Browsing by Author "Jeuland, Marc"

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    Aligning evidence generation and use across health, development, and environment
    Tallis, Heather; Kreis, Katharine; Olander, Lydia P.; Ringler, Claudia; Ameyaw, David; Borsuk, Mark E.; Fletschner, Diana; Game, Edward; Gilligan, Daniel O.; Jeuland, Marc; Kennedy, Gina; Masuda, Yuta J.; Mehta, Sumi; Miller, Nicholas; Parker, Megan; Pollino, Carmel; Rajaratnam, Julie; Wilkie, David; Zhang, Wei; Ahmed, Selena; Ajayi, Oluyede C.; Alderman, Harold; Arhonditsis, George; Azevedo, Ines; Badola, Ruchi; Bailis, Rob; Balvanera, Patricia; Barbour, Emily; Bardini, Mark; Barton, David N.; Baumgartner, Jill; Benton, Tim G.; Bobrow, Emily; Bossio, Deborah; Bostrom, Ann; Braimoh, Ademola; Brondizio, Eduardo; Brown, Joe; Bryant, Benjamin P.; Calder, Ryan S. D.; Chaplin-Kramer, Becky; Cullen, Alison; DeMello, Nicole; Dickinson, Katherine L.; Ebi, Kristie L.; Eves, Heather E.; Fanzo, Jessica; Ferraro, Paul J.; Fisher, Brendan; Frongillo, Edward A.; Galford, Gillian; Garrity, Dennis; Gatere, Lydiah; Grieshop, Andrew P.; Grigg, Nicola J.; Groves, Craig; Gugerty, Mary Kay; Hamm, Michael; Hou, Xiaoyue; Huang, Cindy; Imhoff, Marc; Jack, Darby; Jones, Andrew D.; Kelsey, Rodd; Kothari, Monica; Kumar, Ritesh; Lachat, Carl; Larsen, Ashley E.; Lawrence, Mark; DeClerck, Fabrice; Levin, Phillip S.; Mabaya, Edward; Gibson, Jacqueline MacDonald; McDonald, Robert; Mace, Georgina; Maertens, Ricardo; Mangale, Dorothy; Martino, Robin; Mason, Sara A.; Mehta, Lyla; Meinzen-Dick, Ruth; Merz, Barbara; Msangi, Siwa; Murray, Grant; Murray, Kris A.; Naude, Celeste E.; Newlands, Nathaniel K.; Nkonya, Ephraim; Peterman, Amber; Petruney, Tricia; Possingham, Hugh; Puri, Jyotsna; Remans, Roseline; Remlinger, Lisa; Ricketts, Taylor H.; Reta, Bedilu; Robinson, Brian E.; Roe, Dilys; Rosenthal, Joshua; Shen, Guofeng; Shindell, Drew; Stewart-Koster, Ben; Sunderland, Terry; Sutherland, William J.; Tewksbury, Joshua; Wasser, Heather; Wear, Stephanie; Webb, Chris; Whittington, Dale; Wilkerson, Marit; Wittmer, Heidi; Wood, Benjamin DK K.; Wood, Stephen; Wu, Joyce; Yadama, Gautam; Zobrist, Stephanie (Elsevier, 2019-08-01)
    Although health, development, and environment challenges are interconnected, evidence remains fractured across sectors due to methodological and conceptual differences in research and practice. Aligned methods are needed to support Sustainable Development Goal advances and similar agendas. The Bridge Collaborative, an emergent research-practice collaboration, presents principles and recommendations that help harmonize methods for evidence generation and use. Recommendations were generated in the context of designing and evaluating evidence of impact for interventions related to five global challenges (stabilizing the global climate, making food production sustainable, decreasing air pollution and respiratory disease, improving sanitation and water security, and solving hunger and malnutrition) and serve as a starting point for further iteration and testing in a broader set of contexts and disciplines. We adopted six principles and emphasize three methodological recommendations: (1) creation of compatible results chains, (2) consideration of all relevant types of evidence, and (3) evaluation of strength of evidence using a unified rubric. We provide detailed suggestions for how these recommendations can be applied in practice, streamlining efforts to apply multi-objective approaches and/or synthesize evidence in multidisciplinary or transdisciplinary teams. These recommendations advance the necessary process of reconciling existing evidence standards in health, development, and environment, and initiate a common basis for integrated evidence generation and use in research, practice, and policy design.
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    COVID-19 Reveals Vulnerabilities of the Food–Energy–Water Nexus to Viral Pandemics
    Calder, Ryan S. D.; Grady, Caitlin; Jeuland, Marc; Kirchhoff, Christine J.; Hale, Rebecca L.; Muenich, Rebecca L. (American Chemical Society, 2021)
    Food, energy, and water (FEW) sectors are inextricably linked, making one sector vulnerable to disruptions in another. Interactions between FEW systems, viral pandemics, and human health have not been widely studied. We mined scientific and news/media articles for causal relations among FEW and COVID-19 variables and qualitatively characterized system dynamics. Food systems promoted the emergence and spread of COVID-19, leading to illness and death. Major supply-side breakdowns were avoided (likely due to low morbidity/mortality among working-age people). However, COVID-19 and physical distancing disrupted labor and capital inputs and stressed supply chains, while creating economic insecurity among the already vulnerable poor. This led to demand-side FEW insecurities, in turn increasing susceptibility to COVID-19 among people with many comorbidities. COVID-19 revealed trade-offs such as allocation of water to hygiene versus to food production and disease burden avoided by physical distancing versus disease burden from increased FEW insecurities. News/media articles suggest great public interest in FEW insecurities triggered by COVID-19 interventions among individuals with low COVID-19 case-fatality rates. There is virtually no quantitative analysis of any of these trade-offs or feedbacks. Enhanced quantitative FEW and health models are urgently needed as future pandemics are likely and may have greater morbidity and mortality than COVID-19.
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    Graphical models and the challenge of evidence-based practice in development and sustainability
    Calder, Ryan S. D.; Alatorre, Andrea; Marx, Rebecca S.; Mallampalli, Varun; Mason, Sara A.; Olander, Lydia P.; Jeuland, Marc; Borsuk, Mark E. (Elsevier, 2020-08-01)
    Governments and social benefit organizations are expected to consider evidence in decision-making. In development and sustainability, evidence spans disciplines and methodological traditions and is often inconclusive. Graphical models are widely promoted to organize interdisciplinary evidence and improve decision-making by considering mediating variables. However, the reproducibility, objectivity and benefits for decision-making of graphical models have not been studied. We evaluate these considerations in the setting of energy services in the developing world, a contemporary development and sustainability imperative. We develop a database of relevant causal relations (313 concepts, 1337 relationships) asserted in the literature (561 peer-reviewed articles). We demonstrate that high-level relationships of interest to practitioners feature less consistent evidence than the causal relationships that underpin them, supporting increased use of problem decomposition through graphical modeling approaches. However, adding such detail increases complexity exponentially, introducing a hazard of overparameterization if evidence is not available to match the level of mechanistic detail.
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    Increasing resiliency of integrated food-energy-water systems to viral pandemics: lessons from COVID-19
    Calder, Ryan S. D.; Grady, Caitlin; Jeuland, Marc; Kirchhoff, Christine J.; Rodgers, Samuel; Hale, Rebecca L.; Muenich, Rebecca L. (2021-12-15)
    COVID-19 disrupted labor and capital inputs to interdependent food, energy, and water (FEW) systems. We demonstrate how graphical modeling of phenomena realized during COVID-19 can reveal dynamics of FEW systems during viral pandemics. For example, physical distancing slowed COVID-19 spread but led to economic disruption and may have increased COVID-19 susceptibility by exacerbating FEW insecurities among individuals with many comorbidities. We review predictions of pandemic impacts on FEW systems and identify the mechanisms that explain divergences with respect to observed outcomes during the COVID-19 pandemic. For example, supply-side breakdowns were averted, likely due to low morbidity and mortality among working-age people and net declines in overall energy demand. Modern food systems promote viral emergence, and future pandemics are likely to differ from COVID-19 with respect to one or more key variables such as age-specific mortality or viral infectivity. We use the case study of the poultry supply chain to highlight challenges in understanding how future viral pandemics may jeopardize food security. For example, a lack of publicly available data on staffing levels, working conditions, and product throughputs limits the possibility to simulate supply chain breakdowns as a function of outbreaks in meatpacking plants. Workers provide labor inputs to the food system, while the food system exposes them to risks of illness and death; simultaneously, workers face economic pressures to work while sick and face demand-side FEW insecurities that affect viral susceptibility. Labor inputs to industrial food supply chains hinge on such system dynamics for which there is virtually no quantitative modeling capacity. COVID-19 however provides an opportunity to parameterize and evaluate new models for FEW resiliency. We propose near-term data collection priorities that span classic FEW research, such as characterization of materials throughputs, and include social science methods and perspectives, such as accounting for workers’ behavioral responses to competing health and economic pressures.