High-risk Areas Research Articles

A geospatial analysis of flood risk zones in Cyprus: insights from statistical and multi-criteria decision analysis methods

Over the past few decades, flood disasters have emerged as the predominant natural hazard in Cyprus, primarily driven by the escalating influence of climate change in the Mediterranean region. In view of this, the objective of this study is to develop a geospatial flood risk map for the island of Cyprus by considering 14 flood hazard factors and five flood vulnerability factors, utilizing geographic information systems (GIS) and remotely sensed datasets. A comparative assessment was conducted for hazard mapping, employing statistical methods of frequency ratio (FR) and FR Shannon’s entropy (FR-SE), and multi-criteria decision analysis method of fuzzy analytic hierarchy process (F-AHP). The main findings indicated that the FR method exhibited the highest predictive capability, establishing it as the most suitable approach for flood hazard mapping. Additionally, vulnerability factors were aggregated using F-AHP to generate the vulnerability map. The resulting flood risk map, which is the product of flood hazard and flood vulnerability, revealed that 9% of the island was located within highly risky regions, while 13.2% was classified as moderate risk zones. Spatial analysis of these high-risk areas indicated their concentration in the primary city districts of the island. Therefore, to mitigate future risks within these cities, an analysis of potential expansion zones was conducted, identifying the best-suited zone exhibiting the lowest risk. The generated flood risk map can serve as a valuable resource for decision-makers on the island, facilitating the integration of flood risk analysis into urban management plans.

Current State of Canine Heartworm in Portugal.

The favourable geo-climatic conditions in Portugal have made it highly conducive to the development of Dirofilaria immitis in dogs, leading to its identification as an endemic region. This nematode is rapidly spreading across Europe, particularly in northeastern countries. The objective of this study was to provide an updated assessment of the prevalence of this disease in Portuguese dogs, analysing the results in relation to epidemiological and geo-environmental factors, and to identify potential risk factors. A total of 1367 dogs from all continental and insular districts were included in the study and tested for D. immitis antigens. The overall prevalence was found to be 5.9%. It was observed that the disease is spreading northward, with previously unaffected districts now reporting cases, and that the prevalence in coastal districts exceeded that of inland ones. Notably, the Aveiro district exhibited a significant increase in D. immitis prevalence, while in certain districts such as Setúbal, Santarém, Madeira, or Faro, a stabilisation or decrease in prevalence was noted. Furthermore, outdoor and older dogs were found to be at a higher risk of infection. No positive cases were detected in the Azores. Most of the infected dogs were located in areas of high and medium risk of infection. This study underscores the importance of implementing pharmacological prophylaxis, vector control strategies, and public awareness programs to control the spread of this zoonotic disease.

REMOTE SENSING AND GOOGLE EARTH ENGINE FOR RAPID FLOOD MAPPING AND DAMAGE ASSESSMENT: A CASE OF TYPHOON GONI (ROLLY) AND VAMCO (ULYSSES)

Abstract. Flooding is a devastating natural disaster with global repercussions, affecting human life, crop production, and infrastructure. The increasing frequency and unpredictability of flood events, driven by climate change, highlight the urgent need for rapid and accurate flood mapping and damage assessment. This study explores the use of Google Earth Engine, a web-based platform that utilizes satellite imagery and geospatial data, for flood mapping and damage assessment. By incorporating localized datasets, such as region-specific land cover maps and population density information, the developed workflow provides a robust tool for assessing flood extent, identifying high-risk areas, and estimating the impact on cropland and urban centers. Key findings showed that Cagayan province presented the highest potential flood area, covering approximately 55,063 hectares. This province also had the largest population at risk, with around 39,440 individuals potentially exposed to the effects of flooding. Moreover, the cropland in Cagayan province experienced the most substantial impact, with around 91.26% being affected due to the swelling of the Cagayan River. Camarines Sur experienced severe devastation in urban areas, with about 269 hectares affected by flooding from the Bicol River. This study's findings contribute to a comprehensive understanding of flood impacts beyond the extent of flooding, facilitating informed decision-making, emergency response planning, and targeted interventions to mitigate the effects of floods on communities, agriculture, and urban areas. The approach presented here can be applied in other regions, supporting improved flood management and mitigation strategies for national.

Environmental Surveillance of Poliovirus and Non-polio Enteroviruses in Iran, 2017-2023: First Report of Imported Wild Poliovirus Type 1 Since 2000.

In Iran, which is at high risk of the Wild Poliovirus (WPV) and Vaccine-Derived Poliovirus (VDPV) importation due to its neighborhood with two polio endemic countries, Pakistan and Afghanistan, Environmental Surveillance (ES) was established in November 2017. Sistan-Balouchestan province was chosen for the ES due to its vicinity with Pakistan and Afghanistan. Five sewage collection sites in 4 cities (Zahedan, Zabol, Chabahar and Konarak) were selected in the high-risk areas. Since the establishment of ES in November 2017 till the end of 2023, 364 sewage specimens were collected and analyzed. The ES detected polioviruses which have the highest significance for polio eradication program, that is, Wild Poliovirus type 1 (WPV1) and Poliovirus type 2 (PV2). In April and May 2019, three of 364 (0.8%) sewage specimens from Konarak were positive for imported WPV1. According to phylogenetic analysis, they were highly related to WPV1 circulating in Karachi (Sindh province) in Pakistan. PV2 was also detected in 5.7% (21/364) of the sewage specimens, most of which proved to be imported from the neighboring countries. Of 21 isolated PV2s, 7 were VDPV2, of which 5 proved to be imported from the neighboring countries as there was VDPV2 circulating in Pakistan at the time of sampling, and 2 were ambiguous VDPVs (aVDPV) with unknown source. According to the findings of this study, as long as WPV1 and VDPV2 outbreaks are detected in Iran's neighboring countries, there is a definite need for continuation and expansion of the environmental surveillance.

Server-enabled mixed reality for flood risk communication: On-site visualization with digital twins and multi-client support

This study introduces a novel mobile mixed reality (MR) system to improve communication among stakeholders regarding climate-change-driven flood risk. This MR system enables stakeholders to visualize flood risks on common mobile devices, such as smartphones and tablets, offering perspectives from their respective environments. The system overcomes the computational limitations of previous mobile MR systems by rendering the MR images on a server. Furthermore, distributing users across multiple servers enables many users to simultaneously perform server-enabled MR, facilitating widespread engagement in flood risk communication. The system uses a viewport transformation to accurately display virtual floods and correct for real-time posture changes. A prototype tested in a high-risk flood area achieved real-time MR visualization at more than 16 frames per second, even on multiple devices. Future research will aim to promote stakeholder participation through more accurate visualization of virtual floods and improved interactive information sharing among users.

InSAR-based landslide hazard mapping and identification of at-risk infrastructures in a selected district of North Shewa Zone, Ethiopia.

The devastating nature of landslides demands a thorough understanding of their spatial distribution and the risks they pose to human settlements and infrastructural assets. In this study, we employed a combination of Interferometric Synthetic Aperture Radar (InSAR) and Geographic Information System (GIS) techniques to explore the western escarpment of the Main Ethiopian Rift, with a focus on selected districts within the northern Shewa Zone, Ethiopia. By analyzing the SAR data, we derived 28 displacement maps and utilized them to create a comprehensive landslide hazard zonation map. The results indicated significant ground displacement, particularly along the rift margins and areas characterized by rugged terrain. The hazard zones were classified based on their level of risk, with 44% classified as very low, 24% as low, 5% as moderate, 13% as high, and 14% as very high hazard zones. The accuracy of our results was evaluated using receiver operating characteristic (ROC) analysis, which was conducted utilizing landslide inventory data. The analysis demonstrated a remarkable area under the curve (AUC) value of 0.848, providing strong evidence for the validity of our findings. Additionally, our study involved a spatial and statistical assessment of major infrastructure, revealing that 20 to 28% of these properties were in hazard zones ranging from moderate to very high levels, which calls for efficient risk-reduction actions. Therefore, this finding enables stakeholders to identify high-risk areas, prioritize mitigation efforts, and minimize the impact of landslide disasters.

Enhancing Disaster Resilience for Sustainable Urban Development: Public–Private Partnerships in Japan

A resilient building environment is crucial for securing sustainable development in urban areas, as the 2030 Agenda for Sustainable Development Goal 11 stresses. In developing countries in particular, the risk of disasters is increasing due to the poorly built environment caused by urbanization. However, building disaster resilience in vulnerable urban environments characterized by aging houses, limited public spaces, and complex land rights and tenancy issues poses a major challenge. This study aims to identify critical factors influencing effective disaster-resilient urban development by examining Japan’s experience, with a focus on approaches facilitating public–private partnerships. Driven by disasters like the 1995 Kobe Earthquake, Japan has promoted innovative strategies to improve urban resilience and mitigate disaster impacts. The Disaster Mitigation Zone Implementation Program represents a novel program designed to revitalize densely populated areas with aging wooden structures highly vulnerable to disasters. Through semi-structured interviews, a literature review, and an in-depth case study in Tokyo, this research analyzes the development and effectiveness of this targeted redevelopment approach. Findings underscore the pivotal role of policies promoting public–private collaboration, consensus-building mechanisms among stakeholders, flexibility in project formulation, and financial incentives via government subsidies. Engaging the private sector ensures project feasibility through urban development expertise, while simpler, smaller-scale projects attract greater private investment. Japan’s experience offers valuable insights into collaborative, context-sensitive strategies for enhancing urban disaster resilience through targeted redevelopment of high-risk areas.

Assessment of flood risk in Söğütlü stream watershed of Trabzon province in Turkey using geographic information systems and analytic hierarchy process approach

Floods are significant natural disasters that have wide-ranging social, economic, and environmental consequences on a global scale. They lead to land degradation and increased erosion, which in turn negatively impacts water quality. In the present study, the Söğütlü stream watershed in the Eastern Black Sea Region of Turkey was chosen as the study area to create a flood risk map using Analytical Hierarchy Process and Weighted Overlay tools in the ArcGIS. The raster maps, including soil type, rainfall, landuse, slope, aspect, elevation, and distance to the stream, were utilized as the foundation for the analysis. The flood risk map generated from this analysis reveals five risk zones that is very high, high, moderate, low, and very low-risk zones. Statistical analysis was performed to evaluate the obtained data. The study results indicate that low and moderate areas encompass 95.98% of the watershed, while high-risk and very high-risk areas account for 4.02% of the watershed in the flood risk map of the Söğütlü watershed. It was observed that areas in close proximity to rivers, low slope end elevation were more susceptible to flooding. This study is great importance as it allows for the development of preventive, preparatory, and post-disaster plans before flood events occur by providing a flood risk map. Moreover, the creation of a flood risk map at the watershed scale helps planners in undertaking soil and water conservation efforts during watershed planning.

Integrating ecosystem service value in the disclosure of landscape ecological risk changes: a case study in Yangtze River Economic Belt, China

Urban expansion and inappropriate land uses have caused a decline in the regional ecosystem services capacity, which is contrary to United Nations’ Sustainable Development Goal (SDG) 15 aiming to protect and promote sustainable use of terrestrial ecosystems. Landscape ecological risk (LER) visually depicts the disturbances to ecosystem services and environmental shifts resulting from human activities. Consideration of ecosystem services in LER assessment has not been sufficiently researched. Here, we employed ecosystem service values (ESV) to define landscape vulnerability, and adopted an enhanced risk assessment framework, amalgamating landscape patterns and ecosystem processes, to evaluate the spatial-temporal shifts in ESV and LER in the Yangtze River Economic Belt (YREB) from 2000 to 2020. We attempted to analyze the relationship between LER and anthropogenic disturbances. The results showed that over the past 20 years, the general trend revealed a diminishing high-risk area, while medium and low-risk regions expanded. Notably, the urban agglomeration of the YREB experienced a marked surge in risk. Regarding migration direction, the low-risk category has expanded in the east–west direction, while the medium and high-risk categories have shown inward contraction mainly in the north–south direction. The findings highlight the complex changes between ecological processes and LER under anthropogenic disturbances, and can serve as a guide for sustainable risk management and the development of ecological security patterns.

Spatial-temporal analysis of hepatitis B in Fujian Province, China in 2012–2021

BackgroundFujian Province has one of the highest reported incidences of hepatitis B virus infection in China. This study aimed to provide a theoretical framework for preventing and controlling hepatitis B in Fujian Province, and to assess the trends and the spatial-temporal distribution patterns of hepatitis B in this region. MethodsData on hepatitis B cases were extracted from the National Notifiable Infectious Disease Surveillance System. Spatial autocorrelation analysis, trend surface analysis, and spatial-temporal scanning statistics were used to identify the spatial and aggregation patterns at the county level. The Joinpoint was used to assess the reported incidence trends. ResultsThe average reported incidence of hepatitis B in Fujian from 2012 to 2021 was 14.46/10,000 population, with 583,262 notified cases. The age-adjusted reported incidence of hepatitis B decreased from 17.44/10,000 population in 2012 to 11.88/10,000 population in 2021, with an average reduction in the annual percentage change of 4.5%. There were obvious spatial-temporal aggregation characteristics in hepatitis B cases, and a high-incidence area was located in eastern Fujian. Spatio-temporal scanning statistics revealed four levels of aggregation of hepatitis B reporting rates. The first level of aggregation area included Minhou, Gulou, Jin'an, Taijiang, and nine other districts and counties. ConclusionsThe incidence of hepatitis B is declining in Fujian Province. Spatial clusters of hepatitis B cases in Fujian Province were identified, and high-risk areas in eastern Fujian still exist. Closely monitoring the general patterns in the occurrence of hepatitis B and implementing focused control and preventative strategies are important.

Risk Analysis and Visualization of Merchant and Fishing Vessel Collisions in Coastal Waters: A Case Study of Fujian Coastal Area

The invasion of ship domains stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying the collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validates it through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of the collision risk. Finally, taking the high-risk area for merchant and fishing vessel collisions in the Minjiang River Estuary as an example, this paper conducts an analysis that involves classifying ship collision scenarios, extracts risk data under different collision scenarios, and visually analyzes areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis are verified by the number of accidents that occurred in the most recent three years.

Mechanical simulation and debonding risk analysis of OLED panels with optically clear adhesives

This paper presents a mechanical simulation model and analysis method for OLED panels. The functional layers within the panel are bonded using optically clear adhesives (OCAs), which are pressure-sensitive adhesives (PSAs), resulting in a soft interface bonding problem. It was discovered that the normal tensile debonding strength of OCAs was significantly lower than the shear debonding strength. To address this issue, a three-layer structure simulation model of “hard + soft + hard” is established, which allows for analyzing the screen folding problem of any radius. Additionally, a suitable element mesh generation strategy for multi-layer structure screens is proposed. A debonding risk index based on pressure is introduced by comparing the interlaminar normal and maximum principal stress. The influence of thickness, bending radius, and Young’s modulus on longitudinal stress and debonding risk index is examined. It is observed that the influence of thickness and Young’s modulus on debonding risk is non-monotonic, indicating the presence of an optimal solution. The high debonding risk area is located at the beginning of the folding mechanism and screen bonding. The proposed debonding risk index is not only applicable to OCAs but also to all PSA with similar structures.

Physical durability and insecticidal activity of long-lasting insecticidal nets in Cruzeiro do Sul, Brazil

Vector control is one of the principal strategies used for reducing malaria transmission. Long-lasting insecticidal bed nets (LLINs) are a key tool used to protect populations at risk of malaria, since they provide both physical and chemical barriers to prevent human-vector contact. This study aimed to assess the physical durability and insecticidal efficacy of LLINs distributed in Cruzeiro do Sul (CZS), Brazil, after 4 years of use. A total of 3000 LLINs (PermaNet 2.0) were distributed in high malaria risk areas of CZS in 2007. After 4 years of use, 27 ‘rectangular’ LLINs and 28 ‘conical’ LLINs were randomly selected for analysis. The evaluation of physical integrity was based on counting the number of holes and measuring their size and location on the nets. Insecticidal efficacy was evaluated by cone bioassays, and the amount of residual insecticide remaining on the surface of the LLINs was estimated using a colorimetric method. After 4 years of use, physical damage was highly prevalent on the rectangular LLINs, with a total of 473 holes detected across the 27 nets. The upper portion of the side panels sustained the greatest damage in rectangular LLINs. The overall mosquito mortality by cone bioassay was < 80% in 25/27 rectangular LLINs, with panel A (at the end of the rectangular bednet) presenting the highest mortality (54%). The overall mean insecticide concentration was 0.5 µg/sample, with the bednet roof containing the highest average concentration (0.61 µg/sample). On the conical LLINs, 547 holes were detected, with the bottom areas sustaining the greatest damage. The cone bioassay mortality was < 80% in 26/28 of the conical LLINs. The mean insecticide concentration was 0.3 µg/sample. After 4 years of use, the insecticidal efficacy of the LLINs was diminished to below acceptable thresholds.

Habitat suitability modeling of mosquito species in Faiyum Governorate, Egypt, using GIS

BackgroundThe life cycle and geographic range of mosquitoes are profoundly influenced by weather conditions. In Faiyum Governorate, Egypt, researchers looked at over 42 different mosquito breeding areas in the wild. Culex pipiens, Culex antennatus, Culex perexiguus, Culex theileri, Anopheles multicolor, Anopheles sergentii, Ochlerotatus caspius, Culiseta longiareolata, and Uranotaenia unguiculata, were all represented among the collected mosquito larvae. Using Maxent, we identified the most important bioclimatic factors affecting habitat appropriateness for each species. In order to determine the link between a species’ habitat appropriateness and bioclimatic factors, the computer builds response curves for each bioclimatic factor. All species risk maps, species richness maps, and individual species maps were generated with a Software that build interactive web maps (ArcGIS 10.3).ResultsEach mosquito species’ range was impacted by four bioclimatic factors. The most influential factors were those linked to temperature and precipitation. Culex antennatus, Culex perexiguus, Culex pipiens, and Ochlerotatus caspius responded best to temperature-related factors. Precipitation of wettest month (bio 13) was effective in four species (Anopheles multicolor, Culex antennatus, Culex perexiguus, and Culex pipiens).ConclusionAreas in the north and west of El-Fayoum district (Zawyat El-Karadsah, Beni-Saleh, and Monshat Abd-Allah), in Tamiya in Kafr Mahfouz, in the south of Abshway, especially in Tobhar, in the north of Atssa, in the south and center of Sinnuris have been identified as high-risk areas and more susceptible to mosquito-borne diseases.

Use of the HEC RAS model for the analysis of exceptional floods in the Ouémé basin

Abstract. The Ouémé River basin extends over almost half of Benin's territory, entirely located in a humid tropical climate. This river system includes a deltaic zone (delta of the Ouémé) known for its high agricultural potential and thus subject to a socio-economic development agenda. The Ouémé delta is facing recurrent floods that maintain rural agricultural population into a retrograding crisis with significant damages such as losses of properties. The objective of this study is to improve decision-making in the Ouémé basin through the simulation of exceptional floods using the HEC-RAS model. The HEC RAS model is a conceptual model, which works through mathematical and physical formulas to implement environmental phenomena for forecasting, understanding and analysis purposes. The model inputs used are basin GIS data, hydro-meteorological data, characteristics of existing hydraulic structures, etc. The targeted outputs include 1D/2D/3D view plans with support of satellite images, tables, graphs and curves. It is worth mentioning that the model provides outputs compatible with other tools, such as civil engineering (Civil 3D, Revit, Infraworks, etc.) and GIS, that help to expand the valorization fields. The implementation of the model in the Ouémé basin has made it possible to note: (i) that the recurring effect of losses and damages is justified by the settlement of the population on the river banks; (ii) that there is an important agricultural production in areas of high flood risk; (iii) that depending on the occurrence of the phenomenon, the flooded extent and the height of submersion remains variable, and more important for extreme flooding; (iv) about 12.07 % occurrence of river flood against 13.24 % for flash flood at a return period of 30 years. Moreover, it is very relevant to note that most of flood waters converge to the western part of the basin (an area with a low risk of flooding, stretched over 63.68 km2) and to the eastern part around the Damè-Wogon depression (an area at high risk of flooding, stretched over 10.49 km2).

Exploration of anatomical distribution of brain metastasis from breast cancer at first diagnosis assisted by artificial intelligence

ObjectivesThis study aimed to explore the spatial distribution of brain metastases (BMs) from breast cancer (BC) and to identify the high-risk sub-structures in BMs that are involved at first diagnosis. MethodsMagnetic resonance imaging (MRI) scans were retrospectively reviewed at our centre. The brain was divided into eight regions according to its anatomy and function, and the volume of each region was calculated. The identification and volume calculation of metastatic brain lesions were accomplished using an automatically segmented 3D BUC-Net model. The observed and expected rates of BMs were compared using 2-tailed proportional hypothesis testing. ResultsA total of 250 patients with BC who presented with 1694 BMs were retrospectively identified. The overall observed incidences of the substructures were as follows: cerebellum, 42.1 %; frontal lobe, 20.1 %; occipital lobe, 9.7 %; temporal lobe, 8.0 %; parietal lobe, 13.1 %; thalamus, 4.7 %; brainstem, 0.9 %; and hippocampus, 1.3 %. Compared with the expected rate based on the volume of different brain regions, the cerebellum, occipital lobe, and thalamus were identified as higher risk regions for BMs (P value ≤ 5.6*10−3). Sub-group analysis according to the type of BC indicated that patients with triple-negative BC had a high risk of involvement of the hippocampus and brainstem. ConclusionsAmong patients with BC, the cerebellum, occipital lobe and thalamus were identified as higher-risk regions than expected for BMs. The brainstem and hippocampus were high-risk areas of the BMs in triple negative breast cancer. However, further validation of this conclusion requires a larger sample size.

Impacts of land use change on surface infiltration capacity and urban flood risk in a representative karst mountain city over the last two decades

Urban areas are undergoing rapid expansion, resulting in diminished vegetation cover and an escalating urban flood problem, and posing substantial threats to aquatic ecosystems, human safety, and socioeconomic structures. However, research on urban flood risk using methods like the Analytic Hierarchy Process (AHP), further exploration of spatiotemporal variations is needed, especially within the context of karst mountainous urban clusters. This study focuses on Guiyang city within a karst mountainous urban cluster, investigating fractional vegetation cover (FVC), infiltration capacity, and urban flood risk. Methodologies encompass slope trend analysis, the utilization of the Google Earth Engine, and geographic detectors to assess the dynamics of FVC and infiltration capacity. AHP is employed to assign weights to infiltration capacity, land use and land cover (LULC), FVC, and elevation, culminating in the generation of flood risk maps through linear weighted overlay. The results showed that: (1) The average FVC in Guiyang City was 0.7440 in 21 years, with relatively low levels in the central and southern regions. The FVC increased by 0.21% per year from 2000 to 2020, driven mainly by land use change and human activities. (2) The infiltration capacity of the city of Guiyang has increased as a whole, mainly due to reforestation efforts in specific areas, while the infiltration capacity of impervious areas tends to decrease. (3) The central urban areas exhibit greater vulnerability, with an estimated ten-year average growth rate of 73.36% in very high flood risk areas by 2030, affecting 7.38% of Guiyang's total area. These urban flood risk maps serve as valuable tools for local governments to enhance urban management practices.

A compartment and metapopulation model of Rocky Mountain spotted fever in southwestern United States and northern Mexico

Rocky Mountain spotted fever (RMSF) is a fatal tick-borne zoonotic disease that has emerged as an epidemic in western North America since the turn of the 21st century. Along the US south-western border and across northern Mexico, the brown dog tick, Rhipicephalus sanguineus, is responsible for spreading the disease between dogs and humans. The widespread nature of the disease and the ongoing epidemics contrast with historically sporadic patterns of the disease. Because dogs are amplifying hosts for the Rickettsia rickettsii bacteria, transmission dynamics between dogs and ticks are critical for understanding the epidemic. In this paper, we developed a compartment metapopulation model and used it to explore the dynamics and drivers of RMSF in dogs and brown dog ticks in a theoretical region in western North America. We discovered that there is an extended lag—as much as two years—between introduction of the pathogen to a naïve population and epidemic-level transmission, suggesting that infected ticks could disseminate extensively before disease is detected. A single large city-size population of dogs was sufficient to maintain the disease over a decade and serve as a source for disease in surrounding smaller towns. This model is a novel tool that can be used to identify high risk areas and key intervention points for epidemic RMSF spread by brown dog ticks.

Spatial clusters of human and livestock anthrax define high-risk areas requiring intervention in Lao Cai Province, Vietnam 1991-2022.

Anthrax, a widespread zoonosis in low and middle-income countries with low disease awareness and insufficient livestock vaccination coverage, has been known in Lao Cai Province in northern Vietnam for years before its apparent absence in 2009, which requires investigation as this infection is frequently reported from neighbouring provinces and countries. We aimed to describe the seasonal patterns of anthrax (1991-2008), compare livestock anthrax vaccine coverage to disease occurrence (1991- 2022), and delineate the high-risk areas to inform local disease surveillance in the province. We illustrated the seasonal pattern of anthrax and provided a comparison between livestock vaccine coverage and disease occurrence by purely spatial SaTScan (Poisson model, 25% population at risk) to detect spatial clusters of human and livestock anthrax using population derived from zonal statistics routines. The number of cases, crude cumulative incidence, and spatial clusters of human and livestock anthrax were mapped in QGIS. Results indicate peak anthrax incidence from May to October. Buffalo, domestic cattle, and horses accounted for 75% of total animal cases. Horse anthrax was more common in Lao Cai than in its neighbours and often occurred in years with human mortality. Vaccination covered less than 30% of the livestock population. We found an apparent pattern where anthrax was controlled from 1998-2003 with higher vaccine coverage (>20%) and identified spatial clusters of human and livestock anthrax in Muong Khuong, Bao Thang, and Bac Ha districts of Lao Cai. The local public health and veterinary agencies are recommended to revisit the high-risk areas and communicate with neighbouring provinces for a regional approach to anthrax surveillance and control.

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Examining the Saihanba Mechanical Forest Farm, this study utilized Landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the Support Vector Machine (SVM) method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units. Employing landscape pattern indices and a method of spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. The results indicate that since 1987, there have been significant changes in land use types, especially in forest landscapes, their proportion increasing from 23.19% to 74.55%. In 1987, the proportion of high-risk areas was 72.30%, but in 2020, high-risk areas had significantly decreased and clustered in specific locations. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. After comprehensive exploration using a geographic detector, we found that landscape type, temperature, and vegetation coverage are the main risk factors. Among them, landscape type has the greatest impact on the landscape and works together with slope, aspect, and precipitation. In forest farm management, only the adaptation and adjustment of single factors are often paid attention to, while the compound effects of multiple factors are ignored. The results of this study bring important reference value to the operation and development of forest farms.