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Venne DM, Hartley DM, Malchione MD, Koch M, Britto AY, Goodman JL. Correction: Review and analysis of the overlapping threats of carbapenem and polymyxin resistant E. Coli and Klebsiella in Africa. Antimicrob Resist Infect Control 2024; 13:51. [PMID: 38735960 DOI: 10.1186/s13756-024-01403-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024] Open
Affiliation(s)
- Danielle M Venne
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - David M Hartley
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, 45229, USA
| | - Marissa D Malchione
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
- Sabin Vaccine Institute, Influenza Vaccine Innovation, 2175 K St NW, Washington, DC, 20037, USA
| | - Michala Koch
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - Anjali Y Britto
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - Jesse L Goodman
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA.
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Stanzler M, Figueroa J, Beck AF, McPherson ME, Miff S, Penix H, Little J, Sampath B, Barker P, Hartley DM. Learning from an equitable, data-informed response to COVID-19: Translating knowledge into future action and preparation. Learn Health Syst 2024; 8:e10369. [PMID: 38249853 PMCID: PMC10797568 DOI: 10.1002/lrh2.10369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 04/04/2023] [Accepted: 04/04/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction The COVID-19 pandemic revealed numerous barriers to effectively managing public health crises, including difficulties in using publicly available, community-level data to create learning systems in support of local public health decision responses. Early in the COVID-19 pandemic, a group of health care partners began meeting to learn from their collective experiences. We identified key tools and processes for using data and learning system structures to drive equitable public health decision making throughout different phases of the pandemic. Methods In fall of 2021, the team developed an initial theory of change directed at achieving herd immunity for COVID-19. The theoretical drivers were explored qualitatively through a series of nine 45-min telephonic interviews conducted with 16 public health and community leaders across the United States. Interview responses were analyzed into key themes to inform potential future practices, tools, and systems. In addition to the interviews, partners in Dallas and Cincinnati reflected on their own COVID-19 experiences. Results Interview responses fell broadly into four themes that contribute to effective, community driven responses to COVID-19: real-time, accessible data that are mindful of the tension between community transparency and individual privacy; a continued fostering of public trust; adaptable infrastructures and systems; and creating cohesive community coalitions with shared alignment and goals. These themes and partner experiences helped us revise our preliminary theory of change around the importance of community collaboration and trust building and also helped refine the development of the Community Protection Dashboard tool. Conclusions There was broad agreement amongst public health and community leaders about the key elements of the data and learning systems required to manage public health responses to COVID-19. These findings may be informative for guiding the use of data and learning in the management of future public health crises or population health initiatives.
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Affiliation(s)
| | | | - Andrew F. Beck
- Cincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- University of Cincinnati College of MedicineCincinnatiOhioUSA
| | | | - Steve Miff
- Parkland Center for Clinical Innovation (PCCI)DallasTexasUSA
| | | | | | | | - Pierre Barker
- Institute for Healthcare ImprovementBostonMassachusettsUSA
| | - David M. Hartley
- Cincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- University of Cincinnati College of MedicineCincinnatiOhioUSA
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Venne DM, Hartley DM, Malchione MD, Koch M, Britto AY, Goodman JL. Review and analysis of the overlapping threats of carbapenem and polymyxin resistant E. coli and Klebsiella in Africa. Antimicrob Resist Infect Control 2023; 12:29. [PMID: 37013626 PMCID: PMC10071777 DOI: 10.1186/s13756-023-01220-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 02/18/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND Carbapenem-resistant Enterobacterales are among the most serious antimicrobial resistance (AMR) threats. Emerging resistance to polymyxins raises the specter of untreatable infections. These resistant organisms have spread globally but, as indicated in WHO reports, the surveillance needed to identify and track them is insufficient, particularly in less resourced countries. This study employs comprehensive search strategies with data extraction, meta-analysis and mapping to help address gaps in the understanding of the risks of carbapenem and polymyxin resistance in the nations of Africa. METHODS Three comprehensive Boolean searches were constructed and utilized to query scientific and medical databases as well as grey literature sources through the end of 2019. Search results were screened to exclude irrelevant results and remaining studies were examined for relevant information regarding carbapenem and/or polymyxin(s) susceptibility and/or resistance amongst E. coli and Klebsiella isolates from humans. Such data and study characteristics were extracted and coded, and the resulting data was analyzed and geographically mapped. RESULTS Our analysis yielded 1341 reports documenting carbapenem resistance in 40 of 54 nations. Resistance among E. coli was estimated as high (> 5%) in 3, moderate (1-5%) in 8 and low (< 1%) in 14 nations with at least 100 representative isolates from 2010 to 2019, while present in 9 others with insufficient isolates to support estimates. Carbapenem resistance was generally higher among Klebsiella: high in 10 nations, moderate in 6, low in 6, and present in 11 with insufficient isolates for estimates. While much less information was available concerning polymyxins, we found 341 reports from 33 of 54 nations, documenting resistance in 23. Resistance among E. coli was high in 2 nations, moderate in 1 and low in 6, while present in 10 with insufficient isolates for estimates. Among Klebsiella, resistance was low in 8 nations and present in 8 with insufficient isolates for estimates. The most widespread associated genotypes were, for carbapenems, blaOXA-48, blaNDM-1 and blaOXA-181 and, for polymyxins, mcr-1, mgrB, and phoPQ/pmrAB. Overlapping carbapenem and polymyxin resistance was documented in 23 nations. CONCLUSIONS While numerous data gaps remain, these data show that significant carbapenem resistance is widespread in Africa and polymyxin resistance is also widely distributed, indicating the need to support robust AMR surveillance, antimicrobial stewardship and infection control in a manner that also addresses broader animal and environmental health dimensions.
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Affiliation(s)
- Danielle M Venne
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - David M Hartley
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, 45229, USA
| | - Marissa D Malchione
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
- Sabin Vaccine Institute, Influenza Vaccine Innovation, 2175 K St NW, Washington, DC, 20037, USA
| | - Michala Koch
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - Anjali Y Britto
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA
| | - Jesse L Goodman
- Center on Medical Product Access, Safety and Stewardship, Georgetown University, 3900 Reservoir Road, Washington, DC, 20057, USA.
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Koo J, Auletta JJ, Hartley DM, Huber J, Jaglowski S, Kapadia M, Kusnier K, Lehmann L, Maakaron J, Myers KC, Pai A, Parker L, Phelan R, Sper C, Rotz SJ, Dandoy CE. Secondary Impact of the Coronavirus Disease 19 Pandemic on Patients and the Cellular Therapy Healthcare Ecosystem. Transplant Cell Ther 2022; 28:737-746. [PMID: 35902050 PMCID: PMC9313529 DOI: 10.1016/j.jtct.2022.07.020] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/18/2022] [Accepted: 07/20/2022] [Indexed: 11/24/2022]
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has significantly impacted global health and healthcare delivery systems. To characterize the secondary effects of the COVID-19 pandemic and mitigation strategies used in the delivery of hematopoietic stem cell transplantation (HSCT) care, we performed a comprehensive literature search encompassing changes in specific donor collection, processing practices, patient outcomes, and patient-related concerns specific to HSCT and HSCT-related healthcare delivery. In this review, we summarize the available literature on the secondary impacts the COVID-19 pandemic on the fields of HSCT and cellular therapy. The COVID-19 pandemic has had numerous secondary impacts on patients undergoing HSCT and the healthcare delivery systems involved in providing complex care to HSCT recipients. Institutions must identify these influences on outcomes and adjust accordingly to maintain and improve outcomes for the transplantation and cellular therapy community.
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Affiliation(s)
- Jane Koo
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio.
| | - Jeffrey J Auletta
- Center for International Blood and Marrow Transplant Research, Milwaukee, Wisconsin; Hematology/Oncology/BMT and Infectious Diseases, Nationwide Children's Hospital, Columbus, Ohio
| | - David M Hartley
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio; James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - John Huber
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio
| | - Samantha Jaglowski
- Division of Hematology-Oncology and Transplantation; Department of Pediatrics, Ohio State University Medical Center, Columbus, Ohio
| | - Malika Kapadia
- Division of Pediatric Oncology, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Department of Pediatrics, Harvard University Medical School, Boston, Massachusetts
| | - Katilyn Kusnier
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio
| | - Leslie Lehmann
- Division of Pediatric Oncology, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Department of Pediatrics, Harvard University Medical School, Boston, Massachusetts
| | - Joseph Maakaron
- Division of Hematology, Oncology, and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Kasiani C Myers
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio
| | - Ahna Pai
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio; Department of Behavioral Medicine & Clinical Psychology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Loretta Parker
- Division of Hematology/Oncology, Department of Pediatrics, The University of Oklahoma College of Medicine, Oklahoma City, Oklahoma
| | - Rachel Phelan
- Division of Pediatric Hematology, Oncology, Blood and Marrow Transplantation, Department of Pediatrics, Medical College of Wisconsin and Children's Wisconsin, Milwaukee, Wisconsin
| | - Christine Sper
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Seth J Rotz
- Department of Pediatric Hematology, Oncology, and Blood and Marrow Transplantation, Cleveland Clinic Children's Hospital, Cleveland, Ohio
| | - Christopher E Dandoy
- Division of Bone Marrow Transplantation and Immune Deficiency, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio
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Addison J, Razzaghi H, Bailey C, Dickinson K, Corathers SD, Hartley DM, Utidjian L, Carle AC, Rhodes ET, Alonso GT, Haller MJ, Gannon AW, Indyk JA, Arbeláez AM, Shenkman E, Forrest CB, Eckrich D, Magnusen B, Davies SD, Walsh KE. Testing an Automated Approach to Identify Variation in Outcomes among Children with Type 1 Diabetes across Multiple Sites. Pediatr Qual Saf 2022; 7:e602. [PMID: 38584961 PMCID: PMC10997286 DOI: 10.1097/pq9.0000000000000602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/21/2022] [Indexed: 11/26/2022] Open
Abstract
Introduction Efficient methods to obtain and benchmark national data are needed to improve comparative quality assessment for children with type 1 diabetes (T1D). PCORnet is a network of clinical data research networks whose infrastructure includes standardization to a Common Data Model (CDM) incorporating electronic health record (EHR)-derived data across multiple clinical institutions. The study aimed to determine the feasibility of the automated use of EHR data to assess comparative quality for T1D. Methods In two PCORnet networks, PEDSnet and OneFlorida, the study assessed measures of glycemic control, diabetic ketoacidosis admissions, and clinic visits in 2016-2018 among youth 0-20 years of age. The study team developed measure EHR-based specifications, identified institution-specific rates using data stored in the CDM, and assessed agreement with manual chart review. Results Among 9,740 youth with T1D across 12 institutions, one quarter (26%) had two or more measures of A1c greater than 9% annually (min 5%, max 47%). The median A1c was 8.5% (min site 7.9, max site 10.2). Overall, 4% were hospitalized for diabetic ketoacidosis (min 2%, max 8%). The predictive value of the PCORnet CDM was >75% for all measures and >90% for three measures. Conclusions Using EHR-derived data to assess comparative quality for T1D is a valid, efficient, and reliable data collection tool for measuring T1D care and outcomes. Wide variations across institutions were observed, and even the best-performing institutions often failed to achieve the American Diabetes Association HbA1C goals (<7.5%).
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Affiliation(s)
- Jessica Addison
- From the Division of Adolescent and Young Adult Medicine, Boston Children’s Hospital, Boston, Mass
| | - Hanieh Razzaghi
- Applied Clinical Research Center, Children’s Hospital of Philadelphia, Philadelphia, Pa
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Pa
| | - Charles Bailey
- Applied Clinical Research Center, Children’s Hospital of Philadelphia, Philadelphia, Pa
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Pa
| | - Kimberley Dickinson
- Applied Clinical Research Center, Children’s Hospital of Philadelphia, Philadelphia, Pa
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Pa
| | - Sarah D. Corathers
- Division of Endocrinology, Cincinnati Children’s Hospital, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - David M. Hartley
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital, Cincinnati, Ohio
| | - Levon Utidjian
- Applied Clinical Research Center, Children’s Hospital of Philadelphia, Philadelphia, Pa
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Pa
| | - Adam C. Carle
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital, Cincinnati, Ohio
- Department of Psychology, College of Arts and Sciences, University of Cincinnati, Cincinnati, Ohio
| | - Erinn T. Rhodes
- Division of Endocrinology, Boston Children’s Hospital, Boston, Mass
- Department of Pediatrics, Harvard Medical School, Boston, Mass
| | - G. Todd Alonso
- University of Colorado Anschutz Medical Campus, Barbara Davis Center, Aurora, Colo
| | | | | | - Justin A. Indyk
- Section of Endocrinology, Nationwide Children’s Hospital, Columbus, Ohio
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio
| | - Ana Maria Arbeláez
- Washington University in St. Louis, St. Louis, Mo
- St. Louis Children’s Hospital, St. Louis, Mo
| | - Elizabeth Shenkman
- University of Florida, College of Medicine, Department of Health Outcomes and Biomedical Informatics, Gainesville, Fla
| | | | | | | | - Sara Deakyne Davies
- University of Colorado Anschutz Medical Campus, Barbara Davis Center, Aurora, Colo
| | - Kathleen E. Walsh
- Department of Pediatrics, Harvard Medical School, Boston, Mass
- Division of General Pediatrics, Boston Children’s Hospital, Boston, Mass
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Keck C, Hartley DM, Havens M, Margolis PA, Seid M. Getting what is needed, when it's needed: Sharing information, knowledge, and know-how in a Collaborative Learning Health System. Learn Health Syst 2021; 5:e10268. [PMID: 34277941 PMCID: PMC8278434 DOI: 10.1002/lrh2.10268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/25/2021] [Accepted: 04/01/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Collaborative Learning Health Systems (CLHS) improve outcomes in part by facilitating collaboration among all stakeholders. One way to facilitate collaboration is by creating conditions for the production and sharing of medical and non-medical resources (information, knowledge, and knowhow [IKK]) so anybody can get "what is needed, when it's needed" (WINWIN) to act in ways that improve health and healthcare. Matching resources to needs can facilitate accurate diagnosis, appropriate prescribing, answered questions, provision of emotional and social support, and uptake of innovations. OBJECTIVES We describe efforts in ImproveCareNow, a CLHS improving outcomes in pediatric inflammatory bowel disease (IBD), to increase the number of patients and families creating and accessing IKK, and the challenges faced in that process. METHODS We applied tactics such as outreach through trusted messengers, community organizing, and digital outreach such as sharing resources on our website, via social media, and email to increase the number of people producing, able to access, and accessing IKK. We applied an existing measurement system to track our progress and supplemented this with community feedback. RESULTS In August of 2017 we identified and began measuring specific actions to track community growth. The number of patients and families producing IKK has increased by a factor of 2.7, using resources has increased by a factor of 4.1 and aware of resources as increased by a factor of 4.0. We identified challenges to measurement and scaling. CONCLUSIONS It is possible to intentionally increase the number of patients and caregivers engaged with a CHLS to produce and share resources to improve their health.
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Affiliation(s)
- Christian Keck
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
| | - David M. Hartley
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | - Mary Havens
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
| | - Peter A. Margolis
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | - Michael Seid
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
- Cincinnati Children's Hospital, Division of Pulmonary MedicineCincinnatiOhioUSA
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Hartley DM, Seid M. Collaborative learning health systems: Science and practice. Learn Health Syst 2021; 5:e10286. [PMID: 34277947 PMCID: PMC8278439 DOI: 10.1002/lrh2.10286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 06/25/2021] [Indexed: 11/16/2022] Open
Affiliation(s)
- David M. Hartley
- James M. Anderson Center for Health Systems ExcellenceCincinnati Children's HospitalCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | - Michael Seid
- James M. Anderson Center for Health Systems ExcellenceCincinnati Children's HospitalCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
- Division of Pulmonary MedicineCincinnati Children's HospitalCincinnatiOhioUSA
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Seid M, Hartley DM, Margolis PA. A science of collaborative learning health systems. Learn Health Syst 2021; 5:e10278. [PMID: 34277944 PMCID: PMC8278442 DOI: 10.1002/lrh2.10278] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/12/2021] [Accepted: 05/13/2021] [Indexed: 11/08/2022] Open
Abstract
INTRODUCTION Improving the U.S. healthcare system and health outcomes is one of the most pressing public health challenges of our time. Previously described Collaborative Learning Health Systems (CLHSs) are a promising approach to outcomes improvement. In order to fully realize this promise, a deeper understanding of this phenomenon is necessary. METHODS We drew on our experience over the past decade with CLHSs as well as qualitative literature review to answer three questions: What kind of phenomena are CLHSs? and what is an appropriate scientific approach? How might we frame CLHSs conceptually? What are potential mechanisms of action? RESULTS CLHSs are complex adaptive systems in which all stakeholders are able to collaborate, at scale, to create and share resources to satisfy a variety of needs. This is accomplished by providing infrastructure and services that enable stakeholders to act on their inherent motivations. This framing has implications for both research and practice. CONCLUSION Articulating this framework and potential mechanisms of action should facilitate research to test and refine hypotheses as well as guide practice to develop and optimize this promising approach to improving healthcare systems.
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Affiliation(s)
- Michael Seid
- Division of Pulmonary MedicineCincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- Department of PediatricsCollege of Medicine, University of CincinnatiCincinnatiOhioUSA
| | - David M. Hartley
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- Department of PediatricsCollege of Medicine, University of CincinnatiCincinnatiOhioUSA
| | - Peter A. Margolis
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical CenterCincinnatiOhioUSA
- Department of PediatricsCollege of Medicine, University of CincinnatiCincinnatiOhioUSA
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Seid M, Bridgeland D, Bridgeland A, Hartley DM. A collaborative learning health system agent-based model: Computational and face validity. Learn Health Syst 2021; 5:e10261. [PMID: 34277939 PMCID: PMC8278449 DOI: 10.1002/lrh2.10261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 01/21/2021] [Accepted: 01/30/2021] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION Improving the healthcare system is a major public health challenge. Collaborative learning health systems (CLHS) - network organizations that allow all healthcare stakeholders to collaborate at scale - are a promising response. However, we know little about CLHS mechanisms of actions, nor how to optimize CLHS performance. Agent-based models (ABM) have been used to study a variety of complex systems. We translate the conceptual underpinnings of a CLHS to a computational model and demonstrate initial computational and face validity. METHODS CLHSs are organized to allow stakeholders (patients and families, clinicians, researchers) to collaborate, at scale, in the production and distribution of information, knowledge, and know-how for improvement. We build up a CLHS ABM from a population of patient- and doctor-agents, assign them characteristics, and set them into interaction, resulting in engagement, information, and knowledge to facilitate optimal treatment selection. To assess computational and face validity, we vary a single parameter - the degree to which patients influence other patients - and trace its effects on patient engagement, shared knowledge, and outcomes. RESULTS The CLHS ABM, developed in Python and using the open-source modeling framework Mesa, is delivered as a web application. The model is simulated on a cloud server and the user interface is a web browser using Python and Plotly Dash. Holding all other parameters steady, when patient influence increases, the overall patient population activation increases, leading to an increase in shared knowledge, and higher median patient outcomes. CONCLUSIONS We present the first theoretically-derived computational model of CLHSs, demonstrating initial computational and face validity. These preliminary results suggest that modeling CLHSs using an ABM is feasible and potentially valid. A well-developed and validated computational model of the health system may have profound effects on understanding mechanisms of action, potential intervention targets, and ultimately translation to improved outcomes.
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Affiliation(s)
- Michael Seid
- Division of Pulmonary MedicineCincinnati Children's HospitalCincinnatiOhioUSA
- James M. Anderson Center for Health Systems ExcellenceCincinnati Children's HospitalCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | | | | | - David M. Hartley
- James M. Anderson Center for Health Systems ExcellenceCincinnati Children's HospitalCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
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Hartley DM, Keck C, Havens M, Margolis PA, Seid M. Measuring engagement in a collaborative learning health system: The case of ImproveCareNow. Learn Health Syst 2021; 5:e10225. [PMID: 33889734 PMCID: PMC8051351 DOI: 10.1002/lrh2.10225] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/27/2020] [Accepted: 03/05/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, and track over time, engagement in ImproveCareNow, a collaborative learning health system for children with inflammatory bowel disease. INTRODUCTION We developed a categorical classification scheme for engagement in ImproveCareNow. Each tier is defined in terms of observable individual behaviors. When an individual completes one or more qualifying behavior, s/he is classified as engaged at that tier. Individuals are entered into a database, which is accessible to care centers throughout the ImproveCareNow network. Database records include fields for individual name, behavior type, time, place, and level of engagement. RESULTS The resulting system is employed at 79 ImproveCareNow care centers in the United States. The system recognizes four levels of engagement. Behaviors are recorded in a managed vocabulary and recorded in an online database. The database is queried weekly for individual engagement behaviors, which are tracked longitudinally. Center- and network-level statistics are generated and disseminated to stakeholders. CONCLUSION It is possible to monitor longitudinal engagement in a collaborative learning health system, thereby charting progress toward engagement goals and enabling quantitative evaluation of interventions aimed at increasing engagement.
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Affiliation(s)
- David M. Hartley
- Cincinnati Children's HospitalJames M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | - Christian Keck
- Cincinnati Children's HospitalJames M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
| | - Mary Havens
- Cincinnati Children's HospitalJames M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
| | - Peter A. Margolis
- Cincinnati Children's HospitalJames M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
| | - Michael Seid
- Cincinnati Children's HospitalJames M. Anderson Center for Health Systems ExcellenceCincinnatiOhioUSA
- Department of PediatricsUniversity of Cincinnati, College of MedicineCincinnatiOhioUSA
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Beck AF, Hartley DM, Kahn RS, Taylor SC, Bishop E, Rich K, Saeed MS, Schuler CL, Seid M, Cronin SC, Raney L, Zafar MA, Margolis PA. Rapid, Bottom-Up Design of a Regional Learning Health System in Response to COVID-19. Mayo Clin Proc 2021; 96:849-855. [PMID: 33714596 PMCID: PMC7885665 DOI: 10.1016/j.mayocp.2021.02.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 01/20/2021] [Accepted: 02/09/2021] [Indexed: 11/01/2022]
Affiliation(s)
- Andrew F Beck
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH.
| | - David M Hartley
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH
| | - Robert S Kahn
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH
| | | | | | - Kate Rich
- Cincinnati Children's Hospital Medical Center, OH
| | - Myra S Saeed
- Cincinnati Children's Hospital Medical Center, OH
| | - Christine L Schuler
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH
| | - Michael Seid
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH
| | | | - Laura Raney
- Cincinnati Children's Hospital Medical Center, OH
| | - Muhammad A Zafar
- University of Cincinnati College of Medicine, OH; University of Cincinnati Medical Center, OH
| | - Peter A Margolis
- Cincinnati Children's Hospital Medical Center, OH; University of Cincinnati College of Medicine, OH
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12
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Affiliation(s)
- David M Hartley
- Cincinnati Children's Hospital, James M. Anderson Center for Health Systems Excellence, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, Ohio
| | - Eli N Perencevich
- Center for Access and Delivery Research and Evaluation, Iowa City VA Health Care System, Iowa City
- Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City
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13
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Seid M, Hartley DM, Dellal G, Myers S, Margolis PA. Organizing for collaboration: An actor-oriented architecture in ImproveCareNow. Learn Health Syst 2019; 4:e10205. [PMID: 31989029 PMCID: PMC6971120 DOI: 10.1002/lrh2.10205] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 08/19/2019] [Accepted: 10/07/2019] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Collaborative learning health systems (CLHSs) enable patients, clinicians, researchers, and others to collaborate at scale to improve outcomes and generate new knowledge. An organizational framework to facilitate this collaboration is the actor-oriented architecture, composed of (a) actors (people, organizations, and databases) with the values and abilities to self-organize; (b) a commons where they create and share resources; and (c) structures, protocols, and processes that facilitate multiactor collaboration. CLHSs may implement a variety of changes to strengthen the actor-oriented architecture and enable more actors to create and share resources. OBJECTIVE To describe and measure implementation of elements of the actor-oriented architecture in an existing Collaborative Learning Health System. METHODS We used the case of ImproveCareNow, a CLHS improving outcomes in pediatric inflammatory bowel disease, founded in 2006. We traced several network-level indicators of actor-oriented architecture between 2010 and 2016. RESULTS We identified measures of actors, the commons, and ways that have made it easier for network member sites to participate. These indicators show ImproveCareNow has made changes in the three elements of the actor-oriented architecture over time. CONCLUSION It is possible to measure the implementation of an actor-oriented architecture in a CLHS. The elements of the actor-oriented architecture may provide a conceptual framework for their development and optimization. Metrics such as those described here may be actionable indicators of the "health of the system."
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Affiliation(s)
- Michael Seid
- Pulmonary MedicineCincinnati Children's Hospital Medical CenterCincinnatiOhio
- James M Anderson Center for Health Systems ExcellenceCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - David M. Hartley
- James M Anderson Center for Health Systems ExcellenceCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - George Dellal
- James M Anderson Center for Health Systems ExcellenceCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - Sarah Myers
- James M Anderson Center for Health Systems ExcellenceCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - Peter A. Margolis
- James M Anderson Center for Health Systems ExcellenceCincinnati Children's Hospital Medical CenterCincinnatiOhio
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14
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Malchione MD, Torres LM, Hartley DM, Koch M, Goodman JL. Carbapenem and colistin resistance in Enterobacteriaceae in Southeast Asia: Review and mapping of emerging and overlapping challenges. Int J Antimicrob Agents 2019; 54:381-399. [DOI: 10.1016/j.ijantimicag.2019.07.019] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 07/16/2019] [Accepted: 07/21/2019] [Indexed: 01/21/2023]
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15
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Hartley DM, Jonas S, Grossoehme D, Kelly A, Dodds C, Alford SM, Shenkman E, Simmons J, Bailey LC, Razzaghi H, Utidjian LH, McCafferty-Fernandez J, Cole FS, Smallwood J, Werk LN, Walsh KE. Use of EHR-Based Pediatric Quality Measures: Views of Health System Leaders and Parents. Am J Med Qual 2019; 35:177-185. [PMID: 31115254 DOI: 10.1177/1062860619850322] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Measures of health care quality are produced from a variety of data sources, but often, physicians do not believe these measures reflect the quality of provided care. The aim was to assess the value to health system leaders (HSLs) and parents of benchmarking on health care quality measures using data mined from the electronic health record (EHR). Using in-context interviews with HSLs and parents, the authors investigated what new decisions and actions benchmarking using data mined from the EHR may enable and how benchmarking information should be presented to be most informative. Results demonstrate that although parents may have little experience using data on health care quality for decision making, they affirmed its potential value. HSLs expressed the need for high-confidence, validated metrics. They also perceived barriers to achieving meaningful metrics but recognized that mining data directly from the EHR could overcome those barriers. Parents and HSLs need high-confidence health care quality data to support decision making.
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Affiliation(s)
- David M Hartley
- University of Cincinnati College of Medicine, Cincinnati, OH.,Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Susannah Jonas
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Daniel Grossoehme
- University of Cincinnati College of Medicine, Cincinnati, OH.,Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Amy Kelly
- Devereux Advanced Behavioral Health, Devon, PA
| | - Cassandra Dodds
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Shannon M Alford
- University of Florida, Department of Health Outcomes and Biomedical Informatics, Gainesville, FL
| | - Elizabeth Shenkman
- University of Florida, Department of Health Outcomes and Biomedical Informatics, Gainesville, FL
| | - Jeff Simmons
- University of Cincinnati College of Medicine, Cincinnati, OH.,Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | | | | | | | | | | | | | | | - Kathleen E Walsh
- University of Cincinnati College of Medicine, Cincinnati, OH.,Cincinnati Children's Hospital Medical Center, Cincinnati, OH
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16
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Mitgang EA, Hartley DM, Malchione MD, Koch M, Goodman JL. Review and mapping of carbapenem-resistant Enterobacteriaceae in Africa: Using diverse data to inform surveillance gaps. Int J Antimicrob Agents 2018; 52:372-384. [DOI: 10.1016/j.ijantimicag.2018.05.019] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/25/2018] [Accepted: 05/26/2018] [Indexed: 01/05/2023]
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17
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Hartley DM, Giannini CM, Wilson S, Frieder O, Margolis PA, Kotagal UR, White DL, Connelly BL, Wheeler DS, Tadesse DG, Macaluso M. Coughing, sneezing, and aching online: Twitter and the volume of influenza-like illness in a pediatric hospital. PLoS One 2017; 12:e0182008. [PMID: 28753678 PMCID: PMC5533314 DOI: 10.1371/journal.pone.0182008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 07/11/2017] [Indexed: 11/25/2022] Open
Abstract
This study investigates the relation of the incidence of georeferenced tweets related to respiratory illness to the incidence of influenza-like illness (ILI) in the emergency department (ED) and urgent care clinics (UCCs) of a large pediatric hospital. We collected (1) tweets in English originating in our hospital’s primary service area between 11/1/2014 and 5/1/2015 and containing one or more specific terms related to respiratory illness and (2) the daily number of patients presenting to our hospital’s EDs and UCCs with ILI, as captured by ICD-9 codes. A Support Vector Machine classifier was applied to the set of tweets to remove those unlikely to be related to ILI. Time series of the pooled set of remaining tweets involving any term, of tweets involving individual terms, and of the ICD-9 data were constructed, and temporal cross-correlation between the social media and clinical data was computed. A statistically significant correlation (Spearman ρ = 0.23) between tweets involving the term flu and ED and UCC volume related to ILI 11 days in the future was observed. Tweets involving the terms coughing (Spearman ρ = 0.24) and headache (Spearman ρ = 0.19) individually were also significantly correlated to ILI-related clinical volume four and two days in the future, respectively. In the 2014–2015 cold and flu season, the incidence of local tweets containing the terms flu, coughing, and headache were early indicators of the incidence of ILI-related cases presenting to EDs and UCCs at our children’s hospital.
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Affiliation(s)
- David M. Hartley
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
- * E-mail:
| | - Courtney M. Giannini
- Medical Scientist Training Program, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Stephanie Wilson
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Ophir Frieder
- Department of Computer Science, Georgetown University, Washington DC, United States of America
| | - Peter A. Margolis
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Uma R. Kotagal
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Denise L. White
- James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Beverly L. Connelly
- Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Derek S. Wheeler
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Dawit G. Tadesse
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Maurizio Macaluso
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America
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18
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Perencevich EN, Hartley DM. Of Models and Methods: Our Analytic Armamentarium Applied to Methicillin-Resistant Staphylococcus aureus. Infect Control Hosp Epidemiol 2016; 26:594-7. [PMID: 16092738 DOI: 10.1086/502587] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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19
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Wright MO, Furuno JP, Venezia RA, Johnson JK, Standiford HC, Hebden JN, Hill J, Hartley DM, Harris AD, Perencevich EN. Methicillin-ResistantStaphylococcus aureusInfection and Colonization Among Hospitalized Prisoners. Infect Control Hosp Epidemiol 2015; 28:877-9. [PMID: 17564994 DOI: 10.1086/518461] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2006] [Accepted: 11/28/2006] [Indexed: 11/03/2022]
Abstract
We assessed methicillin-resistantStaphylococcus aureus(MRSA) infection and colonization in hospitalized prisoners. Of 434 admission surveillance cultures, 58 (13%) were positive for MRSA. The sensitivity of admission surveillance cultures of samples from the anterior nares was 72% and increased to 84% when the calculation included cultures of wound samples. Hospitalized prisoners are at high risk for MRSA infection and colonization, and surveillance should include cultures of nares and wound samples.
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Affiliation(s)
- Marc-Oliver Wright
- Evanston Northwestern Healthcare, Department of Infection Control, Evanston, IL 60201, USA.
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20
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21
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Corley CD, Pullum LL, Hartley DM, Benedum C, Noonan C, Rabinowitz PM, Lancaster MJ. Disease prediction models and operational readiness. PLoS One 2014; 9:e91989. [PMID: 24647562 PMCID: PMC3960139 DOI: 10.1371/journal.pone.0091989] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2012] [Accepted: 02/19/2014] [Indexed: 11/18/2022] Open
Abstract
The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4), spatial (26), ecological niche (28), diagnostic or clinical (6), spread or response (9), and reviews (3). The model parameters (e.g., etiology, climatic, spatial, cultural) and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological) were recorded and reviewed. A component of this review is the identification of verification and validation (V&V) methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology Readiness Level definitions.
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Affiliation(s)
- Courtney D. Corley
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
- * E-mail:
| | - Laura L. Pullum
- Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America
| | - David M. Hartley
- Georgetown University Medical Center, Washington, DC, United States of America
| | - Corey Benedum
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
| | - Christine Noonan
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
| | - Peter M. Rabinowitz
- Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Mary J. Lancaster
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
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22
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Barboza P, Vaillant L, Le Strat Y, Hartley DM, Nelson NP, Mawudeku A, Madoff LC, Linge JP, Collier N, Brownstein JS, Astagneau P. Factors influencing performance of internet-based biosurveillance systems used in epidemic intelligence for early detection of infectious diseases outbreaks. PLoS One 2014; 9:e90536. [PMID: 24599062 PMCID: PMC3944226 DOI: 10.1371/journal.pone.0090536] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2013] [Accepted: 02/01/2014] [Indexed: 11/19/2022] Open
Abstract
Background Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se, p = 013). I-Se was significantly associated with individual systems, types of system, languages, regions of occurrence, and types of infectious disease. Conversely, no statistical difference of C-DR was observed after adjustment for other variables. Conclusion Although differences could result from a biosurveillance system's conceptual design, findings suggest that the combined expertise amongst systems enhances early detection performance for detection of infectious diseases. While all systems showed similar early detection performance, systems including human moderation were found to have a 53% higher I-Se (p = 00001) after adjustment for other variables. Overall, the use of moderation, sources, languages, regions of occurrence, and types of cases were found to influence system performance.
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Affiliation(s)
- Philippe Barboza
- International Department, French Institute for Public Health Surveillance (Institut de Veille Sanitaire), Saint Maurice, France
- * E-mail:
| | - Laetitia Vaillant
- International Department, French Institute for Public Health Surveillance (Institut de Veille Sanitaire), Saint Maurice, France
| | - Yann Le Strat
- Infectious Department, French Institute for Public Health Surveillance (Institut de Veille Sanitaire), Saint Maurice, France
| | - David M. Hartley
- Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, D.C, United States of America
- Imaging Science and Information Systems Center, Georgetown University School of Medicine, Washington, D.C, United States of America
| | - Noele P. Nelson
- Department of Pediatrics, Georgetown University Medical Center, Washington, D.C, United States of America
| | - Abla Mawudeku
- Centre for Emergency Preparedness and Response, Public Health Agency of Canada, Ottawa, Canada
| | - Lawrence C. Madoff
- ProMED-mail, International Society for Infectious Diseases, Boston, Massachusetts, United States of America
| | - Jens P. Linge
- Joint Research Centre of the European Commission, Ispra, Italy
| | - Nigel Collier
- National Institute of Informatics, Tokyo, Japan
- The European Bioinformatics Institute, Cambridge, United Kingdom
| | - John S. Brownstein
- Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Pascal Astagneau
- École des Hautes Études en Santé Publique (EHESP), University school of public Health, PRES Sorbonne Cité, Paris, France
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23
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Smith DL, Perkins TA, Reiner RC, Barker CM, Niu T, Chaves LF, Ellis AM, George DB, Le Menach A, Pulliam JRC, Bisanzio D, Buckee C, Chiyaka C, Cummings DAT, Garcia AJ, Gatton ML, Gething PW, Hartley DM, Johnston G, Klein EY, Michael E, Lloyd AL, Pigott DM, Reisen WK, Ruktanonchai N, Singh BK, Stoller J, Tatem AJ, Kitron U, Godfray HCJ, Cohen JM, Hay SI, Scott TW. Recasting the theory of mosquito-borne pathogen transmission dynamics and control. Trans R Soc Trop Med Hyg 2014; 108:185-97. [PMID: 24591453 PMCID: PMC3952634 DOI: 10.1093/trstmh/tru026] [Citation(s) in RCA: 111] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Mosquito-borne diseases pose some of the greatest challenges in public health, especially
in tropical and sub-tropical regions of the world. Efforts to control these diseases have
been underpinned by a theoretical framework developed for malaria by Ross and Macdonald,
including models, metrics for measuring transmission, and theory of control that
identifies key vulnerabilities in the transmission cycle. That framework, especially
Macdonald's formula for R0 and its entomological derivative,
vectorial capacity, are now used to study dynamics and design interventions for many
mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010
found that the vast majority adopted the Ross–Macdonald assumption of homogeneous
transmission in a well-mixed population. Studies comparing models and data question these
assumptions and point to the capacity to model heterogeneous, focal transmission as the
most important but relatively unexplored component in current theory. Fine-scale
heterogeneity causes transmission dynamics to be nonlinear, and poses problems for
modeling, epidemiology and measurement. Novel mathematical approaches show how
heterogeneity arises from the biology and the landscape on which the processes of mosquito
biting and pathogen transmission unfold. Emerging theory focuses attention on the
ecological and social context for mosquito blood feeding, the movement of both hosts and
mosquitoes, and the relevant spatial scales for measuring transmission and for modeling
dynamics and control.
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Affiliation(s)
- David L Smith
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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Abstract
Rift Valley Fever virus (RVFV) is an enzootic virus that causes extensive morbidity and mortality in domestic ruminants in Africa, and it has shown the potential to invade other areas such as the Arabian Peninsula. Here, we develop methods for linking mathematical models to real-world data that could be used for continent-scale risk assessment given adequate data on local host and vector populations. We have applied the methods to a well-studied agricultural region of California with [Formula: see text]1 million dairy cattle, abundant and competent mosquito vectors, and a permissive climate that has enabled consistent transmission of West Nile virus and historically other arboviruses. Our results suggest that RVFV outbreaks could occur from February-November, but would progress slowly during winter-early spring or early fall and be limited spatially to areas with early increases in vector abundance. Risk was greatest in summer, when the areas at risk broadened to include most of the dairy farms in the study region, indicating the potential for considerable economic losses if an introduction were to occur. To assess the threat that RVFV poses to North America, including what-if scenarios for introduction and control strategies, models such as this one should be an integral part of the process; however, modeling must be paralleled by efforts to address the numerous remaining gaps in data and knowledge for this system.
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Affiliation(s)
- Christopher M. Barker
- Center for Vectorborne Diseases and Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, Davis, California, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Tianchan Niu
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Division of Integrated Biodefense, Georgetown University Medical Center, Washington, District of Columbia, United States of America
| | - William K. Reisen
- Center for Vectorborne Diseases and Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, Davis, California, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - David M. Hartley
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Division of Integrated Biodefense, Georgetown University Medical Center, Washington, District of Columbia, United States of America
- Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, District of Columbia, United States of America
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Hartley DM, Nelson NP, Arthur RR, Barboza P, Collier N, Lightfoot N, Linge JP, van der Goot E, Mawudeku A, Madoff LC, Vaillant L, Walters R, Yangarber R, Mantero J, Corley CD, Brownstein JS. An overview of internet biosurveillance. Clin Microbiol Infect 2013; 19:1006-13. [PMID: 23789639 DOI: 10.1111/1469-0691.12273] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Internet biosurveillance utilizes unstructured data from diverse web-based sources to provide early warning and situational awareness of public health threats. The scope of source coverage ranges from local media in the vernacular to international media in widely read languages. Internet biosurveillance is a timely modality that is available to government and public health officials, healthcare workers, and the public and private sector, serving as a real-time complementary approach to traditional indicator-based public health disease surveillance methods. Internet biosurveillance also supports the broader activity of epidemic intelligence. This overview covers the current state of the field of Internet biosurveillance, and provides a perspective on the future of the field.
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Affiliation(s)
- D M Hartley
- Imaging Science and Information Systems Center, Georgetown University School of Medicine, Washington, DC, USA; Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA
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26
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Barboza P, Vaillant L, Mawudeku A, Nelson NP, Hartley DM, Madoff LC, Linge JP, Collier N, Brownstein JS, Yangarber R, Astagneau P. Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events. PLoS One 2013; 8:e57252. [PMID: 23472077 PMCID: PMC3589479 DOI: 10.1371/journal.pone.0057252] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2012] [Accepted: 01/18/2013] [Indexed: 11/18/2022] Open
Abstract
The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI) Early Alerting and Reporting (EAR) project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7-13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.
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Affiliation(s)
- Philippe Barboza
- International Department, French Institute for Public Health Surveillance (Institut de Veille Sanitaire), Saint Maurice, France.
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Reiner RC, Perkins TA, Barker CM, Niu T, Chaves LF, Ellis AM, George DB, Le Menach A, Pulliam JRC, Bisanzio D, Buckee C, Chiyaka C, Cummings DAT, Garcia AJ, Gatton ML, Gething PW, Hartley DM, Johnston G, Klein EY, Michael E, Lindsay SW, Lloyd AL, Pigott DM, Reisen WK, Ruktanonchai N, Singh BK, Tatem AJ, Kitron U, Hay SI, Scott TW, Smith DL. A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970-2010. J R Soc Interface 2013; 10:20120921. [PMID: 23407571 PMCID: PMC3627099 DOI: 10.1098/rsif.2012.0921] [Citation(s) in RCA: 239] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Mathematical models of mosquito-borne pathogen transmission originated in the early twentieth century to provide insights into how to most effectively combat malaria. The foundations of the Ross–Macdonald theory were established by 1970. Since then, there has been a growing interest in reducing the public health burden of mosquito-borne pathogens and an expanding use of models to guide their control. To assess how theory has changed to confront evolving public health challenges, we compiled a bibliography of 325 publications from 1970 through 2010 that included at least one mathematical model of mosquito-borne pathogen transmission and then used a 79-part questionnaire to classify each of 388 associated models according to its biological assumptions. As a composite measure to interpret the multidimensional results of our survey, we assigned a numerical value to each model that measured its similarity to 15 core assumptions of the Ross–Macdonald model. Although the analysis illustrated a growing acknowledgement of geographical, ecological and epidemiological complexities in modelling transmission, most models during the past 40 years closely resemble the Ross–Macdonald model. Modern theory would benefit from an expansion around the concepts of heterogeneous mosquito biting, poorly mixed mosquito-host encounters, spatial heterogeneity and temporal variation in the transmission process.
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Affiliation(s)
- Robert C Reiner
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
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Nelson NP, Yang L, Reilly AR, Hardin JE, Hartley DM. Event-based internet biosurveillance: relation to epidemiological observation. Emerg Themes Epidemiol 2012; 9:4. [PMID: 22709988 PMCID: PMC3493297 DOI: 10.1186/1742-7622-9-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2011] [Accepted: 06/06/2012] [Indexed: 11/24/2022] Open
Abstract
Background The World Health Organization (WHO) collects and publishes surveillance data and statistics for select diseases, but traditional methods of gathering such data are time and labor intensive. Event-based biosurveillance, which utilizes a variety of Internet sources, complements traditional surveillance. In this study we assess the reliability of Internet biosurveillance and evaluate disease-specific alert criteria against epidemiological data. Methods We reviewed and compared WHO epidemiological data and Argus biosurveillance system data for pandemic (H1N1) 2009 (April 2009 – January 2010) from 8 regions and 122 countries to: identify reliable alert criteria among 15 Argus-defined categories; determine the degree of data correlation for disease progression; and assess timeliness of Internet information. Results Argus generated a total of 1,580 unique alerts; 5 alert categories generated statistically significant (p < 0.05) correlations with WHO case count data; the sum of these 5 categories was highly correlated with WHO case data (r = 0.81, p < 0.0001), with expected differences observed among the 8 regions. Argus reported first confirmed cases on the same day as WHO for 21 of the first 64 countries reporting cases, and 1 to 16 days (average 1.5 days) ahead of WHO for 42 of those countries. Conclusion Confirmed pandemic (H1N1) 2009 cases collected by Argus and WHO methods returned consistent results and confirmed the reliability and timeliness of Internet information. Disease-specific alert criteria provide situational awareness and may serve as proxy indicators to event progression and escalation in lieu of traditional surveillance data; alerts may identify early-warning indicators to another pandemic, preparing the public health community for disease events.
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Affiliation(s)
- Noele P Nelson
- Department of Pediatrics, Georgetown University Medical Center, Washington, DC, 20007, USA.
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Hartley DM, Barker CM, Le Menach A, Niu T, Gaff HD, Reisen WK. Effects of temperature on emergence and seasonality of West Nile virus in California. Am J Trop Med Hyg 2012; 86:884-94. [PMID: 22556092 PMCID: PMC3335698 DOI: 10.4269/ajtmh.2012.11-0342] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2011] [Accepted: 02/04/2012] [Indexed: 11/07/2022] Open
Abstract
Temperature has played a critical role in the spatiotemporal dynamics of West Nile virus transmission throughout California from its introduction in 2003 through establishment by 2009. We compared two novel mechanistic measures of transmission risk, the temperature-dependent ratio of virus extrinsic incubation period to the mosquito gonotrophic period (BT), and the fundamental reproductive ratio (R(0)) based on a mathematical model, to analyze spatiotemporal patterns of receptivity to viral amplification. Maps of BT and R(0) were created at 20-km scale and compared throughout California to seroconversions in sentinel chicken flocks at half-month intervals. Overall, estimates of BT and R(0) agreed with intensity of transmission measured by the frequency of sentinel chicken seroconversions. Mechanistic measures such as these are important for understanding how temperature affects the spatiotemporal dynamics of West Nile virus transmission and for delineating risk estimates useful to inform vector control agency intervention decisions and communicate outbreak potential.
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Affiliation(s)
- David M Hartley
- Georgetown University Medical Center, Washington, District of Columbia 20057, USA.
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Corley CD, Lancaster MJ, Brigantic RT, Chung JS, Walters RA, Arthur RR, Bruckner-Lea CJ, Calapristi A, Dowling G, Hartley DM, Kennedy S, Kircher A, Klucking S, Lee EK, McKenzie T, Nelson NP, Olsen J, Pancerella C, Quitugua TN, Reed JT, Thomas CS. Assessing the continuum of event-based biosurveillance through an operational lens. Biosecur Bioterror 2012; 10:131-41. [PMID: 22320664 DOI: 10.1089/bsp.2011.0096] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This research follows the Updated Guidelines for Evaluating Public Health Surveillance Systems, Recommendations from the Guidelines Working Group, published by the Centers for Disease Control and Prevention nearly a decade ago. Since then, models have been developed and complex systems have evolved with a breadth of disparate data to detect or forecast chemical, biological, and radiological events that have a significant impact on the One Health landscape. How the attributes identified in 2001 relate to the new range of event-based biosurveillance technologies is unclear. This article frames the continuum of event-based biosurveillance systems (that fuse media reports from the internet), models (ie, computational that forecast disease occurrence), and constructs (ie, descriptive analytical reports) through an operational lens (ie, aspects and attributes associated with operational considerations in the development, testing, and validation of the event-based biosurveillance methods and models and their use in an operational environment). A workshop was held in 2010 to scientifically identify, develop, and vet a set of attributes for event-based biosurveillance. Subject matter experts were invited from 7 federal government agencies and 6 different academic institutions pursuing research in biosurveillance event detection. We describe 8 attribute families for the characterization of event-based biosurveillance: event, readiness, operational aspects, geographic coverage, population coverage, input data, output, and cost. Ultimately, the analyses provide a framework from which the broad scope, complexity, and relevant issues germane to event-based biosurveillance useful in an operational environment can be characterized.
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Affiliation(s)
- Courtney D Corley
- National Security Directorate, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
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Thomas CS, Nelson NP, Jahn GC, Niu T, Hartley DM. Use of media and public-domain Internet sources for detection and assessment of plant health threats. Emerg Health Threats J 2011; 4:7157. [PMID: 24149031 PMCID: PMC3168368 DOI: 10.3402/ehtj.v4i0.7157] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2011] [Revised: 06/30/2011] [Accepted: 07/26/2011] [Indexed: 12/04/2022]
Abstract
Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance.
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Affiliation(s)
- Carla S. Thomas
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
| | - Noele P. Nelson
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Pediatrics, Georgetown University Medical Center, Washington, DC, USA
| | - Gary C. Jahn
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
| | - Tianchan Niu
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
| | - David M. Hartley
- Division of Integrated Biodefense, Imaging Science and Information Systems, Georgetown University Medical Center, Washington, DC, USA
- Department of Radiology, Georgetown University Medical Center, Washington, DC, USA
- Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA
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Torii M, Yin L, Nguyen T, Mazumdar CT, Liu H, Hartley DM, Nelson NP. An exploratory study of a text classification framework for Internet-based surveillance of emerging epidemics. Int J Med Inform 2011; 80:56-66. [PMID: 21134784 PMCID: PMC3904285 DOI: 10.1016/j.ijmedinf.2010.10.015] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2010] [Revised: 09/20/2010] [Accepted: 10/19/2010] [Indexed: 11/15/2022]
Abstract
PURPOSE Early detection of infectious disease outbreaks is crucial to protecting the public health of a society. Online news articles provide timely information on disease outbreaks worldwide. In this study, we investigated automated detection of articles relevant to disease outbreaks using machine learning classifiers. In a real-life setting, it is expensive to prepare a training data set for classifiers, which usually consists of manually labeled relevant and irrelevant articles. To mitigate this challenge, we examined the use of randomly sampled unlabeled articles as well as labeled relevant articles. METHODS Naïve Bayes and Support Vector Machine (SVM) classifiers were trained on 149 relevant and 149 or more randomly sampled unlabeled articles. Diverse classifiers were trained by varying the number of sampled unlabeled articles and also the number of word features. The trained classifiers were applied to 15 thousand articles published over 15 days. Top-ranked articles from each classifier were pooled and the resulting set of 1337 articles was reviewed by an expert analyst to evaluate the classifiers. RESULTS Daily averages of areas under ROC curves (AUCs) over the 15-day evaluation period were 0.841 and 0.836, respectively, for the naïve Bayes and SVM classifier. We referenced a database of disease outbreak reports to confirm that this evaluation data set resulted from the pooling method indeed covered incidents recorded in the database during the evaluation period. CONCLUSIONS The proposed text classification framework utilizing randomly sampled unlabeled articles can facilitate a cost-effective approach to training machine learning classifiers in a real-life Internet-based biosurveillance project. We plan to examine this framework further using larger data sets and using articles in non-English languages.
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Affiliation(s)
- Manabu Torii
- The ISIS Center, Georgetown University Medical Center, Washington, DC, USA.
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Nelson NP, Brownstein JS, Hartley DM. Event-based biosurveillance of respiratory disease in Mexico, 2007–2009: connection to the 2009 influenza A(H1N1) pandemic? Euro Surveill 2010. [DOI: 10.2807/ese.15.30.19626-en] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Binary file ES_Abstracts_Final_ECDC.txt matches
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Affiliation(s)
- N P Nelson
- Georgetown University School of Medicine, Department of Paediatrics, Washington, DC, United States
| | - J S Brownstein
- Children's Hospital Boston and Harvard University Medical School, Boston, MA, United States
| | - D M Hartley
- Georgetown University School of Medicine, Department of Microbiology and Immunology and Department of Radiology, Washington, DC, United States
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Nelson NP, Brownstein JS, Hartley DM. Event-based biosurveillance of respiratory disease in Mexico, 2007-2009: connection to the 2009 influenza A(H1N1) pandemic? Euro Surveill 2010; 15:19626. [PMID: 20684815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023] Open
Abstract
The emergence of the 2009 pandemic influenza A(H1N1) virus in North America and its subsequent global spread highlights the public health need for early warning of infectious disease outbreaks. Event-based biosurveillance, based on local- and regional-level Internet media reports, is one approach to early warning as well as to situational awareness. This study analyses media reports in Mexico collected by the Argus biosurveillance system between 1 October 2007 and 31 May 2009. Results from Mexico are compared with the United States and Canadian media reports obtained from the HealthMap system. A significant increase in reporting frequency of respiratory disease in Mexico during the 2008-9 influenza season relative to that of 2007-8 was observed (p<0.0001). The timing of events, based on media reports, suggests that respiratory disease was prevalent in parts of Mexico, and was reported as unusual, much earlier than the microbiological identification of the pandemic virus. Such observations suggest that abnormal respiratory disease frequency and severity was occurring in Mexico throughout the winter of 2008-2009, though its connection to the emergence of the 2009 pandemic influenza A(H1N1) virus remains unclear.
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Affiliation(s)
- N P Nelson
- Department of Paediatrics, Georgetown University School of Medicine, Washington, DC, United States.
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Hartley DM, Nelson NP, Walters R, Arthur R, Yangarber R, Madoff L, Linge JP, Mawudeku A, Collier N, Brownstein JS, Thinus G, Lightfoot N. Landscape of international event-based biosurveillance. Emerg Health Threats J 2010; 3:e3. [PMID: 22460393 PMCID: PMC3167659 DOI: 10.3134/ehtj.10.003] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/09/2009] [Revised: 11/17/2009] [Accepted: 01/12/2010] [Indexed: 11/18/2022]
Abstract
Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.
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Affiliation(s)
- DM Hartley
- Imaging Science and Information Systems Center, Georgetown University School of Medicine, Washington, DC, USA
| | - NP Nelson
- Georgetown University School of Medicine, Washington, DC, USA
| | - R Walters
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - R Arthur
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - R Yangarber
- Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - L Madoff
- University of Massachusetts Medical School, Worcester, MA, USA
| | - JP Linge
- Joint Research Centre, European Commission, Ispra, Italy
| | - A Mawudeku
- Public Health Agency of Canada, Ottawa, Ontario, Canada
| | - N Collier
- National Institute of Informatics, Tokyo, Japan
| | - JS Brownstein
- Children's Hospital Boston, Harvard Medical School, Boston, MA, USA
| | - G Thinus
- Imaging Science and Information Systems Center, Georgetown University School of Medicine, Washington, DC, USA
| | - N Lightfoot
- Georgetown University School of Medicine, Washington, DC, USA
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Furuno JP, Harris AD, Wright MO, Hartley DM, McGregor JC, Gaff HD, Hebden JN, Standiford HC, Perencevich EN. Value of performing active surveillance cultures on intensive care unit discharge for detection of methicillin-resistant Staphylococcus aureus. Infect Control Hosp Epidemiol 2007; 28:666-70. [PMID: 17520538 DOI: 10.1086/518348] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2006] [Accepted: 11/08/2006] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To quantify the value of performing active surveillance cultures for detection of methicillin-resistant Staphylococcus aureus (MRSA) on intensive care unit (ICU) discharge. DESIGN Prospective cohort study. SETTING Medical ICU (MICU) and surgical ICU (SICU) of a tertiary care hospital. PARTICIPANTS We analyzed data on adult patients who were admitted to the MICU or SICU between January 17, 2001, and December 31, 2004. All participants had a length of ICU stay of at least 48 hours and had surveillance cultures of anterior nares specimens performed on ICU admission and discharge. Patients who had MRSA-positive clinical cultures in the ICU were excluded. RESULTS Of 2,918 eligible patients, 178 (6%) were colonized with MRSA on ICU admission, and 65 (2%) acquired MRSA in the ICU and were identified by results of discharge surveillance cultures. Patients with MRSA colonization confirmed by results of discharge cultures spent 853 days in non-ICU wards after ICU discharge, which represented 27% of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU. CONCLUSIONS Surveillance cultures of nares specimens collected at ICU discharge identified a large percentage of MRSA-colonized patients who would not have been identified on the basis of results of clinical cultures or admission surveillance cultures alone. Furthermore, these patients were responsible for a large percentage of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.
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Affiliation(s)
- Jon P Furuno
- Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
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Hartley DM, Klontz KC, Ryan P, Morris JG. Shigellosis and Cryptosporidiosis, Baltimore, Maryland. Emerg Infect Dis 2006; 12:1164-5. [PMID: 16845778 PMCID: PMC3291073 DOI: 10.3201/eid1207.060449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- David M. Hartley
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Karl C. Klontz
- The George Washington University School of Public Health and Health Services, Washington, DC, USA
- US Food and Drug Administration, College Park, Maryland, USA
| | - Patricia Ryan
- Maryland Department of Health and Mental Hygiene, Baltimore, Maryland, USA
| | - J. Glenn Morris
- University of Maryland School of Medicine, Baltimore, Maryland, USA
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Hartley DM, Furuno JP, Wright MO, Smith DL, Perencevich EN. The role of institutional epidemiologic weight in guiding infection surveillance and control in community and hospital populations. Infect Control Hosp Epidemiol 2006; 27:170-4. [PMID: 16465633 DOI: 10.1086/501052] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2005] [Accepted: 08/19/2005] [Indexed: 11/03/2022]
Abstract
BACKGROUND Institutions such as hospitals, prisons, and long-term care facilities have been identified as focal points for the transmission of emerging infections. Cost-effective control of these infections in large populations requires the identification of optimal subpopulations for targeted infection control interventions. Our objective was to quantify and compare the relative impact that individual institutions or subpopulations have on wider population-level outbreaks of emerging pathogens. DESIGN We describe a simple mathematical model to compute the epidemiologic weight (EW) of an institution or subpopulation. The EW represents the rate at which newly infectious individuals exit the institution under consideration. SETTING A hypothetical academic tertiary-care hospital (700 beds, 5-day length of stay [LOS]) and prison (3098 inmates, 27-day LOS). PATIENTS Individuals entering a hospital in-patient prison ward and nonprisoners entering both medical and surgical intensive-care units and those admitted to the general medical and surgical wards. RESULTS The recent example of the community-acquired methicillin-resistant Staphylococcus aureus epidemic is used to illustrate the EW calculation. Hospitals and prisons, which often have vastly dissimilar populations sizes and LOSs and might have differing transmission rates, can have comparable EWs and thus contribute equally to an epidemic in the community. CONCLUSIONS This method highlights the importance of measuring entrance and exit colonization prevalences for the optimal targeting of prevention measures. The EW not only identified superspreader institutions but also ranks them, enabling public health workers to optimize the allocation of resources to places where they are likely to be of most benefit.
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Affiliation(s)
- David M Hartley
- Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
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Abstract
BACKGROUND Cholera is an ancient disease that continues to cause epidemic and pandemic disease despite ongoing efforts to limit its spread. Mathematical models provide one means of assessing the utility of various proposed interventions. However, cholera models that have been developed to date have had limitations, suggesting that there are basic elements of cholera transmission that we still do not understand. METHODS AND FINDINGS Recent laboratory findings suggest that passage of Vibrio cholerae O1 Inaba El Tor through the gastrointestinal tract results in a short-lived, hyperinfectious state of the organism that decays in a matter of hours into a state of lower infectiousness. Incorporation of this hyperinfectious state into our disease model provides a much better fit with the observed epidemic pattern of cholera. These findings help to substantiate the clinical relevance of laboratory observations regarding the hyperinfectious state, and underscore the critical importance of human-to-human versus environment-to-human transmission in the generation of epidemic and pandemic disease. CONCLUSIONS To have maximal impact on limiting epidemic spread of cholera, interventions should be targeted toward minimizing risk of transmission of the short-lived, hyperinfectious form of toxigenic Vibrio cholerae. The possibility of comparable hyperinfectious states in other major epidemic diseases also needs to be evaluated and, as appropriate, incorporated into models of disease prevention.
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Affiliation(s)
- David M Hartley
- Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
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Brett MT, Arhonditsis GB, Mueller SE, Hartley DM, Frodge JD, Funke DE. Non-point-source impacts on stream nutrient concentrations along a forest to urban gradient. Environ Manage 2005; 35:330-42. [PMID: 15925975 DOI: 10.1007/s00267-003-0311-z] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We conducted statistical analyses of a 10-year record of stream nutrient and sediment concentrations for 17 streams in the greater Seattle region to determine the impact of urban non-point-source pollutants on stream water quality. These catchments are dominated by either urban (22-87%) or forest (6-73%) land cover, with no major nutrient point sources. Stream water phosphorus concentrations were moderately strongly (r2=0.58) correlated with catchment land-cover type, whereas nitrogen concentrations were weakly (r2=0.19) and nonsignificantly (at alpha<0.05) correlated with land cover. The most urban streams had, on average, 95% higher total phosphorus (TP) and 122% higher soluble reactive phosphorus (SRP) and 71% higher turbidity than the most forested streams. Nitrate (NO3), ammonium (NH4), and total suspended solids (TSS) concentrations did not vary significantly with land cover. These results suggest that urbanization markedly increased stream phosphorus concentrations and modestly increased nitrogen concentrations. However, nutrient concentrations in Seattle region urban streams are significantly less than those previously reported for agricultural area streams.
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Affiliation(s)
- Michael T Brett
- Department of Civil & Environmental EngineeringBox 352700, University of Washington, Seattle, Washington 98195, USA.
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Buehler JW, Berkelman RL, Hartley DM, Peters CJ. Syndromic Surveillance. Emerg Infect Dis 2004. [DOI: 10.3201/eid1007.040125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
| | | | - David M. Hartley
- University of Maryland School of Medicine, Baltimore, Maryland, USA
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Abstract
To facilitate rapid detection of a future bioterrorist attack, an increasing number of public health departments are investing in new surveillance systems that target the early manifestations of bioterrorism-related disease. Whether this approach is likely to detect an epidemic sooner than reporting by alert clinicians remains unknown. The detection of a bioterrorism-related epidemic will depend on population characteristics, availability and use of health services, the nature of an attack, epidemiologic features of individual diseases, surveillance methods, and the capacity of health departments to respond to alerts. Predicting how these factors will combine in a bioterrorism attack may be impossible. Nevertheless, understanding their likely effect on epidemic detection should help define the usefulness of syndromic surveillance and identify approaches to increasing the likelihood that clinicians recognize and report an epidemic.
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Affiliation(s)
- James W Buehler
- Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322, USA.
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Walsh DM, Hartley DM, Condron MM, Selkoe DJ, Teplow DB. In vitro studies of amyloid beta-protein fibril assembly and toxicity provide clues to the aetiology of Flemish variant (Ala692-->Gly) Alzheimer's disease. Biochem J 2001; 355:869-77. [PMID: 11311152 PMCID: PMC1221805 DOI: 10.1042/bj3550869] [Citation(s) in RCA: 93] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In a Flemish kindred, an Ala(692)-->Gly amino acid substitution in the amyloid beta-protein precursor (AbetaPP) causes a form of early-onset Alzheimer's disease (AD) which displays prominent amyloid angiopathy and unusually large senile plaque cores. The mechanistic basis of this Flemish form of AD is unknown. Previous in vitro studies of amyloid beta-protein (Abeta) production in HEK-293 cells transfected with cDNA encoding Flemish AbetaPP have shown that full-length [Abeta(1-40)] and truncated [Abeta(5-40) and Abeta(11-40)] forms of Abeta are produced. In an effort to determine how these peptides might contribute to the pathogenesis of the Flemish disease, comparative biophysical and neurotoxicity studies were performed on wild-type and Flemish Abeta(1-40), Abeta(5-40) and Abeta(11-40). The results revealed that the Flemish amino acid substitution increased the solubility of each form of peptide, decreased the rate of formation of thioflavin-T-positive assemblies, and increased the SDS-stability of peptide oligomers. Although the kinetics of peptide assembly were altered by the Ala(21)-->Gly substitution, all three Flemish variants formed fibrils, as did the wild-type peptides. Importantly, toxicity studies using cultured primary rat cortical cells showed that the Flemish assemblies were as potent a neurotoxin as were the wild-type assemblies. Our results are consistent with a pathogenetic process in which conformational changes in Abeta induced by the Ala(21)-->Gly substitution would facilitate peptide adherence to the vascular endothelium, creating nidi for amyloid growth. Increased peptide solubility and assembly stability would favour formation of larger deposits and inhibit their elimination. In addition, increased concentrations of neurotoxic assemblies would accelerate neuronal injury and death.
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Affiliation(s)
- D M Walsh
- Center for Neurologic Diseases, Brigham and Women's Hospital, 77 Avenue Louis Pasteur, Boston MA 02115, USA
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Fezoui Y, Hartley DM, Walsh DM, Selkoe DJ, Osterhout JJ, Teplow DB. A de novo designed helix-turn-helix peptide forms nontoxic amyloid fibrils. Nat Struct Biol 2000; 7:1095-9. [PMID: 11101888 DOI: 10.1038/81937] [Citation(s) in RCA: 112] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We report here that a monomeric de novo designed alpha-helix-turn-alpha-helix peptide, alpha t alpha, when incubated at 37 degrees C in an aqueous buffer at neutral pH, forms nonbranching, protease resistant fibrils that are 6-10 nm in diameter. These fibrils are rich in beta-sheet and bind the amyloidophilic dye Congo red. alpha t alpha fibrils thus display the morphologic, structural, and tinctorial properties of authentic amyloid fibrils. Surprisingly, unlike fibrils formed by peptides such as the amyloid beta-protein or the islet amyloid polypeptide, alpha t alpha fibrils were not toxic to cultured rat primary cortical neurons or PC12 cells. These results suggest that the potential to form fibrils under physiologic conditions is not limited to those proteins associated with amyloidoses and that fibril formation alone is not predictive of cytotoxic activity.
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Affiliation(s)
- Y Fezoui
- Department of Neurology (Neuroscience), Harvard Medical School, Boston, Massachusetts 02115, USA.
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Fezoui Y, Hartley DM, Harper JD, Khurana R, Walsh DM, Condron MM, Selkoe DJ, Lansbury PT, Fink AL, Teplow DB. An improved method of preparing the amyloid beta-protein for fibrillogenesis and neurotoxicity experiments. Amyloid 2000; 7:166-78. [PMID: 11019857 DOI: 10.3109/13506120009146831] [Citation(s) in RCA: 208] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Synthetic amyloid beta-protein (A beta) is used widely to study fibril formation and the physiologic effects of low molecular weight and fibrillar forms of the peptide on cells in culture or in experimental animals. Not infrequently, conflicting results have arisen in these studies, in part due to variation in the starting conformation and assembly state of A beta. To avoid these problems, we sought a simple, reliable means of preparing A beta for experimental use. We found that solvation of synthetic peptide with sodium hydroxide (A beta x NaOH), followed by lyophilization, produced stocks with superior solubility and fibrillogenesis characteristics. Solubilization of the pretreated material with neutral buffers resulted in a pH transition from approximately 10.5 to neutral, avoiding the isoelectric point of A beta (pI approximately 5.5), at which A beta precipitation and aggregation propensity are maximal. Relative to trifluoroacetate (A beta x TFA) or hydrochloric acid (A beta x HCl) salts of A beta, yields of "low molecular weight A beta" (monomers and/or dimers) were improved significantly by NaOH pretreatment. Time-dependent changes in circular dichroism spectra and Congo red dye-binding showed that A beta x NaOH formed fibrils more readily than did the other A beta preparations and that these fibrils were equally neurotoxic. NaOH pretreatment thus offers advantages for the preparation of A beta for biophysical and physiologic studies.
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Affiliation(s)
- Y Fezoui
- Center for Neurologic Diseases, Brigham and Women's Hospital, and Department of Neurology, Harvard Medical School, Boston, MA 02215, USA
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