The development of an early warning system to detect trends in illicit drug use in Australia: The illicit drug reporting-system

Appropriate ways to monitor the availability and use of illicit drugs were examined. Four methods were tested concurrently: (1) a quantitative survey of injecting drug users, (2) a qualitative key informant study of illicit drug users and professionals working in the drug field, (3) examination of existing sources of survey, health and law enforcement data and (4) an ethnographic study of a high risk group of illicit drug users. The first three methods were recommended for inclusion in an ongoing national monitoring system, enabling the collection of both quantitative and qualitative data on a range of illicit drugs in a relatively brief, quick and cost-effective manner. A degree of convergent validity was also noted among these methods, improving the degree of confidence in drug trends. The importance of injecting drug users as a sentinel population of illicit drug users was highlighted, along with optimal methods for qualitative research.

Predictors of local malaria outbreaks: an approach to the development of an early warning system in Colombia

Risk factor surveillance is a complementary tool of morbidity and mortality surveillance that improves the likelihood that public health interventions are implemented in a timely fashion. The aim of this study was to identify population predictors of malaria outbreaks in endemic municipalities of Colombia with the goal of developing an early warning system for malaria outbreaks. We conducted a multiple-group, exploratory, ecological study at the municipal level. Each of the 290 municipalities with endemic malaria that we studied was classified according to the presence or absence of outbreaks. The measurement of variables was based on historic registries and logistic regression was performed to analyse the data. Altitude above sea level [odds ratio (OR) 3.65, 95% confidence interval (CI) 1.34-9.98], variability in rainfall (OR 1.85, 95% CI 1.40-2.44) and the proportion of inhabitants over 45 years of age (OR 0.17, 95% CI 0.08-0.38) were factors associated with malaria outbreaks in Colombian municipalities. The results suggest that environmental and demographic factors could have a significant ability to predict malaria outbreaks on the municipal level in Colombia. To advance the development of an early warning system, it will be necessary to adjust and standardise the collection of required data and to evaluate the accuracy of the forecast models.

The First International Workshop on Warning Criteria for Active Slides: technical issues, problems and solutions for managing early warning systems

Early warning systems (EWSs) rely on the capacity to forecast a dangerous event with a certain amount of advance by defining warning criteria on which the safety of the population will depend. Monitoring of landslides is facilitated by new technologies, decreasing prices and easier data processing. At the same time, predicting the onset of a rapid failure or the sudden transition from slow to rapid failure and subsequent collapse, and its consequences is challenging for scientists that must deal with uncertainties and have limited tools to do so. Furthermore, EWS and warning criteria are becoming more and more a subject of concern between technical experts, researchers, stakeholders and decision makers responsible for the activation, enforcement and approval of civil protection actions. EWSs imply also a sharing of responsibilities which is often averted by technical staff, managers of technical offices and governing institutions. We organized the First International Workshop on Warning Criteria for Active Slides (IWWCAS) to promote sharing and networking among members from specialized institutions and relevant experts of EWS. In this paper, we summarize the event to stimulate discussion and collaboration between organizations dealing with the complex task of managing hazard and risk related to active slides.

The scrutiny of the principle of subsidiarity by autonomous regional parliaments with particular reference to the participation of the Parliament of Catalonia in the early warning system

The purpose of this article is to offer a practical approach to the new European dimension for regional parliaments signified by the entry into force of the Treaty of Lisbon. The parliamentary scrutiny of subsidiarity by way of the early warning system has assigned a new mission to legislative assemblies with the aim of reinforcing the intervention of regions in the drafting of policies by Union institutions. In the Spanish case, the institutionalisation of this mechanism came about with Act nº 24/2009, which attributes to the Joint Committee for the European Union, in the name of the Cortes Generales [the Spanish Parliament], the function of receiving the proposals for legislative acts by the EU and transferring them to the regional parliaments in order for the latter to issue, in a brief period of four weeks, a report on compliance with the principle of subsidiarity. The majority of regional parliaments have also carried out normative reforms to regulate the procedure of participation in the early warning system.

Could the Asian Crisis Have Been More Accurately Predicted? Improving and Early Warning System Model.

Rapport de recherche

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

Early warning with calibrated and sharper probabilistic forecasts

Given a nonlinear model, a probabilistic forecast may be obtained by Monte Carlo simulations. At a given forecast horizon, Monte Carlo simulations yield sets of discrete forecasts, which can be converted to density forecasts. The resulting density forecasts will inevitably be downgraded by model mis-specification. In order to enhance the quality of the density forecasts, one can mix them with the unconditional density. This paper examines the value of combining conditional density forecasts with the unconditional density. The findings have positive implications for issuing early warnings in different disciplines including economics and meteorology, but UK inflation forecasts are considered as an example.

Statistical monitoring of student performance: an early warning system

Weekly monitoring of profiles of student performances on formative and summative coursework throughout the year can be used to quickly identify those who need additional help, possibly due to acute and sudden-onset problems. Such an early-warning system can help retention, but also assist students in overcoming problems early on, thus helping them fulfil their potential in the long run. We have developed a simple approach for the automatic monitoring of student mark profiles for individual modules, which we intend to trial in the near future. Its ease of implementation means that it can be used for very large cohorts with little additional effort when marks are already collected and recorded on a spreadsheet.

Towards global drought early warning capability: expanding international cooperation for the development of a framework for global drought monitoring and forecasting

Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.

Building climate resilience: lessons of early warning in Africa

Given the high levels of uncertainty and substantial variability in local weather and climate, what constitutes successful adaptation for the 800 million food-insecure people in Africa? In this context there is a need for building climate resilience through effective early warning systems, bringing real-time monitoring and decision-making together with stakeholders. The chapter presents two effective operational early warning systems in Africa: The Radio and Internet (RANET) network and the Rainwatch project. These examples were developed in partnership with local climate scientists and tailored to local development needs, enabled and encouraged with only modest international support. They deliver important lessons about how to prepare for crises using simple real-time monitoring. They also help us identify characteristics of managing for resilience in practice. The chapter concludes that successful adaptation requires adaptive, flexible, linked institutions, together with ground-based collaboration and practical tools. In the context of early warning three features stand out that make these systems successful: effective communication of current weather and climate information, a key individual within a bridging organization with the ability to navigate the governance systems, and sufficient time for innovation development.

Science for Humanitarian Emergencies and Resilience (SHEAR) scoping study: Annex 3 - Early warning system and risk assessment case studies

This report provides case studies of Early Warning Systems (EWSs) and risk assessments encompassing three main hazard types: drought; flood and cyclone. The case studies are taken from ten countries across three continents (focusing on Africa, South Asia and the Caribbean). The case studies have been developed to assist the UK Department for International Development (DFID) to prioritise areas for Early Warning System (EWS) related research under their ‘Science for Humanitarian Emergencies and Resilience’ (SHEAR) programme. The aim of these case studies is to ensure that DFID SHEAR research is informed by the views of Non-Governmental Organisations (NGOs) and communities engaged with Early Warning Systems and risk assessments (including community-based Early Warning Systems). The case studies highlight a number of challenges facing Early Warning Systems (EWSs). These challenges relate to financing; integration; responsibilities; community interpretation; politics; dissemination; accuracy; capacity and focus. The case studies summarise a number of priority areas for EWS related research: • Priority 1: Contextualising and localising early warning information • Priority 2: Climate proofing current EWSs • Priority 3: How best to sustain effective EWSs between hazard events? • Priority 4: Optimising the dissemination of risk and warning information • Priority 5: Governance and financing of EWSs • Priority 6: How to support EWSs under challenging circumstances • Priority 7: Improving EWSs through monitoring and evaluating the impact and effectiveness of those systems