Assessing the cascading impacts of natural disasters in a multi-layer behavioral network framework.
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ABSTRACT:
SUBMITTER: Naqvi A
PROVIDER: S-EPMC8505522 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundNatural disasters are increasing in their frequency and complexity. Understanding how their cascading effects can lead to infectious disease outbreaks is important for developing cross-sectoral preparedness strategies. The review focussed on earthquakes and floods because of their importance in Europe and their potential to elucidate the pathways through which natural disasters can lead to infectious disease outbreaks.MethodsA systematic literature review complemented by a call for evidence was conducted to identify earthquake or flooding events in Europe associated with potential infectious disease events.ResultsThis review included 17 peer-reviewed papers that reported on suspected and confirmed infectious disease outbreaks following earthquakes (4 reports) or flooding (13 reports) in Europe. The majority of reports related to food- and water-borne disease. Eleven studies described the cascading effect of post-disaster outbreaks. The most reported driver of disease outbreaks was heavy rainfall, which led to cross-connections between water and other environmental systems, leading to the contamination of rivers, lakes, springs and water supplies. Exposure to contaminated surface water or floodwater following flooding, exposure to animal excreta and post-disaster living conditions were among other reported drivers of outbreaks.ConclusionsThe cascade effects of natural disasters, such as earthquakes and floods, include outbreaks of infectious disease. The projection that climate change-related extreme weather events will increase in Europe in the coming century highlights the importance of strengthening preparedness planning and measures to mitigate and control outbreaks in post-disaster settings.
| S-EPMC7536539 | biostudies-literature
Project description:Complex systems can fail through different routes, often progressing through a series of (rate-limiting) steps and modified by environmental exposures. The onset of disease, cancer in particular, is no different. Multi-stage models provide a simple but very general mathematical framework for studying the failure of complex systems, or equivalently, the onset of disease. They include the Armitage-Doll multi-stage cancer model as a particular case, and have potential to provide new insights into how failures and disease, arise and progress. A method described by E.T. Jaynes is developed to provide an analytical solution for a large class of these models, and highlights connections between the convolution of Laplace transforms, sums of random variables, and Schwinger/Feynman parameterisations. Examples include: exact solutions to the Armitage-Doll model, the sum of Gamma-distributed variables with integer-valued shape parameters, a clonal-growth cancer model, and a model for cascading disasters. Applications and limitations of the approach are discussed in the context of recent cancer research. The model is sufficiently general to be used in many contexts, such as engineering, project management, disease progression, and disaster risk for example, allowing the estimation of failure rates in complex systems and projects. The intended result is a mathematical toolkit for applying multi-stage models to the study of failure rates in complex systems and to the onset of disease, cancer in particular.
| S-EPMC6527192 | biostudies-literature
Project description:Reliable and complete data held in disaster databases are imperative to inform effective disaster preparedness and mitigation policies. Nonetheless, disaster databases are highly prone to missingness. In this article, we conduct a missing data diagnosis of the widely-cited, global disaster database, the Emergency Events Database (EM-DAT) to identify the extent and potential determinants of missing data within EM-DAT. In addition, through a review of prominent empirical literature, we contextualise how missing data within EM-DAT has been handled previously. A large proportion of missing data was identified for disasters attributed to natural hazards occurring between 1990 and 2020, particularly on the economic losses. The year the disaster occurred, income-classification of the affected country and disaster type were all significant predictors of missingness for key human and economic loss variables. Accordingly, data are unlikely to be missing completely at random. Advanced statistical methods to handle missing data are thus warranted when analysing disaster data to minimise the risk of biasing statistical inferences and to ensure global disaster data can be trusted.
| S-EPMC9481555 | biostudies-literature
Project description:Cascading disasters progress from one hazard event to a range of interconnected events and impacts, with often devastating consequences. Rain-related cascading disasters are a particularly frequent form of cascading disasters in many parts of the world, and they are likely to become even more frequent due to climate change and accelerating coastal development, among other issues. (1) Background: The current literature review extended previous reviews of documented progressions from one natural hazard event to another, by focusing on linkages between rain-related natural hazard triggers and infrastructural impacts. (2) Methods: A wide range of case studies were reviewed using a systematic literature review protocol. The review quality was enhanced by only including case studies that detailed mechanisms that have led to infrastructural impacts, and which had been published in high-quality academic journals. (3) Results: A sum of 71 articles, concerning 99 case studies of rain-related disasters, were fully reviewed. Twenty-five distinct mechanisms were identified, as the foundation for a matrix running between five different natural hazards and eight types of infrastructural impacts. (4) Conclusion: Relatively complex quantitative methods are needed to generate locality-specific, cascading disaster likelihoods and scenarios. Appropriate methods can leverage the current matrix to structure both Delphi-based approaches and network analysis using longitudinal data.
| S-EPMC7400172 | biostudies-literature
Project description:This paper develops a framework for analyzing the dynamics through which cascading disasters evolve, spread and come to control in situations of uncertainty and vulnerability. The framework first establishes the idea that disasters are inherently a social phenomenon rooted in the social structure and reflects the processes of social change. The core of such social structures and processes is the mechanism of collective action. We then explain the ways in which formal mathematical models in general, and game theoretical models in particular, can help analyze the dynamics of collective action, detect the core parameters through which they evolve and, in particular, identify the interactions between these parameters. We show that these dynamics may have different forms of development, which are usually non-linear and cyclic. The framework also emphasizes the major role of information and social learning in these dynamics.
| S-EPMC7240265 | biostudies-literature
Project description:The relationship between natural disasters and communicable diseases is frequently misconstrued. The risk for outbreaks is often presumed to be very high in the chaos that follows natural disasters, a fear likely derived from a perceived association between dead bodies and epidemics. However, the risk factors for outbreaks after disasters are associated primarily with population displacement. The availability of safe water and sanitation facilities, the degree of crowding, the underlying health status of the population, and the availability of healthcare services all interact within the context of the local disease ecology to influence the risk for communicable diseases and death in the affected population. We outline the risk factors for outbreaks after a disaster, review the communicable diseases likely to be important, and establish priorities to address communicable diseases in disaster settings.
| S-EPMC2725828 | biostudies-literature
Project description:Circadian KaiC phosphorylation in cyanobacteria reconstituted in vitro recently initiates a series of studies experimentally and theoretically to explore its mechanism. In this paper, we report a dynamic diversity in hexameric KaiC phosphoforms using a multi-layer reaction network based on the nonequivalence of the dual phosphorylation sites (S431 and T432) in each KaiC subunit. These diverse oscillatory profiles can generate a kaleidoscopic phase modulation pattern probably responsible for the genome-wide transcription rhythms directly and/or indirectly in cyanobacteria. Particularly, our model reveals that a single KaiC hexamer is an energy-based, phosphorylation-dependent and self-regulated circadian oscillator modulated by KaiA and KaiB. We suggest that T432 is the main regulator for the oscillation amplitude, while S431 is the major phase regulator. S431 and T432 coordinately control the phosphorylation period. Robustness of the Kai network was examined by mixing samples in different phases, and varying protein concentrations and temperature. Similar results were obtained regardless of the deterministic or stochastic method employed. Therefore, the dynamic diversities and robustness of Kai oscillator make it a qualified core pacemaker that controls the cellular processes in cyanobacteria pervasively and accurately.
| S-EPMC2773046 | biostudies-literature
Project description:Recent availability of geo-localized data capturing individual human activity together with the statistical data on international migration opened up unprecedented opportunities for a study on global mobility. In this paper, we consider it from the perspective of a multi-layer complex network, built using a combination of three datasets: Twitter, Flickr and official migration data. Those datasets provide different, but equally important insights on the global mobility - while the first two highlight short-term visits of people from one country to another, the last one - migration - shows the long-term mobility perspective, when people relocate for good. The main purpose of the paper is to emphasize importance of this multi-layer approach capturing both aspects of human mobility at the same time. On the one hand, we show that although the general properties of different layers of the global mobility network are similar, there are important quantitative differences among them. On the other hand, we demonstrate that consideration of mobility from a multi-layer perspective can reveal important global spatial patterns in a way more consistent with those observed in other available relevant sources of international connections, in comparison to the spatial structure inferred from each network layer taken separately.
| S-EPMC5426086 | biostudies-literature
Project description:Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.
| S-EPMC5811603 | biostudies-other
Project description:BackgroundPatient portals play an important role in connecting patients with their medical care team, which improves patient engagement in treatment plans, decreases unnecessary visits, and reduces costs. During natural disasters, patients' needs increase, whereas available resources, specifically access to care, become limited.ObjectiveThis study aims to examine patients' health needs during a natural crisis by analyzing the electronic messages sent during Hurricane Harvey to guide future disaster planning efforts.MethodsWe explored patient portal use data from a large Greater Houston area health care system focusing on the initial week of the Hurricane Harvey disaster, beginning with the date of landfall, August 25, 2017, to August 31, 2017. A mixed methods approach was used to assess patients' immediate health needs and concerns during the disruption of access to routine and emergent medical care. Quantitative analysis used logistic regression models to assess the predictive characteristics of patients using the portal during Hurricane Harvey. This study also included encounters by type (emergency, inpatient, observation, outpatient, and outpatient surgery) and time (before, during, and after Hurricane Harvey). For qualitative analysis, the content of these messages was examined using the constant comparative method to identify emerging themes found within the message texts.ResultsOut of a total of 557,024 patients, 4079 (0.73%) sent a message during Hurricane Harvey, whereas 31,737 (5.69%) used the portal. Age, sex, race, and ethnicity were predictive factors for using the portal and sending a message during the natural disaster. We found that prior use of the patient portal increased the likelihood of portal use during Hurricane Harvey (odds ratio 13.688, 95% CI 12.929-14.491) and of sending a portal message during the disaster (odds ratio 14.172, 95% CI 11.879-16.907). Having an encounter 4 weeks before or after Hurricane Harvey was positively associated with increased use of the portal and sending a portal message. Patients with encounters during the main Hurricane Harvey week had a higher increased likelihood of portal use across all five encounter types. Qualitative themes included: access, prescription requests, medical advice (chronic conditions, acute care, urgent needs, and Hurricane Harvey-related injuries), mental health, technical difficulties, and provider constraints.ConclusionsThe patient portal can be a useful tool for communication between patients and providers to address the urgent needs and concerns of patients as a natural disaster unfolds. This was the first known study to include encounter data to understand portal use compared with care provisioning. Prior use was predictive of both portal use and message sending during Hurricane Harvey. These findings could inform the types of demands that may arise in future disaster situations and can serve as the first step in intentionally optimizing patient portal usability for emergency health care management during natural disasters.
| S-EPMC8444041 | biostudies-literature