Search Results (149)

Blackleg caused by a hemi-biotrophic fungus Plenodomus lingam (syn. Leptosphaeria maculans) poses a significant threat to global canola production. Changing climatic conditions further exacerbate the intensity and prevalence of blackleg epidemics. Shifts in temperature, humidity, and precipitation patterns can enhance pathogen virulence and disease spread. This review synthesizes the knowledge on integrated disease management (IDM) approaches for blackleg, including crop rotation, resistant cultivars, and chemical and biological controls, with an emphasis on advanced strategies such as disease forecasting models, remote sensing, and climate-adapted breeding. Notably, bibliometric analysis reveals an increasing research focus on the intersection of blackleg, climate change, and sustainable disease management. However, critical research gaps remain, which include the lack of region-specific forecasting models, the limited availability of effective biological control agents, and underexplored socio-economic factors limiting farmer adoption of IDM. Additionally, the review identifies an urgent need for policy support and investment in breeding programs using emerging tools like AI-driven decision support systems, CRISPR/Cas9, and gene stacking to optimize fungicide use and resistance deployment. Overall, this review highlights the importance of coordinated, multidisciplinary efforts, integrating plant pathology, breeding, climate modeling, and socio-economic analysis to develop climate-resilient, locally adapted, and economically viable IDM strategies for sustainable canola production. Full article

The management of public health projects in a BANI (brittle, anxious, non-linear, incomprehensible) environment, exemplified by the ongoing war in Ukraine, presents unprecedented challenges due to fragile systems, heightened uncertainty, and complex socio-political dynamics. This study proposes an AI-driven framework to enhance the resilience and effectiveness of public health interventions under such conditions. By integrating a coupled SEIR–Infodemic–Panicdemic Model with war-specific factors, we simulate the interplay of infectious disease spread, misinformation dissemination, and panic dynamics over 1500 days in a Ukrainian city (Kharkiv). The model incorporates time-varying parameters to account for population displacement, healthcare disruptions, and periodic war events, reflecting the evolving conflict context. Sensitivity and risk–opportunity analyses reveal that disease transmission, misinformation, and infrastructure damage significantly exacerbate epidemic peaks, while AI-enabled interventions, such as fact-checking, mental health support, and infrastructure recovery, offer substantial mitigation potential. Qualitative assessments identify technical, organisational, ethical, regulatory, and military risks, alongside opportunities for predictive analytics, automation, and equitable healthcare access. Quantitative simulations demonstrate that risks, like increased displacement, can amplify infectious peaks by up to 28.3%, whereas opportunities, like enhanced fact-checking, can reduce misinformation by 18.2%. These findings provide a roadmap for leveraging AI to navigate BANI environments, offering actionable insights for public health practitioners in Ukraine and other crisis settings. The study underscores AI’s transformative role in fostering adaptive, data-driven strategies to achieve sustainable health outcomes amidst volatility and uncertainty. Full article

This study develops a novel framework for supply chain financial resilience (SCFR) by integrating complex adaptive systems theory with supply chain finance and resilience concepts. To explore how disruption risks propagate through the supply chain, we propose an SEIJR epidemic model that categorizes node enterprises into five distinct states: susceptible (S), exposed (E), infected (I), quarantined (J), and recovered (R). Transitions between these states are captured using differential equations. Through numerical simulations linking this epidemiological approach to financial resilience metrics, we demonstrate several key findings: first, disruption risks temporarily reduce resilience; second, properly managed risk propagation through timely isolation and effective mitigation can transform disruptions into opportunities for systemic improvement; third, isolation measures need to work alongside recovery mechanisms to significantly improve the overall resilience of supply chain finance. Our results show that optimal isolation strategies enable the system to reach a risk-free equilibrium while simultaneously elevating the supply chain’s long-term financial resilience above initial levels. These findings offer theoretical and practical guidance for dynamic, adaptive risk management strategies in supply chain finance. Empirical validation and other research topics will be explored in subsequent studies. Full article

Epidemics spread through shipping networks and have dual characteristics as both biological sources of infection and triggers of cascading failures. However, existing resilience models fail to capture this dual and coupled dynamics. To minimize the cascading impacts of epidemics on global shipping networks, this paper proposes an innovative resilience assessment framework that considers the interaction between epidemic transmission and the shipping network cascading failure. First, a weighted shipping network topology is constructed based on route flow characteristics to quantify route frequency, stopping time, and the number of infected people, and the epidemic transmission across ports is modeled with an improved SEIR model, which contains a heterogeneous infectivity function and a dynamic transmission matrix, revealing a dual transmission mechanism inside and outside the ports. Second, a two-stage cascading failure model is developed: a direct failure triggered by infected people exceeding the threshold and an indirect failure triggered by the dynamic redistribution of loads. The load redistribution strategy is optimized to reconcile the residual port capacity and the risk of infection. Finally, a multidimensional resilience assessment framework covering structural destruction resistance, network efficiency, path redundancy, and a cascading failure propagation rate is constructed. Example validation shows that the improved load redistribution strategy reduces the maximum connected subgraph decay rate by 68.2%, reduces the cascading failure rate by 88%, and improves the peak network efficiency by 128.2%. In case of multi-source epidemics, the state of the network collapse can be shortened by 12 days if the following recovery strategy is adopted: initially repair high connectivity hubs (e.g., Port of Shanghai), and then repair high centrality nodes (e.g., Antwerp Port) to achieve a balance between recovery efficiency and network functionality. The research results reduce the risk of systemic disruptions in maritime networks and provide decision-making tools for dynamic port scheduling during pandemics. Full article

Background/Objectives: Epidemics have historically shaped societies, influencing demographic structures, social organization, and economic stability. The 1742–1743 epidemic had a profound impact on populations along the Royal Road (Camino Real), the main colonial corridor between Buenos Aires and Lima. However, its specific demographic and socio-economic effects remain underexplored. This study aims to examine these impacts of the 1742–1743 epidemic through a comparative analysis of urban centers and Indigenous communities. Methods: A historical–comparative approach was employed, analyzing secondary sources including parish records and colonial administrative documents. This study assessed excess mortality and socio-economic consequences across different population groups and settlement types. Results: Mortality rates increased dramatically—up to twelve times the pre-epidemic average in Cordova (Córdoba) and by 45% in Santa Fe—disproportionately affecting Indigenous and enslaved populations. Urban centers experienced severe economic disruption and slow recovery, whereas Indigenous communities and Jesuit missions demonstrated greater resilience. Their communal strategies and early isolation measures contributed to a faster demographic stabilization. Additionally, the epidemic weakened colonial governance in some areas, altering local power structures. Conclusions: The epidemic of 1742–1743 revealed divergent patterns of vulnerability and resilience. Comparative analysis underscores recurring themes in the epidemic response and recovery, drawing relevant parallels with contemporary crises such as COVID-19. Recognizing these historical patterns of adaptation can inform present and future public health strategies. The terminology “plague” is used based on contemporary sources and not confirmed clinically. Full article

Although the immediate impact of the COVID-19 pandemic has been alleviated, its long-term effects continue to shape global health and public safety. Policymakers should prepare for potential future health crises and direct urban planning toward more sustainable outcomes. While numerous studies have examined factors influencing the risk of COVID-19, few have investigated the spatial spillover effects of urban form and green space. In this study, we quantified urban form using landscape pattern indices, represented population mobility with the Baidu Migration Scale Index, and assessed the role of key influencing factors on the epidemic through STIRPAT and spatial Durbin models. Our findings reveal that population migration from Wuhan had a significant local impact on the spread of COVID-19. These factors not only intensified local transmission, but also triggered positive spatial spillover effects, spreading the virus to neighboring regions. We also found that green space connectivity (pc₅) plays a crucial role in reducing the spread of the virus, both locally and in surrounding areas. High green space connectivity helps mitigate disease transmission during an epidemic. In contrast, the spatial configuration and unipolarity of urban areas (pc₁) contributed to the increased spread of the virus to neighboring cities. Ultimately, balancing building density with green space distribution is essential for enhancing urban resilience. This research provides new insights into sustainable urban planning and helps us understand the impact of the spillover effects of gray–green space forms on public health and safety. Full article

With the acceleration of urbanization, citizens are facing more pandemic challenges. A deeper understanding of constructing more resilient cities can help citizens be better prepared for potential future pandemics or disasters. In this study, a static–dynamic analytical framework for urban health resilience evaluation and influencing factor exploration was proposed, which helped not only to analyze the basic static urban health resilience (SUHRI) under normal conditions but also to evaluate the dynamic urban health resilience (DURHI) under an external epidemic shock. The epidemic dynamic model could reasonably simulate the epidemic change trend and quantitatively evaluate resistance and recovery capacity, and the proposed influencing factor exploration model improved the model fitness by filtering out the influence of population flow autocorrelation existing in the residuals. SUHRI and DUHRI, and their corresponding key influencing factors, were compared and discussed. The results of the static–dynamic integration and difference score showed that 60.6% cities within the study area had a similar performance on SUHRI and DUHRI, but there was also a typical difference: some regional hubs exhibited high SUHRI but had only mid-level DUHRI, which was attributed to stronger external disturbances such as higher population mobility. The key influencing factors for static and dynamic urban health resilience also vary. Hospital capacity and income had the strongest influence on static urban health resilience but a relatively weaker or even non-significant correlation with dynamic urban health resilience sub-indices. The extracted population flow eigenvector collection had the strongest influence on dynamic urban health resilience, as it represents the population flow connection among cities, which could reflect the information of policy response, such as policy stringency and support intensity. We hope that our study will shed some light on constructing more resilient urban systems and being prepared for future public health emergencies. Full article

The deep integration of the digital economy and the tourism industry has reconstructed the ecological pattern of the industry, and the tourism industry urgently needs to explore ways to improve resilience in the post-epidemic era to cope with uncertainties and risks. Relying on the FIIF framework, this study uses the statistical data of 30 provinces in China to verify the path configuration of the digital economy on the resilience improvement of the tourism industry and the synergistic effect between various variables, aiming to reveal the multi-configuration effect of the digital economy, driving the resilience improvement of the tourism industry, analyzing the regional differentiated path selection mechanism, and providing a theoretical framework and practical guidance for the resilience improvement and digital transformation of the tourism industry. The results show that (1) the variables of “digital infrastructure” and “digital innovation expenditure” constitute the necessary conditions for the high-resilience level of the tourism industry, and “digital talent shortage” and “digital innovation investment” are the key factors for the formation of low-resilience configuration. (2) There are three configuration paths for high resilience, which are manifested in the two types of “digital infrastructure and digital innovation driven type” and “digital infrastructure and digital industry driven type”. The low-resilience configuration has three paths and has an asymmetric relationship with high-resilience configuration paths. (3) The tourism industry’s resilience configuration in the eastern and central–western regions shows significant differences. Full article

African swine fever (ASF) has had a devastating impact on Vietnam’s swine industry since its introduction in Vietnam in 2019, leading to the culling of six million pigs. This paper aimed to review the epidemiological dynamics of ASF in Vietnam and measures applied to control the disease. ASF progressed through an initial epidemic phase (2019–2020) and has transitioned into a more endemic phase (2021–2024). The disease spread rapidly during the epidemic phase, driven by human-mediated transmission routes and inadequate biosecurity practices, particularly on smallholder farms. To control ASF, the Vietnamese government endorsed a national control plan that included biosecurity enhancements, disease surveillance, establishing ASF-free compartments, researching and evaluating ASF vaccines, and strengthening the capacity of veterinary services. While these measures have helped reduce the number of outbreaks, challenges persist, including the emergence of recombinant ASF strains, limited vaccine adoption, and gaps in the veterinary infrastructure. ASF has substantially changed Vietnam’s swine industry, shifting toward reducing small-scale household farming and increasing professional households and large-scale farms. As ASF has transitioned into an endemic phase, sustainable strategies focusing on continuous monitoring, improved vaccination coverage, and education programs are essential in order to mitigate its impacts and ensure the resilience of Vietnam’s swine industry. Full article

Livelihood resilience research is a critical area in contemporary sustainable livelihood studies, offering valuable insights into residents’ livelihood transformation and strategies under sudden shocks or disruptions. This research analyzes 365 households from five towns reliant on tourism in the Wulingyuan Scenic range, situated in the central section of the Wuling Mountain range. The findings reveal that residents’ livelihood resilience decreased by 6.38% from the normal tourism stage (before 2020) to the epidemic disruption stage (2020–2022), followed by a 4.54% increase during the tourism recovery stage (after 2022). Despite fluctuations caused by exogenous shocks like the COVID-19 pandemic, residents’ livelihood resilience remained at a moderate level overall. Spatially, livelihood resilience exhibited a northwest–southeast dispersion trend, with a noticeable shift toward the southeast. Key drivers of resilience included increased material capital, enhanced organizational management capabilities, residents’ clear understanding of livelihood challenges, and positive attitudes. Conversely, constraints included the pandemic’s impacts, limited community participation, reduced tourist numbers, inefficient ecotourism management, insufficient financial capital, weak learning capacities, and monolithic livelihood strategies. The study highlights that those changes in the tourism development environment, coupled with interactive pathways of buffering, adaptation, and transformation capabilities, jointly influence livelihood resilience. Synergistic efforts in these areas can significantly enhance residents’ livelihood resilience. Full article

Climate change is driving the spread of transboundary wheat diseases, necessitating the development of resilient wheat varieties for sustainable agriculture. Wheat rusts, including leaf rust (LR), yellow rust (YR), and stem rust (SR), remain among the most economically significant diseases, causing substantial yield losses worldwide. Enhancing genetic diversity by identifying and deploying rust resistance genes is crucial for durable resistance in wheat breeding programs. This study aimed to identify quantitative trait loci (QTL) associated with rust resistance in the CIMMYT wheat line Kasuku, released in Kenya in 2018. A recombinant inbred line (RIL) population (181 lines) derived from Kasuku (triple rust-resistant) and Apav#1 (triple rust-susceptible) was evaluated under artificial LR and YR epidemics in Mexico and YR and SR in Kenya. QTL mapping using genotyping-by-sequencing (DArTSeq) and phenotypic data identified four major loci: QLrYrSr.cim-1BL (Lr46/Yr29/Sr58) on 1BL, conferring resistance to LR, YR, and SR; QLrYr.cim-2AS (Yr17/Lr37) on 2AS, providing LR and YR resistance; QLrYr.cim-3AL on 3AL; and QLrYrSr.cim-6AL on 6AL, representing novel loci associated with multiple rust resistances. Additionally, minor QTL were also identified: for LR (QLr.cim-2DS on 2DS, QLr.cim-6DS on 6DS), for YR (QYrKen.cim-3DS on 3DS, QYrKen.cim-6BS on 6BS), and for SR (QSr.cim-2BS on 2BS, QSr.cim-5AL on 5AL, QSr.cim-6AS on 6AS). RILs carrying these QTL combinations exhibited significant reductions in rust severity. Flanking markers for these loci are being used to develop Kompetitive Allele-Specific PCR (KASP) markers for fine mapping and marker-assisted selection (MAS). These findings contribute to the strategic deployment of rust resistance genes in wheat breeding programs, facilitating durable resistance to multiple rust pathogens. Full article

The aging communities within traditional historical and cultural districts in the post-epidemic era face numerous challenges, including declining vitality, deteriorating environments, sluggish economies, and heightened public health risks. This paper aims to explore strategies for promoting the internal self-development of aging communities and enhancing their resilience. It analyzes the resilience of these communities through four dimensions: social factors, built environments, economic factors, and ecological environments. Using the Sizhou’an community in China as a case study, this paper examines the underlying causes of vulnerability and proposes renewal strategies. These strategies include stimulating the vitality of elderly groups, improving the community’s spatial environment, leveraging regional cultural advantages, and establishing urban community agricultural gardens. Furthermore, it presents a community renewal model characterized by “government guidance + community leadership + capital introduction + resident participation” to bolster community resilience and vitality, thereby ensuring sustainable development. Full article

Background/Objectives: The 1742–1743 plague epidemic had a profound impact on populations along the Royal Road (Camino Real), the principal trade route connecting Buenos Aires and Lima. This study aimed to quantify the demographic and socioeconomic consequences of the epidemic in Cordova and Santa Fe, with a focus on excess mortality and its broader implications for marginalized groups. Methods: This research utilized parish death records and complementary historical sources to calculate excess mortality in Cordova and Santa Fe during the epidemic. Mortality rates were compared across pre-epidemic (1740–1741), epidemic (1742–1743), and post-epidemic (1744–1745) periods. Additional data on demographic variables such as age, gender, marital status, and ethnicity were analyzed to identify patterns of vulnerability and resilience. Results: Excess mortality during the epidemic was significant, with death rates in Cordova peaking at 12 times the pre-epidemic average in May 1743, while Santa Fe experienced a 45% increase in mortality, peaking in December 1743. Marginalized groups, including enslaved and Indigenous populations, were disproportionately affected, exacerbating existing social inequalities. The epidemic also disrupted socioeconomic structures and highlighted systemic vulnerabilities in both urban centers. Conclusions: This study demonstrates the critical role of excess mortality as a metric for understanding the demographic and socioeconomic impacts of historical epidemics. By integrating quantitative and qualitative analyses, it underscores the intersection of public health crises with social structures in colonial Latin America. The findings offer insights into resilience and recovery mechanisms relevant to both historical and contemporary public health strategies. Full article

The frequent occurrence of disasters has brought significant challenges to increasingly complex urban systems. Resilient city planning and construction has emerged as a new paradigm for dealing with the growing risks. Infrastructure systems like transportation, lifelines, flood control, and drainage are essential to the operation of a city during disasters. It is necessary to measure how risks affect these systems’ resilience at different spatial scales. This paper develops an infrastructure risk and resilience evaluation index system in city and urban areas based on resilience characteristics. Then, a comprehensive infrastructure resilience evaluation is established based on the risk–resilience coupling mechanism. The overall characteristics of comprehensive infrastructure resilience are then identified. The resilience transmission level and the causes of resilience effects are analyzed based on the principle of resilience scale. Additionally, infrastructure resilience enhancement strategies under different risk scenarios are proposed. In the empirical study of Zhengzhou City, comprehensive infrastructure resilience shows significant clustering in the city area. It is high in the central city and low in the periphery. Specifically, it is relatively high in the southern and northwestern parts of the airport economy zone (AEZ) and low in the center. The leading driving factors in urban areas are risk factors like flood and drought, hazardous materials, infectious diseases, and epidemics, while resilience factors include transportation networks, sponge city construction, municipal pipe networks, and fire protection. This study proposes a “risk-resilience” coupling framework to evaluate and analyze multi-hazard risks and the multi-system resilience of urban infrastructure across multi-level spatial scales. It provides an empirical resilience evaluation framework and enhancement strategies, complementing existing individual dimensional risk or resilience studies. The findings could offer visualized spatial results to support the decision-making in Zhengzhou’s resilient city planning outline and infrastructure special planning and provide references for resilience assessment and planning in similar cities. Full article

The novel coronavirus (COVID-19) pandemic has become one of the most devastating epidemics recorded in world history. The adverse impact of the pandemic is significant within the architecture, engineering, and construction (AEC) industry and other sectors of the economy. A considerable number of COVID-19 research studies have been undertaken in response to this global challenge across disciplines, with minimal output in the built environment. Thus, this study aims to identify, analyse, and visualise COVID-19 research trends in the AEC industry to unfold the sector’s response and readiness for possible future global pandemics. The study employed the scientometric approach to explore COVID-19 research outputs in the AEC industry, an aspect of health and safety in construction that has not been considered in past studies owing to the novel nature of the coronavirus pandemic. The findings revealed that the USA, China, and the United Kingdom were the top published countries and most affected as well. Co-occurring keywords analysis further showed that the predominant focus of scholarly outputs on the subject is around four clusters focusing on sustainable resilience, pandemic pathways and insights, land use and energy strategies, and indoor air excellence. Notwithstanding its limitations, the findings establish the need for the AEC industry to adopt innovative and holistically sustainable construction practices in the event of future disasters and pandemics. The findings of the study provide a robust theoretical foundation for researchers and stakeholders in the built environment, improving the sector’s mitigative and adaptive capacity in the potential occurrence of future pandemics. Full article