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477 results on '"Dobson, Andrew"'

1. Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Author

Borlase, Anna, Brady, Oliver, Browning, Raiha, Chitnis, Nakul, Coffeng, Luc, Crowley, Emily, Cucunubá, Zulma, Cummings, Derek, Davis, Christopher, Davis, Emma, Dixon, Matthew, Dobson, Andrew, Dyson, Louise, French, Michael, Fronterre, Claudio, Giorgi, Emanuele, Huang, Ching-I, Jain, Saurabh, James, Ananthu, Kim, Sung, Kura, Klodeta, Lucianez, Ana, Marks, Michael, Mbabazi, Pamela, Medley, Graham, Michael, Edwin, Montresor, Antonio, Mutono, Nyamai, Mwangi, Thumbi, Rock, Kat, Saboyá-Díaz, Martha-Idalí, Sasanami, Misaki, Schwehm, Markus, Spencer, Simon, Srivathsan, Ariktha, Stawski, Robert, Stolk, Wilma, Sutherland, Samuel, Tchuenté, Louis-Albert, de Vlas, Sake, Walker, Martin, Brooker, Simon, Hollingsworth, T, Solomon, Anthony, Fall, Ibrahima, Vasconcelos, Andreia, King, Jonathan, Nunes-Alves, Cláudio, Anderson, Roy, Argaw, Daniel, Basáñez, Maria-Gloria, Bilal, Shakir, Blok, David, and Blumberg, Seth

Subjects
control, elimination, mathematical models, neglected tropical diseases, policy-making, Neglected Diseases, Humans, Tropical Medicine, COVID-19, Models, Theoretical, World Health Organization, SARS-CoV-2, Decision Making, Global Health
Abstract

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

Published
2024

3. Manipulating Deformable Objects by Interleaving Prediction, Planning, and Control

Author

McConachie, Dale, Dobson, Andrew, Ruan, Mengyao, and Berenson, Dmitry

Subjects
Computer Science - Robotics
Abstract

We present a framework for deformable object manipulation that interleaves planning and control, enabling complex manipulation tasks without relying on high-fidelity modeling or simulation. The key question we address is when should we use planning and when should we use control to achieve the task? Planners are designed to find paths through complex configuration spaces, but for highly underactuated systems, such as deformable objects, achieving a specific configuration is very difficult even with high-fidelity models. Conversely, controllers can be designed to achieve specific configurations, but they can be trapped in undesirable local minima due to obstacles. Our approach consists of three components: (1) A global motion planner to generate gross motion of the deformable object; (2) A local controller for refinement of the configuration of the deformable object; and (3) A novel deadlock prediction algorithm to determine when to use planning versus control. By separating planning from control we are able to use different representations of the deformable object, reducing overall complexity and enabling efficient computation of motion. We provide a detailed proof of probabilistic completeness for our planner, which is valid despite the fact that our system is underactuated and we do not have a steering function. We then demonstrate that our framework is able to successfully perform several manipulation tasks with rope and cloth in simulation which cannot be performed using either our controller or planner alone. These experiments suggest that our planner can generate paths efficiently, taking under a second on average to find a feasible path in three out of four scenarios. We also show that our framework is effective on a 16 DoF physical robot, where reachability and dual-arm constraints make the planning more difficult., Comment: Accepted to The International Journal of Robotics Research

Published
2020
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5. Association of Environmental Factors with Seasonal Intensity of Erysipelothrix rhusiopathiae Seropositivity among Arctic Caribou

Author

Aleuy, O. Alejandro, Anholt, Michele, Orsel, Karin, Mavrot, Fabien, Gagnon, Catherine A., Beckmen, Kimberlee, Cote, Steeve D., Cuyler, Christine, Dobson, Andrew, Elkin, Brett, Leclerc, Lisa-Marie, Taillon, Joelle, and Kutz, Susan

Subjects
Reindeer -- Diseases -- Environmental aspects, Caribou -- Diseases -- Environmental aspects, Mycoplasmatales -- Identification and classification -- Environmental aspects, Emerging communicable diseases -- Risk factors -- Environmental aspects, Health
Abstract

A 2021 report of the Intergovernmental Panel on Climate Change (1) reinforced that anthropogenic influences on climate systems are causing increases in temperature and extremes of weather and climate events [...]

Published
2022
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6. dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planning

Author

Shome, Rahul, Solovey, Kiril, Dobson, Andrew, Halperin, Dan, and Bekris, Kostas E.

Subjects
Computer Science - Robotics
Abstract

Many exciting robotic applications require multiple robots with many degrees of freedom, such as manipulators, to coordinate their motion in a shared workspace. Discovering high-quality paths in such scenarios can be achieved, in principle, by exploring the composite space of all robots. Sampling-based planners do so by building a roadmap or a tree data structure in the corresponding configuration space and can achieve asymptotic optimality. The hardness of motion planning, however, renders the explicit construction of such structures in the composite space of multiple robots impractical. This work proposes a scalable solution for such coupled multi-robot problems, which provides desirable path-quality guarantees and is also computationally efficient. In particular, the proposed \drrtstar\ is an informed, asymptotically-optimal extension of a prior sampling-based multi-robot motion planner, \drrt. The prior approach introduced the idea of building roadmaps for each robot and implicitly searching the tensor product of these structures in the composite space. This work identifies the conditions for convergence to optimal paths in multi-robot problems, which the prior method was not achieving. Building on this analysis, \drrt\ is first properly adapted so as to achieve the theoretical guarantees and then further extended so as to make use of effective heuristics when searching the composite space of all robots. The case where the various robots share some degrees of freedom is also studied. Evaluation in simulation indicates that the new algorithm, \drrtstar\, converges to high-quality paths quickly and scales to a higher number of robots where various alternatives fail. This work also demonstrates the planner's capability to solve problems involving multiple real-world robotic arms.

Published
2019
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8. Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Author

Vasconcelos, Andreia, primary, King, Jonathan D, additional, Nunes-Alves, Cláudio, additional, Anderson, Roy, additional, Argaw, Daniel, additional, Basáñez, Maria-Gloria, additional, Bilal, Shakir, additional, Blok, David J, additional, Blumberg, Seth, additional, Borlase, Anna, additional, Brady, Oliver J, additional, Browning, Raiha, additional, Chitnis, Nakul, additional, Coffeng, Luc E, additional, Crowley, Emily H, additional, Cucunubá, Zulma M, additional, Cummings, Derek A T, additional, Davis, Christopher Neil, additional, Davis, Emma Louise, additional, Dixon, Matthew, additional, Dobson, Andrew, additional, Dyson, Louise, additional, French, Michael, additional, Fronterre, Claudio, additional, Giorgi, Emanuele, additional, Huang, Ching-I, additional, Jain, Saurabh, additional, James, Ananthu, additional, Kim, Sung Hye, additional, Kura, Klodeta, additional, Lucianez, Ana, additional, Marks, Michael, additional, Mbabazi, Pamela Sabina, additional, Medley, Graham F, additional, Michael, Edwin, additional, Montresor, Antonio, additional, Mutono, Nyamai, additional, Mwangi, Thumbi S, additional, Rock, Kat S, additional, Saboyá-Díaz, Martha-Idalí, additional, Sasanami, Misaki, additional, Schwehm, Markus, additional, Spencer, Simon E F, additional, Srivathsan, Ariktha, additional, Stawski, Robert S, additional, Stolk, Wilma A, additional, Sutherland, Samuel A, additional, Tchuenté, Louis-Albert Tchuem, additional, de Vlas, Sake J, additional, Walker, Martin, additional, Brooker, Simon J, additional, Hollingsworth, T Déirdre, additional, Solomon, Anthony W, additional, and Fall, Ibrahima Socé, additional

Published
2024
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12. Evidence gaps and diversity among potential win–win solutions for conservation and human infectious disease control

Author

Hopkins, Skylar R, Lafferty, Kevin D, Wood, Chelsea L, Olson, Sarah H, Buck, Julia C, De Leo, Giulio A, Fiorella, Kathryn J, Fornberg, Johanna L, Garchitorena, Andres, Jones, Isabel J, Kuris, Armand M, Kwong, Laura H, LeBoa, Christopher, Leon, Ariel E, Lund, Andrea J, MacDonald, Andrew J, Metz, Daniel C G, Nova, Nicole, Peel, Alison J, Remais, Justin V, Stewart Merrill, Tara E, Wilson, Maya, Bonds, Matthew H, Dobson, Andrew P, Lopez Carr, David, Howard, Meghan E, Mandle, Lisa, and Sokolow, Susanne H

Published
2022
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15. Scalable Asymptotically-Optimal Multi-Robot Motion Planning

Author

Dobson, Andrew, Solovey, Kiril, Shome, Rahul, Halperin, Dan, and Bekris, Kostas E.

Subjects
Computer Science - Multiagent Systems, Computer Science - Robotics
Abstract

Finding asymptotically-optimal paths in multi-robot motion planning problems could be achieved, in principle, using sampling-based planners in the composite configuration space of all of the robots in the space. The dimensionality of this space increases with the number of robots, rendering this approach impractical. This work focuses on a scalable sampling-based planner for coupled multi-robot problems that provides asymptotic optimality. It extends the dRRT approach, which proposed building roadmaps for each robot and searching an implicit roadmap in the composite configuration space. This work presents a new method, dRRT* , and develops theory for scalable convergence to optimal paths in multi-robot problems. Simulated experiments indicate dRRT* converges to high-quality paths while scaling to higher numbers of robots where the naive approach fails. Furthermore, dRRT* is applicable to high-dimensional problems, such as planning for robot manipulators, Comment: 8 pages, 12 figures, submitted to the first International Symposium on Multi-Robot and Multi-Agent Systems (MRS)

Published
2017

16. A solution scan of societal options to reduce transmission and spread of respiratory viruses: SARS-CoV-2 as a case study

Author

Sutherland, William J., Taylor, Nigel G., Aldridge, David C., Martin, Philip, Rhodes, Catherine, Shackelford, Gorm, Beard, Simon, Belfield, Haydn, Bladon, Andrew J., Brick, Cameron, Christie, Alec P., Dobson, Andrew P., Downey, Harriet, Hood, Amelia S.C., Hua, Fangyuan, Hughes, Alice C., Jarvis, Rebecca M., MacFarlane, Douglas, Morgan, William H., Mupepele, Anne-Christine, Marciniak, Stefan J., Nelson, Cassidy, Ó hÉigeartaigh, Seán, Rios Rojas, Clarissa, Sainsbury, Katherine A., Smith, Rebecca K., Sundaram, Lalitha S., Thornton, Ann, Watkins, John, White, Thomas B., Willott, Kate, and Petrovan, Silviu O.

Published
2021
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21. Lyme disease ecology in a changing world: consensus, uncertainty and critical gaps for improving control

Author

Kilpatrick, A Marm, Dobson, Andrew DM, Levi, Taal, Salkeld, Daniel J, Swei, Andrea, Ginsberg, Howard S, Kjemtrup, Anne, Padgett, Kerry A, Jensen, Per M, Fish, Durland, Ogden, Nick H, and Diuk-Wasser, Maria A

Subjects
Vector-Borne Diseases, Infectious Diseases, Prevention, Lyme Disease, Emerging Infectious Diseases, Infection, Good Health and Well Being, Animals, Borrelia burgdorferi, Communicable Disease Control, Humans, Incidence, Ixodes, Risk, epidemiology, emerging infectious disease, dilution effect, Biological Sciences, Medical and Health Sciences, Evolutionary Biology
Abstract

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats, (iv) reservoir competence of host species, and (v) pathogenicity for humans of different genotypes of Borrelia burgdorferi Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host-vector-borne zoonotic disease.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Published
2017

22. Transformational Principles for NEON Sampling of Mammalian Parasites and Pathogens: A Response to Springer and Colleagues

Author

Cook, Joseph A, Greiman, Stephen E, Agosta, Salvatore J, Anderson, Robert P, Arbogast, Brian S, Baker, Robert J, Boeger, Walter, Bradley, Robert D, Brooks, Daniel R, Cole, Rebecca, Demboski, John R, Dobson, Andrew P, Dunnum, Jonathan L, Eckerlin, Ralph P, Esselstyn, Jacob, Galbreath, Kurt E, Hawdon, John, Hoekstra, Hopi E, Kutz, Susan J, Light, Jessica E, Olson, Link E, Patterson, Bruce D, Patton, James L, Phillips, Anna J, Rickart, Eric, Rogers, Duke S, Siddall, Mark E, Tkach, Vasyl V, and Hoberg, Eric P

Subjects
Environmental Sciences, Biological Sciences, Ecology
Published
2016

27. Transmission ecology of canine parvovirus in a multi-host, multi-pathogen system

Author

Behdenna, Abdelkader, Lembo, Tiziana, Calatayud, Olga, Cleaveland, Sarah, Halliday, Jo E. B., Packer, Craig, Lankester, Felix, Hampson, Katie, Craft, Meggan E., Czupryna, Anna, Dobson, Andrew P., Dubovi, Edward J., Ernest, Eblate, Fyumagwa, Robert, Hopcraft, J. Grant C., Mentzel, Christine, Mzimbiri, Imam, Sutton, David, Willett, Brian, Haydon, Daniel T., and Viana, Mafalda

Published
2019

31. Eight challenges in modelling disease ecology in multi-host, multi-agent systems

Author

Buhnerkempe, Michael G, Roberts, Mick G, Dobson, Andrew P, Heesterbeek, Hans, Hudson, Peter J, and Lloyd-Smith, James O

Subjects
Aetiology, 2.1 Biological and endogenous factors, Infection, Good Health and Well Being, Communicable Diseases, Ecology, Food Chain, Host-Pathogen Interactions, Humans, Life Cycle Stages, Models, Statistical, Population Dynamics, Multiple hosts, Multiple pathogens, Community ecology, Maintenance, Food webs, Clinical Sciences, Public Health and Health Services
Abstract

Many disease systems exhibit complexities not captured by current theoretical and empirical work. In particular, systems with multiple host species and multiple infectious agents (i.e., multi-host, multi-agent systems) require novel methods to extend the wealth of knowledge acquired studying primarily single-host, single-agent systems. We outline eight challenges in multi-host, multi-agent systems that could substantively increase our knowledge of the drivers and broader ecosystem effects of infectious disease dynamics.

Published
2015

34. Ivory crisis : Growing no-trade consensus

Author

Sills, Jennifer, Sekar, Nitin, Clark, William, Dobson, Andrew, Coelho, Paula Cristina Francisco, Hannam, Phillip M., Hepworth, Robert, Hsiang, Solomon, Kahumbu, Paula, Lee, Phyllis C., Lindsay, Keith, Pereira, Carlos Lopes, Wasser, Samuel K., and Nowak, Katarzyna

Published
2018

36. Pneumonia in Bighorn Sheep : Risk and Resilience

Author

CASSIRER, E. FRANCES, MANLOVE, KEZIA R., ALMBERG, EMILY S., KAMATH, PAULINE L., COX, MIKE, WOLFF, PEREGRINE, ROUG, ANNETTE, SHANNON, JUSTIN, ROBINSON, RUSTY, HARRIS, RICHARD B., GONZALES, BEN J., PLOWRIGHT, RAINA K., HUDSON, PETER J., CROSS, PAUL C., DOBSON, ANDREW, and BESSER, THOMAS E.

Published
2018

37. Preface

Author

Dobson, Andrew, primary, Holt, Robert D., additional, and Tilman, David, additional

Published
2020
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39. Valuing water for sustainable development

Author

Garrick, Dustin E., Hall, Jim W., Dobson, Andrew, Damania, Richard, Grafton, R. Quentin, Hope, Robert, Hepburn, Cameron, Bark, Rosalind, Boltz, Frederick, De Stefano, Lucia, O’Donnell, Erin, Matthews, Nathanial, and Money, Alex

Published
2017

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