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24. AgriFoodPy: a package for modelling food systems

Author

Cordero, Juan P., primary, Donkers, Kevin, additional, Harrison, Ian, additional, Bridle, Sarah L., additional, Frankowska, Angelina, additional, Cain, Michelle, additional, Ward, Neil, additional, Frendenburgh, Jez, additional, Pope, Edward, additional, Kluczkovski, Alana, additional, Schmidt, Ximena, additional, Silva, Jacqueline, additional, Reynolds, Christian, additional, Denby, Katherine, additional, Doherty, Bob, additional, and Jones, Aled, additional

Published
2024
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41. Continuous positive airway pressure versus standard care for the treatment of people with mild obstructive sleep apnoea (MERGE): a multicentre, randomised controlled trial

Author

Wimms, Alison J, Kelly, Julia L, Turnbull, Christopher D, McMillan, Alison, Craig, Sonya E, O'Reilly, John F, Nickol, Annabel H, West, Sophie D, Simonds, Anita K, Withana, Shirmila, Pepperell, Justin CT, Ward, Neil R, Kent, Brian D, Quinnell, Timothy, Paracha, Mohammad, Anderson, William, Hedley, Emma L, Decker, Meredith D, Willes, Leslee A, Calverley, Peter M A, Benjafield, Adam V, Stradling, John R, and Morrell, Mary J

Published
2020
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44. Scoping Potential Routes to UK Civil Unrest via the Food System: Results of a Structured Expert Elicitation

Author

Jones, Aled, primary, Bridle, Sarah, additional, Denby, Katherine, additional, Bhunnoo, Riaz, additional, Morton, Daniel, additional, Stanbrough, Lucy, additional, Coupe, Barnaby, additional, Pilley, Vanessa, additional, Benton, Tim, additional, Falloon, Pete, additional, Matthews, Tom K., additional, Hasnain, Saher, additional, Heslop-Harrison, John S., additional, Beard, Simon, additional, Pierce, Julie, additional, Pretty, Jules, additional, Zurek, Monika, additional, Johnstone, Alexandra, additional, Smith, Pete, additional, Gunn, Neil, additional, Watson, Molly, additional, Pope, Edward, additional, Tzachor, Asaf, additional, Douglas, Caitlin, additional, Reynolds, Christian, additional, Ward, Neil, additional, Fredenburgh, Jez, additional, Pettinger, Clare, additional, Quested, Tom, additional, Cordero, Juan Pablo, additional, Mitchell, Clive, additional, Bewick, Carrie, additional, Brown, Cameron, additional, Brown, Christopher, additional, Burgess, Paul J., additional, Challinor, Andy, additional, Cottrell, Andrew, additional, Crocker, Thomas, additional, George, Thomas, additional, Godfray, Charles J., additional, Hails, Rosie S., additional, Ingram, John, additional, Lang, Tim, additional, Lyon, Fergus, additional, Lusher, Simon, additional, MacMillan, Tom, additional, Newton, Sue, additional, Pearson, Simon, additional, Pritchard, Sue, additional, Sanders, Dale, additional, Sanderson Bellamy, Angelina, additional, Steven, Megan, additional, Trickett, Alastair, additional, Voysey, Andrew, additional, Watson, Christine, additional, Whitby, Darren, additional, and Whiteside, Kerry, additional

Published
2023
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45. Predictability of the East Africa long rains through Congo zonal winds.

Author

Ward, Neil, Walker, Dean P., Keane, Richard J., Marsham, John H., Scaife, Adam A., Birch, Cathryn E., and Maybee, Ben

Subjects
*ZONAL winds, *EXTREME weather, *NORTH Atlantic oscillation, *RAINFALL, *DROUGHTS, *DYNAMICAL systems
Abstract

East Africa is highly vulnerable to extreme weather events, such as droughts and floods. Skillful seasonal forecasts exist for the October–November–December short rains, enabling informed decisions, whereas seasonal forecasts for the March–April–May (MAM) long rains have historically had low skill, limiting preparation capacity. Therefore, improved long rains prediction is a high priority and would contribute to climate change resilience in the region. Recent work has highlighted how lower‐troposphere Congo zonal winds in MAM strongly impact regional moisture fluxes and the long rains total precipitation. We therefore approach long rains predictability through the predictability of the Congo winds. We analyze a set of hindcasts from a dynamical prediction system that is able to reproduce the long rains—Congo winds relationship in its individual ensemble members. Encouragingly, in observations, the strength of MAM Congo zonal winds and East Africa rainfall show substantial correlation with the MAM Atlantic (including North Atlantic Oscillation, NAO) and Indo‐Pacific variability, suggestive of ocean influence and potential predictability. However, these features are replaced by different teleconnections in the hindcast ensemble mean fields. This is also true for NAO linkage to Congo winds, despite correct representation in individual members, and good skill in hindcasting the NAO itself. The net effect is strongly negative skill for the Congo winds. We explore statistical correction methods, including using the Congo zonal wind as an anchor index in a signal‐to‐noise calibration for the long rains. This is considered a demonstration of concept, for subsequent implementation using models with better Congo zonal wind skill. Indeed, the clear signals found in the Atlantic (including Mediterranean) and Indo‐Pacific, studied here both in observations and a dynamical prediction system, motivate evaluation of these features across other prediction systems, and offer the prospect of improved physically‐informed long rains dynamical predictions. [ABSTRACT FROM AUTHOR]

Published
2023
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46. Diagnosis of sleep-disordered breathing in chronic heart failure

Author

Ward, Neil Robert, Morrell, Mary, Simonds, Anita, and Cowie, Martin

Subjects
616.129075
Abstract

Sleep-disordered breathing (SDB) is prevalent but underdiagnosed in chronic heart failure (CHF). The aim of this thesis was to investigate the utility of simple portable monitoring and clinical features to identify CHF patients with SDB. In addition, the influence of scoring criteria on diagnosis and classification of SDB in CHF was investigated. In the first study, clinical characteristics in CHF patients with SDB were compared to those without SDB. No specific symptom, anthropometric characteristic or measure of heart failure severity was reliably able to identify CHF patients with SDB. In the second study, the accuracy of heart rate variability (HRV) analysis and overnight pulse oximetry for diagnosis of SDB in CHF were investigated. The percent very low frequency increment (%VLFI) of HRV had low accuracy for diagnosis of SDB. In contrast, the >3% oxygen desaturation index measured by pulse oximetry had a high diagnostic accuracy, with sensitivity 0.97 and negative likelihood ratio 0.08 at a prespecified cutoff of >7.5 desaturations per hour. In the third study, the impact of hypopnoea scoring criteria on SDB diagnosis in CHF was evaluated. The prevalence of SDB changed significantly from 29% when hypopnoeas were scored with a corroborative ≥4% oxygen desaturation, to 46% when hypopnoeas were scored with a corroborative ≥3% oxygen desaturation or arousal from sleep (p<0.001). Respiratory event scoring criteria did not influence the classification of SDB as obstructive or central sleep apnoea. In summary, this thesis has shown that clinical features and HRV analysis can not be used to identify CHF patients with SDB. Overnight pulse oximetry has a high diagnostic accuracy and would be of greatest clinical use to rule out SDB in patients with CHF. The criteria used to score respiratory events during sleep studies can have a significant impact on the diagnosis and prevalence of SDB in CHF.

Published
2012
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