Seasonal Variability of Carbon Dioxide in the Rivers and Lagoons of Ivory Coast (West Africa)

peer reviewedWe report partial pressure of CO2 (pCO2) and ancillary data in three rivers (Bia, Tanoé, and Comoé) and five lagoons (Tendo, Aby, Ebrié, Potou, and Grand-Lahou) in Ivory Coast (West Africa), during four cruises covering the main climatic seasons. The three rivers were oversaturated in CO2 with respect to atmospheric equilibrium, and the seasonal variability of pCO2 was due to dilution during the flooding period. Surface waters of the Potou, Ebrié, and Grand-Lahou lagoons were oversaturated in CO2 during all seasons. These lagoons behaved similarly to the oligohaline regions of macrotidal estuaries that are CO2 sources to the atmosphere due to net ecosystem heterotrophy and inputs of riverine CO2 rich waters. The Aby and Tendo lagoons were undersaturated in CO2 with respect to the atmosphere because of their permanent haline stratification (unlike the other lagoons) that seemed to lead to higher phytoplankton production and export of organic carbon below the pycnocline

Developing credible vulnerability indicators for climate adaptation policy assessment

We address the issue of how to develop credible indicators of vulnerability to climate change that can be used to guide the development of adaptation policies. We compare the indicators and measures that five past national-level studies have used and examine how and why their approaches have differed. Other relevant indicator studies of social facets of society as well as vulnerability studies at sub-national level are also examined for lessons regarding best practice. We find that the five studies generally emphasise descriptive measures by aggregating environmental and social conditions. However, they vary greatly both in the types of indicators and measures used and differ substantially in their identification of the most vulnerable countries. Further analysis of scientific approaches underlying indicator selection suggests that the policy relevance of national-level indicators can be enhanced by capturing the processes that shape vulnerability rather than trying to aggregate the state itself. Such a focus can guide the selection of indicators that are representative even when vulnerability varies over time or space. We find that conceptualisation regarding how specific factors and processes influencing vulnerability interact is neither given sufficient consideration nor are assumptions transparently defined in previous studies. Verification has been neglected, yet this process is important both to assess the credibility of any set of measures and to improve our understanding of vulnerability. A fundamental lesson that emerges is the need to enhance our understanding of the causes of vulnerability in order to develop indicators that can effectively aid policy development

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran