlapping climatic niches, differences in microhabitat preferences in terms of insolation were observed among studied taxa. Vulnerable regions with potential habitat decreases were identified under future scenarios, emphasizing the importance of environmental heterogeneity in securing local species persistence. This study supports the hypothesis that these lichen symbiotic systems are restricted to the Mediterranean Basin, highlighting their potential to reflect Mediterranean climate, environmental stability, and indicate the boundaries of the Mediterranean biome. Our investigation demonstrates that collection-based research can yield significant contributions to current biogeography.

The effect of climate change on the variation of low flow rates within mountainous basins: Case study of the Srou basin-Middle Atlas-Morocco (1976-2016)

Abstract The study of hydro-climatic variability over extended periods is crucial for comprehending the effects of climate variability on water resources and the incidence of droughts. In Morocco, drought has historically afflicted the plains, eastern, and southern regions of the country. However, the impact of drought in mountainous areas has often been overlooked. Climate change has exacerbated this situation, as evidenced by significant water deficits experienced by Morocco in 1982 and 2007. These events underscore the vulnerability of regions to drought, especially during periods of low-flow. This study focuses on examining rainfall variability within the Srou River basin, and its impact on fluctuations in low-flow rates in the context of a changing climate. The analysis utilizes the Cumulative Sum method to assess these dynamics. Besides, rainfall data and monthly low-flow rates were analysed and assessed. The obtained results reveal a significant variability in rainfall across the watershed, with a general trend of decline punctuated by occasional brief wet periods. These drought episodes have led to diminished surface and groundwater resources within the area. This research sheds light on the pressing need to address hydro-climatic challenges and underscores the urgency of adaptation measures to safeguard water security in Morocco’s diverse geographical contexts.

HIGH-RESOLUTION SATELLITE ESTIMATION OF SNOW COVER FOR FLOOD ANALYSIS IN EAST KAZAKHSTAN REGION

The increasing frequency of extreme weather events linked to climate change has made flood forecasting an important issue, particularly in mountainous regions where snowmelt is a major driver of seasonal flooding. This study explores the application of snow cover estimation techniques to assess snowmelt dynamics and their potential impact on flood risks in the Ulba and Uba basins in East Kazakhstan. To achieve this, high-resolution multispectral satellite imagery from the Sentinel-2 Surface Reflectance dataset is used, focusing on images collected between March and October for the years 2021 to 2024. The images are processed in Google Earth engine platform with strict filtering based on spatial intersection with the basins and cloud cover pixels percentage, ensuring high-quality data for snow cover analysis. The study utilizes multiple remote sensing indices for snow cover estimation. The normalized difference snow index is calculated using the green and shortwave infrared bands to detect snow-covered pixels. Fractional snow-covered area is derived from the NDSI using the 'FRA6T' relationship, offering a more nuanced estimate of snow distribution across the basins. Additionally, a near-infrared to shortwave infrared ratio threshold is employed to minimize confusion between snow and water, improving the detection of snow cover, particularly in regions near water bodies or during melt periods. The resulting snow cover maps and fSCA estimates provide a detailed picture of snow distribution and melt dynamics, contributing to the assessment of snowmelt’s role in flood risk development. The obtained insights can assist in refining flood forecasting models, improving early warning systems, and supporting informed water resource management in vulnerable regions.

Remotely Sensed Comparative Spatiotemporal Analysis of Drought and Wet Periods in Distinct Mediterranean Agroecosystems

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions.

Identification of Flood-Prone Areas Using Geo-Informatics: A Case Study of Erbil City, Kurdistan Region, Iraq

Global flood events, intensified by an intricate interplay of natural dynamics and human activities, pose severe environmental and safety threats, driving the demand for advanced vulnerability assessments. This research innovates with a holistic geo-informatics methodology, pinpointing flood-prone regions in Erbil City, Kurdistan Region, Iraq. It harnesses the Analytic Hierarchy Process and Geographic Information System synergies, enriched with insights from multispectral satellite observations, to conduct an exhaustive analysis of key flood susceptibility indicators. These encompass geological, hydrological, meteorological, and anthropogenic parameters, integrated into a robust Geographic Information System analytical matrix. Through strategic factor analysis and prioritization, the study distills a detailed flood susceptibility cartogram, classifying regional vulnerabilities into distinct risk echelons: high (encompassing 25%), moderate (38.1%), low (28.4%), and very low (8.5%). The final flood map highlights an acute susceptibility epicenter in the northeast, contrasting with the minimal threat southwest. This demarcation reaffirms the Analytic Hierarchy Process-Geographic Information System fusion's precision in translating multifaceted data into strategic intelligence, proving instrumental for scholars, administrative frameworks, and developmental strategists. The insights garnered are pivotal in sculpting informed urban development and flood counteractive blueprints, instrumental in mitigating flood repercussions and preserving ecological and human integrities.

Regional Impact of the COVID-19 Pandemic on Cancer Screening.

Cancer screening is the most cost-effective prevention strategy that enables improved cancer mortality and morbidity rates. However, there was a significant decline in cancer screening during the COVID-19 pandemic worldwide. This study aimed to measure regional differences in cancer screening by comparing screening rates before and during COVID-19 and to examine factors explaining the regional difference in cancer screening. All variables including the differences in cancer screening rate before and during the COVID-19 pandemic were collected from 229 administrative subregions in South Korea and joined with each community in ArcGIS environment. Factors explaining regional difference in cancer screening were analyzed through descriptive statistics, correlation analysis, and interactive decision tree modeling. Cancer screening rates decreased in all regions during the COVID-19 pandemic in South Korea. The findings revealed that national health insurance premiums, the number of cancer screening facilities, livelihood benefit recipients, and the population aged 65+ could be classified as variables highly affecting the decrease in cancer screening rate. These findings highlight the efforts to appraise different barriers to cancer screening in each community. In addition, it is important to promote sustainable cancer screening strategies from regional perspectives based on regional vulnerabilities and their complex impact on cancer screening.

Macroseismic Analysis of the 2023 Earthquakes in Jayapura

On January 2 and February 9, 2023, two significant earthquakes struck Jayapura City, leading to widespread panic, severe damage to buildings and public infrastructure, and multiple casualties. In response, the BBMKG V Earthquake Survey Team conducted a macroseismic study to evaluate the geological impacts, assess community responses, and document the overall effects of the earthquakes. The methodology employed included structured interviews and questionnaires administered to affected residents. The study revealed that soft rock conditions in the area contributed to an MMI scale VI impact, which resulted in extensive damage to public facilities and residential buildings. The insights gained from this study offer valuable information for improving future earthquake mitigation strategies and enhancing preparedness in seismically vulnerable regions.