Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

Interannual climate variability associated with the El Niño/Southern Oscillation (ENSO) phenomenon and regional climatic circulation mechanisms in the equatorial Indian Ocean result in significant rainfall and ecological anomaly patterns that are major drivers of spatial and temporal patterns of mosquito-borne disease outbreaks. Correlation and regression analyses of long time series rainfall, vegetation index, and temperature data show that large scale anomalies occur periodically that may influence mosquito vector populations and thus spatial and temporal patterns of Rift Valley fever and chikungunya outbreaks. Rift Valley fever outbreak events occurred after a period of ∼3–4 months of persistent and above-normal rainfall that enabled vector habitats to flourish. On the other hand, chikungunya outbreaks occurred during periods of high temperatures and severe drought over East Africa and the western Indian Ocean islands. This is consistent with highly populated environmental settings where domestic and peri-domestic stored water containers were the likely mosquito sources. However, in Southeast Asia, approximately 52% of chikungunya outbreaks occurred during cooler-than-normal temperatures and were significantly negatively correlated with drought. Besides climate variability, other factors not accounted for such as vertebrate host immunity may contribute to spatio-temporal patterns of outbreaks

Land cover change in the Bolivian Amazon and its implications for REDD+ and endemic biodiversity

Tropical deforestation is a major contributor to green house gas emissions in developing countries. Incentive mechanisms, such as reducing emissions from deforestation and forest degradation (REDD), are currently being considered as a possible emissions reduction and offset solution. Although REDD has expanded its scope to include co-benefits such as sustainable management of forests and biodiversity conservation (known as REDD+), current carbon-base methodologies do not specifically target projects for the parallel protection of these co-benefits. This study demonstrates the incorporation of both carbon and biodiversity benefits within REDD+ in the Bolivian Amazon, through the analysis of land cover change and future change scenario modeling to the year 2050. Current protected areas within the Bolivian Amazon were evaluated for REDD+ project potential by identifying concordant patterns of carbon content, species biodiversity and deforestation vulnerability. Biodiversity-based versus carbon-based protection schemes were evaluated and protected areas were prioritized using irreplaceability-vulnerability plots. Deforestation projection scenarios to the year 2050 varied depending on the historical period analyzed, producing low, intermediate and high deforestation scenarios. All scenarios showed increasing deforestation pressure in the northern region of Bolivia along with high levels of biodiversity loss. Expected reductions in the carbon pool ranged from 8 to 48%, for the low and high demand scenarios respectively. Some protected areas presented large numbers of endemic species, high concentrations of carbon and high deforestation vulnerability, demonstrating the potential for win-win REDD+ projects in Bolivia. © 2012 Springer Science+Business Media B.V

Incorporating anthropogenic variables into a species distribution model to map gypsy moth risk

This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities. © 2007 Elsevier B.V. All rights reserved

Clinical response beyond the systemic lupus erythematosus responder index: Post-hoc analysis of the BLISS-SC study

Objective The Systemic Lupus Erythematosus (SLE) Responder Index (SRI), developed as a primary outcome measure for use in clinical trials, captures improvement in SLE disease activity without concomitant worsening in disease manifestations. This study investigated the relationships between the SRI and clinical/laboratory correlates of SRI response in patients with SLE. Methods This was a post-hoc analysis of the phase III, double-blind, placebo-controlled study of subcutaneous BeLimumab in Subjects with Systemic lupus erythematosus-SubCutaneous (BLISS-SC). Patients were randomised to weekly belimumab 200 mg subcutaneously or placebo, plus standard SLE therapy. Changes from baseline to week 52 in clinical and laboratory parameters were compared among SRI responders and non-responders, irrespective of the treatment received. Results SRI responders (n=475) had significantly better (p7.5mg/day corticosteroids at baseline, significantly more SRI responders had reductions in prednisone dose to ≤7.5 mg/day than non-responders. SRI responders reported lower flare rates and improvements in serological markers and Functional Assessment of Chronic Illness Therapy-Fatigue score than non-responders. Conclusion SRI response is associated with improvements in clinical and laboratory measures, strengthening its value as a clinically meaningful primary endpoint in clinical trials

Cumulative rainfall anomalies and vegetation index anomalies for East Africa, Sudan and Southern Africa.

<p>Patterns of rainfall anomalies preceding outbreaks of Rift Valley fever in (A) East Africa: September–December, 2006, (C) Sudan: June–September, 2007, and (E) Southern Africa: October, 2007–January, 2008. Each outbreak was preceded by persistent and above-normal rain on the order of +200 mm for a period of ∼2–4 months (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0001465#pntd.0001465.s003" target="_blank">Fig. S2</a>). This resulted in anomalous green-up of vegetation, creating ideal ecological conditions for the production of <i>Aedes</i> and <i>Culex</i> mosquito vectors that transmit Rift Valley fever virus to domestic animals and humans. Vegetation anomalies are shown for (B) East Africa: October, 2006–January 2007, (D) Sudan: July–September, 2007, and (F) Southern Africa: October, 2007–January, 2008. Rift Valley fever outbreaks are marked with yellow dots.</p

Summary correlation map between monthly NINO3.4 SST and rainfall anomalies, 1979–2008.

<p>Correlation of sea surface temperatures and rainfall anomalies illustrate ENSO teleconnection patterns. There is a tendency for above (below) normal rainfall during <i>El Niño</i> (<i>La Niña</i>) events over East Africa (Southern Africa, Southeast Asia). Similar differential anomaly patterns were observed for other regions, especially within the global tropics. These extremes (above or below) in rainfall influence regional ecology and consequently dynamics of mosquito disease vector populations and patterns of mosquito-borne disease outbreaks.</p