Search

Background: Long acting injectable (LAI) antipsychotics have been claimed to ensure treatment adherence and possibly reduce the daily burden of oral formulations. So far, only surveys investigating the theoretical prescribing attitudes of clinicians have been employed. On this basis, we aimed to investigate reasons for prescribing LAIs in a real-world, unselected sample of patients. Methods: The STAR Network Depot Study is an observational, multicentre study consecutively enrolling adults initiating a LAI over a 12-months period. Clinical severity was assessed with the Brief Psychiatric Rating Scale, and patient’s attitude toward medications with the Drug Attitude Inventory 10 items. Psychiatrists recorded reasons for LAI prescribing for each study participant. Responses were grouped into six non-mutually exclusive categories: aggressiveness, patient engagement, ease of drug taking, side-effects, stigma, adherence. Results: Of the 451 patients included, two-thirds suffered from chronic psychoses. Improving patient engagement with the outpatient psychiatric service was the most common reason for prescribing LAIs (almost 80% of participants), followed by increasing treatment adherence (57%), decreasing aggressiveness (54%), and improving ease of drug taking (52%). After adjusting for confounders, logistic regression analyses showed that reasons for LAI use were associated with LAI choice (e.g. first-generation LAIs for reducing aggressiveness). Conclusion: Despite the wide availability of novel LAI formulation and the emphasis on their wider use, our data suggest that the main reasons for LAI use have remained substantially unchanged over the years, focusing mostly on improving patient’s engagement. Further, clinicians follow implicit prescribing patterns when choosing LAIs, and this may generate hypotheses for future experimental studies.

Purpose of Review: Knowledge of how monsoons will respond to external forcings through the twenty-first century has been confounded by incomplete theories of tropical climate and insufficient representation in climate models. This review highlights recent insights from past warm climates and historical trends that can inform our understanding of monsoon evolution in the context of an emerging energetic framework. Recent Findings: Projections consistent with paleoclimate evidence and theory indicate expanded/wetter monsoons in Africa and Asia, with continued uncertainty in the Americas. Twentieth century observations are not congruent with expectations of monsoon responses to radiative forcing from greenhouse gases, due to the confounding effect of aerosols. Lines of evidence from warm climate analogues indicate that while monsoons respond in globally coherent and predictable ways to orbital forcing and inter-hemispheric thermal gradients, there are differences in response to these forcings and also between land and ocean. Summary: Further understanding of monsoon responses to climate change will require refinement of the energetic framework to incorporate zonal asymmetries and the use of model hierarchies.

We combine socioeconomic data from a large‐scale household survey with historical climate data to map the climate sensitivity of availability and access dimensions of food security in Mali, and infer the ways in which at‐risk communities may have been impacted by persistent climatic shift. Thirty years after 1982–1984, the period of most intense drought during the protracted late 20th century drying of the Sahel, the impact of drought on livelihoods and food security is still recognizable in the Sahelian center of Mali. This impact is expressed in the larger fraction of households in this Sahelian center of the country—the agro‐ecological transition between pastoralism in the north, and sedentary agriculture in the south—who practice agriculture but not livestock raising, despite environmental conditions that are suitable to their combination. These households have lower food security and rely more frequently on detrimental nutrition‐based coping strategies, such as reducing the quantity or quality of meals. In contrast, the more food secure households show a clear tendency toward livelihood diversification away from subsistence agriculture. These households produce less of what they consume, yet spend less on food in proportion. The analysis points to the value of interdisciplinary research—in this case bridging climate science and vulnerability analysis—to gain a dynamical understanding of complex systems, understanding which may be exploited to address real‐world challenges, offering lessons about food security and local adaptation strategies in places among the most vulnerable to climate.

The unusual severity and return time of the 2005 and 2010 dry-season droughts in western Amazon is attributed partly to decadal climate fluctuations and a modest drying trend. Decadal variability of western Amazon hydroclimate is highly correlated to the Atlantic sea surface temperature (SST) north-south gradient (NSG). Shifts of dry and wet events frequencies are also related to the NSG phase, with a 66% chance of 3+ years of dry events per decade when NSG > 0 and 19% when NSG

Twenty-first century climate model projections show an amplification of the annual cycle in tropical precipitation with increased strength in both wet and dry seasons, but uncertainty is large and few studies have examined transition seasons. Here we analyze coupled climate model projections of global land monsoons and show a redistribution of precipitation from spring to summer in northern (North America, West Africa and Southeast Asia) and southern (South America, Southern Africa) regions. The annual cycle changes are global in scale. Two mechanisms, remote (based on tropospheric stability) and local (based on low level and surface moisture), are evaluated through the annual cycle. Increases in tropospheric stability persist from winter into spring and are reinforced by a reduction in surface moisture conditions, suggesting that in spring both remote and local mechanisms act to inhibit convection. This enhanced spring convective barrier leads to reduced early season rainfall; however, once sufficient increases in moisture (by transport) are achieved, decreases in tropospheric stability result in increased precipitation during the late rainy season. Further examination of this mechanism is needed in observations and models, as the projected changes would have substantial implications for agriculture, water management, and disaster preparedness.

This report documents the process and results of the index insurance design effort leading to the index insurance contracts for Adi Ha in 2009. This report represents deliverables 1 and 2 in the terms of reference with Oxfam America, it outlines and compares analysis and design methodologies including the performance of rainfall simulators for index-based contract design. It also details contracts, methodologies, associated issues, and important lessons learned. A separate project report details the Experimental Games, deliverable 3 in the terms of reference.

This report is one of the deliverables for the project "Commodity Risk Management Group (ARD) seeks a qualified firm for Designing Index-Based Weather Insurance Contracts For Farmers in Central America, Terms of Reference." In this report, we document the development of eleven revised and improved standardized drought contracts, including six contracts specified in the World Bank's Commodity Risk Management Group's Terms of Reference for this project. Contracts are developed for three locations in Nicaragua (Chinandega, Leon, and Managua) for rice, soy, and sorghum crops and three locations in Honduras (La Conce, Catacamas, and Guayabillas/Olancho) for sorghum, soy, and maize crops. We provide background on the contract structure and design methods used. The final standardized drought contracts perform very well in our statistical analysis using crop models, likely due to the strong potential represented by the initial contracts proposed by project partners. In this report we provide a detailed report and discussion of the contracts and the refinement process. Of course, it is important that project partners make sure to validate this performance through alternate sources of information, such as discussions with farmers, experts, and accurate historical yield data, when available. For the future, for standardization of the process, it could be worthwhile to make a more systematic process for quantitatively evaluating and tuning the contracts for additional risks (such as excess rainfall) based on farmer interviews and agronomic knowledge. Specifically we recommend evaluating each risk of the contract independently prior to bundling. We also recommend development of a process for documentation of farmer and expert interviews that would provide information on the risk, as well as a historical record of when each risk was an issue. More intimate inclusion of Reinsurers in the design process for standardized contracts, as well as development of guidelines for features that may lead to additional expense could help provide for fewer surprises in reinsurance pricing. We also recommend that the contracts for additional risks be structured and designed so that they can be adjusted to meet price, payout, and coverage constraints through systematic statistically-based tuning of a small number of parameters. In response to queries raised during the project by project partners we have deepened our study of the climate of Central America and its implications for the forecasts, we find that although there appears to be a strong link between the natural ENSO climate cycle and contract payouts, there is probably little scope for geographical hedging, as crops covered do not span the geographic regions with negatively correlated rainfall. It is likely that the best hedging strategy would be to include excess contracts in the drought portfolio. Also, we see little evidence for altering contracts or pricing to address potential long term precipitation trends in the near term. Given the strong potential for index insurance as a mechanism for adapting to climate risk, we highly recommend that products and prices be regularly updated over the years, with care to ensure the value and product continuity with each change. In response to queries raised during the project by project partners, we perform an in depth illustration and analysis of the use of rainfall simulators on the contracts. We illustrate the limitations of rainfall simulators as well as their potential for improving contract design and pricing for areas with short datasets, developing rainfall simulator for the analysis. Certain features of some contracts (the shifting sowing window) led a wide range of rainfall simulators to under-represent variability. Often, subtle contract features can lead to a lack of robustness to sensitivity tests and difficulty in analysis, and potentially could lead to increased reinsurance pricing without substantially adding to the quality of the coverage. We have noticed that the bulk of the protection of many of the contracts could be provided through much simpler indices that are much more robust to sensitivity tests and perform much more predictably on rainfall simulators when practically implementable. It may be that an additional stage of index design might be very valuable following the development of a sophisticated contract. This additional stage would be to determine if the bulk of the coverage of the contract could be duplicated in a simplified statistical approximation of the contract.

Downscaling is the term used to describe the various methods used to translate the climate projections from coarse resolution GCMs to finer resolutions deemed more useful for assessing impacts. Projections of future climate are produced using complex, coupled atmosphere-ocean models (GCMs). The GCMs are most reliable at the continental scale. Due to the inherent uncertainty of the climate system and the inevitable existence of model errors, multi-model ensembling is the recommended approach for characterizing expected climate changes. As downscaling is dependent on the ability of GCMs to successfully project the climate change signal, it is limited to where that signal is clear. Assessments of climate change in Africa indicate some consensus of reduced winter rainfall in southern Africa, increased annual rainfall in east Africa and uncertainty for the rest of Africa. Selection of GCMs that "do better" over Africa, or any region, is difficult and probably not warranted, given the general parity in model skill and the difficulty in identifying which models are more skillful. Ensemble means or medians offer the highest level of projection accuracy. Downscaling approaches are generally categorized as dynamical, using regional climate models, and statistical, using empirical relationships. However, dynamical downscaling often includes statistical modeling in the form of "bias correction." Dynamical downscaling is useful for incorporating topographic features, such as strong orography, and land use and vegetation. It is recommended where those features play a significant role in regional climate. However, computational time and the uncertainties that accompany complex models outweigh the benefits of dynamical downscaling where these features are not significant. The spatial resolution that can be achieved is on the order of tens of kilometers. Statistical downscaling is simpler and more efficient than dynamical downscaling. It is preferred where estimates of specific variables, especially at point locations, are sought for input to sector models (e.g., hydrologic models) or decision making. However, statistical modeling can mask a true understanding of regional climate dynamics and estimates may be overconfident. In summary, downscaling is best understood as an attempt to increase the understanding of climate change influences at the regional scale. In that context, a variety of methodologies should be explored, using all tools possible to increase that understanding. A set of "Best Practices" is recommended for pursuing this effort.

An overview of the connection between climate and meningitis in the West African Sahel.