Early-warning Indicators Research Articles

How much matching there is in functional, phylogenetic and taxonomic optima of epiphytic macrolichen communities along a European climatic gradient?

Adopting an integrative approach that explicitly includes the different facets of biodiversity is crucial to assess the response of biological communities to changing environments. The identification of the optimal climatic conditions where communities maximize their functional, phylogenetic and taxonomic diversity is useful to compare whether the optima of the different facets of biodiversity match. Using a wide climatic gradient across Europe, we quantified the functional, phylogenetic and taxonomic diversity of epiphytic macrolichen communities, which are valuable early-warning ecological indicators. We ordinated 22 environmental variables and simultaneously illustrated non-parametric regressions of the diversity metrics against the climatic space using the ‘hilltop plot’ method to detect the climatic conditions in which the different diversity facets peaked and to compare the match between them. Functional diversity predicted at least part of the peaks of phylogenetic and taxonomic diversity, but phylogenetic and taxonomic hotspots did not overlap. Epiphytic macrolichen communities maximized their functional and phylogenetic diversity in the southernmost forests, with the Mediterranean region appearing as a biodiversity hotspot. Regarding the studied traits, photobiont type and growth form showed clearly defined optima while the quantitative physiological traits and families' optima did not show this pattern in response to climate. The different facets of biodiversity were not surrogates of each other highlighting the need for an integrative approach to assess the effect of environmental changes on communities and to establish conservation priorities. As functional traits mediated the response of lichen communities to climate, preserving high functional diversity might indirectly preserve high phylogenetic and taxonomic diversity. Relevant ecological indicators useful to develop rapid assessment methods to evaluate the effects of climatic changes include the photobiont type and growth form. The lack of relation between quantitative traits and climate call for further research to unveil their role as ecological indicators of small-scale variables or as effect traits.

National profile of early warning indicators of HIV pharmaco-resistance in Cameroon

Introductiondepuis le lancement en 2015 de la stratégie « Traitement pour tous » au Cameroun, un plan d´accélération du traitement antirétroviral (TARV) est mis en œuvre avec des progrès remarquables. Ces efforts s´accompagnent d´un risque d´émergence de la pharmaco-résistance du VIH. L´Organisation Mondiale de la Santé (OMS) propose ainsi la surveillance des indicateurs d´alerte précoce (IAP) de la pharmaco-résistance du VIH. L'objectif de cette étude était d'évaluer sur le plan national les IAP de la pharmaco-résistance du VIH au Cameroun.Méthodesune étude rétrospective a été menée en décembre 2017 dans les 10 régions du Cameroun; elle a évalué les six IAPs recommandés par l´OMS sur 68 sites de prise en charge du VIH sélectionnés de façon aléatoire. La période de rapportage s´étendait de Juillet 2016 à Juin 2017.Résultatsles scores à l´échelle nationale étaient: retrait des médicaments dans les délais (IAP1): 66%; rétention sous TARV 12 mois après l´initiation (IAP2): 66%; rupture de stocks d´ARVs sur une période de 12 mois (IAP3): 53%; couverture en réalisation des tests de charge virale (CV) (IAP4): 10%; suppression de la CV à 12 mois de TARV (IAP5): 73% et pratiques de dispensation du TARV (IAP6): 100%. Les scores régionaux étaient similaires.Conclusionla performance des IAP au Cameroun est faible et nécessite des interventions urgentes, prioritairement la couverture des tests de CV, la gestion optimale des ARV et l´adhérence des patients.

An Early Warning System for Identifying Financial Instability

Financial crises prediction is an essential topic in finance. Designing an efficient Early Warning System (EWS) can help prevent catastrophic losses resulting from financial crises. We propose an EWS for predicting potential market instability conditions under which perturbations in the price level may evolve in large price declines or changes in general. Our system is based on the so called price-volatility feedback rate, which is supposed to describe the ease of the market in absorbing small price perturbations. A logit regression EWS is employed to predict future large price losses and Early Warning Indicators (EWIs) based on the realized variance (RV) and on the price-volatility feedback rate are considered. Our study reveals that, while the RV may sometimes fail in predicting future price losses in a given time series, the EWI employing the price-volatility feedback rate is always an important predictor of financial instability.

Characterizing the Energetics of Vortex-Scale and Sub-Vortex-Scale Asymmetries during Tropical Cyclone Rapid Intensity Changes

AbstractOur collective understanding of azimuthally asymmetric features within the coherent structure of a tropical cyclone (TC) continues to improve with the availability of more detailed observations and high-resolution model outputs. However, a precise understanding of how these asymmetries impact TC intensity changes is lacking. Prior attempts at investigating the asymmetric impacts follow a mean–eddy partitioning that condenses the effect of all the asymmetries into one term and fails to highlight the differences in the role of asymmetries at different scales. In this study, we present a novel energetics-based approach to analyze the asymmetric impacts at multiple length scales during periods of rapid intensity changes. Using model outputs of TCs under low and high shear, we compute the different energy pathways that enhance/suppress the growth of multiscale asymmetries in the wavenumber (WN) domain. We then compare and contrast the energetics of the mean-flow field (WN 0) with that of the persistent, coherent vortex-scale asymmetric structures (WNs 1 and 2) and the more local, transient, sub-vortex-scale asymmetries (WNs ≥ 3). We find in our case studies that the dominant mechanisms of growth/decay of the asymmetries are the baroclinic conversion from available potential to kinetic energy at individual scales of asymmetries and the transactions of kinetic energy between the asymmetries of various length scales, rather than the barotropic mean–eddy transactions as is typically assumed. Our case study analysis further shows that the growth/decay of asymmetries is largely independent of the mean. Certain aspects of eddy energetics can potentially serve as early-warning indicators of TC rapid intensity changes.

News-based Sentiment Indicators

We construct sentiment indices for 20 countries from 1980 to 2019. Relying on computational text analysis, we capture specific language like “fear”, “risk”, “hedging”, “opinion”, and, “crisis”, as well as “positive” and “negative” sentiments, in news articles from the Financial Times. We assess the performance of our sentiment indices as “news-based” early warning indicators (EWIs) for financial crises. We find that sentiment indices spike and/or trend up ahead of financial crises.

Early Warning of mmWave Signal Blockage and AoA Transition Using sub-6 GHz Observations

The susceptibility of millimeter-wave (mmWave) signals to physical blockage and abrupt signal strength variations presents a challenge to reliable 5G communication. This work proposes and examines the feasibility of utilizing lower-frequency signals as early-warning indicators of mobile mmWave signal blockage or recovery. A physics-based channel simulation tool incorporating Fresnel diffraction and image sources is employed to demonstrate that sub-6 GHz signals "lead" mmWave signals in reaching a specific signal-strength threshold by several to tens of milliseconds at mobile speeds, suggesting early-warning systems are viable. This predictive approach stems from frequency-dependent properties of diffraction and does not assume a specific topology or mobile and obstacle speeds. Realistic simulations that include transitions from line of sight (LoS) to non-line of sight (NLoS) and reflection scenarios are employed to verify the proposed prediction capabilities. Moreover, prediction of the strongest multipath component and its angle of arrival (AoA) using sub-6 GHz observations is investigated.

Early warning indicators and microbial community dynamics during unstable stages of continuous hydrogen production from food wastes by thermophilic dark fermentation

Early warning indicators (EWIs) and microbial community dynamics during thermophilic dark fermentation-based hydrogen production (TFHP) from food wastes were investigated during stable and fluctuating operations in continuous systems. Difference and redundancy analyses revealed the linkage between dominant genera, metabolites and process parameters and characterized the EWIs and mechanism of instability of the TFHP. Besides biogas production rate (GPR), hydrogen proportion and volatile fatty acids (VFAs) concentrations, the potential warning function of the microbial community were observed. Thermoanaerobacterium was the dominant genus which decreased during the unstable stages. Bacillus is another EWI in unstable stages when the value of pH is lower. Lactobacillus and Weissella appeared as OLR increased to 9 g VS L−1 d−1 in the OLR-9 unstable stage. This study demonstrates the key EWIs for monitoring and controlling continuous hydrogen production and its stability.

Náboženský extremismus jako příčina ozbrojených konfliktů: indikátory a systémy včasného varování

The main topic and focus of this article is to identify the most relevant indicators of the rise of religious extremism as an important cause of armed conflicts. A religiously motivated conflict is a relevant topic in modern security studies and research. Conflict prevention using the early-warning indicators identified in this article might be interesting for the security expert community. In the article chosen methodology is available with the recommendation to following research in the examined field.

Evaluating early warning and coincident indicators of business cycles using smooth trends

AbstractWe present a composite coincident indicator designed to capture the state of the Spanish economy. Our approach, based on smooth trends, guarantees that the resulting indicators are reasonably smooth and issue stable signals, reducing the uncertainty. The coincident indicator has been checked by comparing it with the one recently proposed by the Spanish Economic Association index. Both indexes show similar behavior and ours captures very well the beginning and end of the official recessions and expansion periods. Our coincident indicator also tracks very well alternative mass media indicators typically used in the political science literature. We also update our composite leading indicator (Bujosa et al., Journal of Forecasting, 2013, 32(6), 481–499). It systematically predicts the peaks and troughs of the new Spanish Economic Association index and provides significant aid in forecasting annual gross domestic product growth rates. Using only real data available at the beginning of each forecast period, our indicator one‐step‐ahead forecast shows improvements over other individual alternatives and different forecast combinations.

Evaluation of treatment response, drug resistance and HIV-1 variability among adolescents on first- and second-line antiretroviral therapy: a study protocol for a prospective observational study in the centre region of Cameroon (EDCTP READY-study)

BackgroundSub-Saharan Africa (SSA) alone has nine out of every 10 children living with HIV globally and monitoring in this setting remains suboptimal, even as these children grow older. With scalability of antiretroviral therapy (ART), several HIV-infected children are growing towards adolescence (over 2.1 million), with the potentials to reach adulthood. However, despite an overall reduction in HIV-related mortality, there are increasing deaths among adolescents living with HIV (ADLHIV), with limited evidence for improved policy-making. Of note, strategies for adolescent transition from pediatrics to adult-healthcare are critical to ensure successful treatment response and longer life expectancy. Interestingly, with uptakes in prevention of mother-to-child transmission, challenges in ART programs, and high viremia among children in SSA, the success rate of paediatric ART might be quickly jeopardised, with possible HIV-1 drug-resistance (HIVDR) emergence, especially after years of paediatric ART exposure. Therefore, monitoring ART response in adolescents and evaluating HIVDR patterns might limit disease progression and guide on subsequent ART options for SSA ADLHIV.ObjectivesAmong Cameroonian ADLHIV receiving ART, we shall evaluate the rate of immunovirologic failure, acquired HIVDR-associated mutations, HIV-1 subtype distribution, genetic variability in circulating (plasma) versus archived (cellular) viral strains, and HIVDR early warning indicators (EWIs) at different time-points.MethodsA prospective and observational study will be conducted among 250 ADLHIV (10–19 years old) receiving ART in the centre region of Cameroon, and followed-up at 6 and 12 months after enrollment. Following consecutive sampling at enrolment, plasma viral load and CD4/CD8 count will be measured, and genotypic resistance testing (GRT) will be performed both in plasma and in buffy coat for participants experiencing virological failure (two consecutive viremia > = 1000 copies/ml). Plasma viral load and CD4/CD8 will be monitored for all participants at 6 and 12 months after enrolment. HIVDR-EWIs will be monitored and survival analysis performed during the 12 months follow-up. Primary outcomes are rates of virological failure, acquired-HIVDR, and mortality.DiscussionOur findings will provide evidence-based recommendations to ensure successful transition from paediatrics to adult ART regimens and highlight further needs of active ART combinations, for reduced morbidity and mortality in populations of ADLHIV within SSA.

An Efficacy Study of a Ninth-Grade Early Warning Indicator Intervention

Building on previous research showing how well ninth-grade student behaviors predict on-time high school graduation, this experimental study investigates the impact of a ninth-grade intervention on student attendance and course passing. The study, conducted in 41 geographically and demographically diverse high schools within a single state, evaluates the effects of placing a half-time staff member in high schools to implement the Early Warning Intervention (EWI) Team model designed to monitor ninth-grade early warning indicators and provide timely interventions. Analyses based on the pre-specified student outcomes of attendance rate and percentage of ninth-grade course credits earned indicated no statistically significant impact of the intervention. On secondary outcome variables, results indicated that students in treatment schools were significantly less likely than control school students to be chronically absent. The difference between treatment and control school students on dichotomous measures of course failure were not statistically significant. The widespread dissemination of research and best practices related to early warning systems and ninth-grade interventions likely accounted for low levels of contrast between treatment and control school practices and outcomes.

Combining biomarker and community approaches using benthic macroinvertebrates can improve the assessment of the ecological status of rivers

Indices based on community structure provide a global ecological status of the biological communities but they are of limited value as early-warning indicators of contamination. Almost two decades after the Water Framework Directive (2000/60/EC) was adopted, we reviewed publications that measured biomarkers in benthic macroinvertebrates in biomonitoring programmes of fluvial systems. The focus was on studies that attempted to incorporate both biomarkers and community-based approaches in the evaluation of the ecological status of rivers and streams. Overall, the data showed that biomarker measurements in benthic macroinvertebrate species can offer complementary information on the factors threatening these communities. This information is particularly useful for water authorities, in order to take actions before a system collapses into a state from which recovery is difficult or impossible. Gaps in need to be addressed for rapid and efficient implementation of biomarkers in benthic macroinvertebrates in routine wide-scale monitoring are discussed. In particular, site-specific baselines have to be defined, taking into account the influence of biotic and abiotic factors on these biochemical responses. Further studies, including different biomarkers, environmental stressors, macroinvertebrate taxa and river types, will provide crucial information on how to establish adequate biomarker strategies to indicate future ecological damage.

Designing Gaps as Early Warning Indicators: Accuracy, Predictive Power, and Robustness

Credit gaps are good predictors for financial crises, and banking regulators recommend using them to inform countercyclical capital buffers for banks. Researchers typically create credit gap measures using trend-cycle decomposition methods, which require many modelling choices, such as the method used, and the smoothness of the underlying trend. Other choices hinge on the tradeoffs implicit in how gaps are used as early warning indicators (EWIs) for predicting crises, such as the preference over false positives and false negatives. We evaluate how the performance of credit-gap-based EWIs for predicting crises is influenced by these modelling choices. For the most common trend-cycle decomposition methods used to recover credit gaps, we find that optimally smoothing the trend enhances out-of-sample prediction. We also show that out-of-sample performance improves further when we consider a preference for robustness of the credit gap estimates to the arrival of new information, which is important as any EWI should work in real-time. We offer several practical implications.

HIV DRUG RESISTANCE EARLY WARNING INDICATORS AND THEIR ASSESSMENT IN SOME REGIONS OF RUSSIA

The article describes the first limited experience of early warning indicators (EWIs) of HIV drug resistance recommended by WHO; information on their content and order of use is given. The results of EWIs survey performed in 2016 in nine Russian cities: Blagoveshchensk, Vladivostok, Yekaterinburg, Izhevsk, Krasnodar, Perm, Saint-Petersburg, Khanty-Mansiysk, and the Moscow Region — are presented. The on-time pill pick up indicators were optimal, >90% in four centers (44,4%), all others showed intermediate resulеs (80–90%). The retention rate was over 85% in six of the nine regions (66,6%). Two of the nine regions (22,2%) reported the existence of stock-outs in the supply of antiretroviral drugs. Bi-and monotherapy with antiretroviral drugs was administered to patients in three regions (33,3%). Suppression of viral load to values less than 1000 copies RNA/ml in more than 85% of patients was achieved only in three regions (33,3%). The conclusion was made concerning the necessity to implement the monitoring of HIV drug resistance in Russia as soon as possible, including an analysis of the EWIs and other types of monitoring studies.

Effects of dietary fluoranthene on nymphs of Blaptica dubia S. (Blattodea: Blaberidae).

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants which exert detrimental effects on living beings. Considering the health risk associated with exposure to these pollutants, their presence in food increases efforts to establish early-warning indicators of pollution. We aimed to examine the effects of environmentally relevant concentrations of fluoranthene (0.2ng and 18ng/g dry weight of diet) on the activities of midgut antioxidant and detoxification enzymes in Blaptica dubia. Significant changes of superoxide dismutase and catalase activities, recorded at the higher fluoranthene concentration regardless of the exposure time, suggest that they may be used as biomarkers of PAH pollution. Increased GST activity and decreased total GSH content, detected upon acute exposure to the lower concentration, indicate processes of detoxification. Reorganization of B. dubia mechanisms of defense in response to oxidative stress caused by exposure to dietary PAH point to the necessity for further examination of fluoranthene actions.

Evaluation of Early Warning Indicators (EWI) of HIV Drug Resistance According to the World Health Organization (WHO) in Some Treatment Centers in Kinshasa

Background: The Early Warning Indicators (EWI) of Human Immunodefi-ciency Virus (HIV) Drug Resistance measure factors found at the site level and known to be associated with the proper functioning of the program and the prevention of the emergence of R-ARV. The fact strengthening certain aspects of implementation of the program at the sites can help minimize the occurring of HIV Drug Resistance that can be prevented to improve the long-term effectiveness and sustainability of the treatment. Objective: The objective of this study was to assess the quality of the prevention of resistance of HIV Drug compared to EWI set by the World Health Organization (WHO) in the different Ambulatory Treatment Centers (ACT) in the city of Kinshasa. Methods: The present work was a retrospective survey conducted in 2015 in 7 ACTs in the 4 districts of Kinshasa in order to evaluate the EWI. Results: Seven (7) ATCs and 157 patient records were selected based on different inclusion criteria. The maintenance of first-line Antiretroviral Treatment (ART) at 12 months and the consistent delivery of ARVs were the two EWI that were respected, evaluation at 100%, for 6 ACTs. Conclusion: The caregivers and HIV-infected patients should be trained on the EWI and their monitoring to prevent the occurrence of treatment failures and that of HIV drug resistance in Kinshasa.

Early warning signals in plant disease outbreaks

Infectious disease outbreaks in plants threaten ecosystems, agricultural crops and food trade. Currently, several fungal diseases are affecting forests worldwide, posing a major risk to tree species, habitats and consequently ecosystem decay. Prediction and control of disease spread are difficult, mainly due to the complexity of the interaction between individual components involved. In this work, we introduce a lattice-based epidemic model coupled with a stochastic process that mimics, in a very simplified way, the interaction between the hosts and pathogen. We studied the disease spread by measuring the propagation velocity of the pathogen on the susceptible hosts. Our quantitative results indicate the occurrence of a critical transition between two stable phases: local confinement and an extended epiphytotic outbreak that depends on the density of the susceptible individuals. Quantitative predictions of epiphytotics are performed using the framework early-warning indicators for impending regime shifts, widely applied on dynamical systems. These signals forecast successfully the outcome of the critical shift between the two stable phases before the system enters the epiphytotic regime. Our study demonstrates that early-warning indicators could be useful for the prediction of forest disease epidemics through mathematical and computational models suited to more specific pathogen–host-environmental interactions. Our results may also be useful to identify a suitable planting density to slow down disease spread and in the future, design highly resilient forests.

Research and Application of RBF Neural Network-based Osmotic Pressure Forecast Model for Concrete-Faced Rockfill Dam

To realize real-time forecast and early-warning of osmotic pressure of concrete-faced rockfill dams, this research analyses factors that influence fluctuation of osmotic pressure and builds a statistical model for the osmotic pressure. A three-layer RBF neural network-based osmotic pressure forecast model for the concrete-faced rockfill dam is built with the 16 standardized variables as input-layer factors and the osmotic pressure as the output-layer factor. With 12 groups of actually-measured data from different sections of the dam as samples, this research analyses the fitting and forecast accuracy of the model via SPSS and the RBF neural network. In light of actual engineering demand, the model is applied to the 3D visual monitoring information system, and with the early-warning indicators determined, it can realize real-time monitoring.

Early warning indicator systems for real estate investments: Empirical evidence and some thoughts from the perspective of financial risk management

In recent years, early warning indicators and real estate—as an increasingly relevant asset class—have received more and more attention in German insurers’ investment strategies. Therefore, this paper examines the relationship of real estate sentiment data as leading indicators for housing activity and house price indices. However, we focus on empirical evidence from the US due to the quite limited data availability in Germany. The National Association of Home Builders (NAHB) housing market index is used as an indicator for US real estate prices and other variables related to housing activity and the S&P/Case-Shiller 20 city home price index for house prices in the US. In order to test for Granger causality among US house prices and the NAHB sentiment indictor we employ a modified Wald test based on Toda and Yamamoto (1995) examining an augmented vector autoregressive (VAR) model in levels. The results of our empirical investigations do show that there are clear signs for unidirectional Granger causality running from the NAHB housing market index to the S&P/Case-Shiller index. Therefore, the NAHB data seem to be quite helpful predicting US house prices. This empirical finding is of high relevance with regard to the construction of early warning indicator systems for real estate prices.

Early warning signals for critical transitions in cardiopulmonary health, related to air pollution in an urban Chinese population

Respiratory, and cardio-cerebrovascular health-related diseases significantly threaten human health and together with air pollution form a complex pathophysiological system. Other complex biological systems show that increased variance and autocorrelations in time series may act as valid early warning signals for critical transitions. On population level, we determined the likelihood that increased variance and autocorrelation of hospital visit on cardiopulmonary disease preceded critical transitions in population health by human-pollution interactions. We investigated long-term hospital visits from a hospital in Nanjing City, China during 2006–2016 for the most important cardiopulmonary diseases likely to be influenced by air pollution: cerebrovascular accident disease (CVAD), coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD), lung cancer disease (LCD), and the grouped categories of respiratory system disease (RESD) and cardio-cerebrovascular system disease (CCD). The time series of standard deviations (SDs) and autocorrelation at-lag-1 (AR-1) were studied as potential Early-Warning Indicators (EWIs) of transitions in population health. Elevated SDs provided an early warning for critical transitions in visit for LCD and overall CCD and CVAD, for the period of 2012–2013, after which a real transition of increased visit occurred for these disease categories. Statistical testing showed that these SDs were significantly increased (p < 0.1). The long-term air pollution together with intermittent pollution episodes may have triggered critical transitions in population health for cardiopulmonary disease. It is recommended to consider significant increases in variability in time series of relevant system parameters, such as visit, as early warning signs for future transitions in populations' health states.