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COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

Disaster medicine and public health preparedness

Links JM, Schwartz BS, Lin S, Kanarek N, Mitrani-Reiser J, Sell TK, Watson CR, Ward D, Slemp C, Burhans R, Gill K, Igusa T, Zhao X, Aguirre B, Trainor J, Nigg J, Inglesby T, Carbone E, Kendra JM.
PMID: 28633681
Disaster Med Public Health Prep. 2018 Feb;12(1):127-137. doi: 10.1017/dmp.2017.39. Epub 2017 Jun 21.

OBJECTIVE: Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a...

Cite
Links JM, Schwartz BS, Lin S, et al. COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster Med Public Health Prep. 2017;12(1):127-137doi: 10.1017/dmp.2017.39.
Links, J. M., Schwartz, B. S., Lin, S., Kanarek, N., Mitrani-Reiser, J., Sell, T. K., Watson, C. R., Ward, D., Slemp, C., Burhans, R., Gill, K., Igusa, T., Zhao, X., Aguirre, B., Trainor, J., Nigg, J., Inglesby, T., Carbone, E., & Kendra, J. M. (2018). COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster medicine and public health preparedness, 12(1), 127-137. https://doi.org/10.1017/dmp.2017.39
Links, Jonathan M, et al. "COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters." Disaster medicine and public health preparedness vol. 12,1 (2018): 127-137. doi: https://doi.org/10.1017/dmp.2017.39
Links JM, Schwartz BS, Lin S, Kanarek N, Mitrani-Reiser J, Sell TK, Watson CR, Ward D, Slemp C, Burhans R, Gill K, Igusa T, Zhao X, Aguirre B, Trainor J, Nigg J, Inglesby T, Carbone E, Kendra JM. COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster Med Public Health Prep. 2018 Feb;12(1):127-137. doi: 10.1017/dmp.2017.39. Epub 2017 Jun 21. PMID: 28633681; PMCID: PMC8743042.
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Complexity Science, Nursing, and COVID-19.

The American journal of nursing

White KR, Begun JW, Vicenzi AE.
PMID: 33755603
Am J Nurs. 2021 Apr 01;121(4):11. doi: 10.1097/01.NAJ.0000742420.41614.78.

Understanding a bewildering crisis like a pandemic as 'normal' may be empowering.

Cite
White KR, Begun JW, Vicenzi AE. Complexity Science, Nursing, and COVID-19. Am J Nurs. 2021;121(4):11doi: 10.1097/01.NAJ.0000742420.41614.78.
White, K. R., Begun, J. W., & Vicenzi, A. E. (2021). Complexity Science, Nursing, and COVID-19. The American journal of nursing, 121(4), 11. https://doi.org/10.1097/01.NAJ.0000742420.41614.78
White, Kenneth R, et al. "Complexity Science, Nursing, and COVID-19." The American journal of nursing vol. 121,4 (2021): 11. doi: https://doi.org/10.1097/01.NAJ.0000742420.41614.78
White KR, Begun JW, Vicenzi AE. Complexity Science, Nursing, and COVID-19. Am J Nurs. 2021 Apr 01;121(4):11. doi: 10.1097/01.NAJ.0000742420.41614.78. PMID: 33755603.
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COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

Disaster medicine and public health preparedness

Links JM, Schwartz BS, Lin S, Kanarek N, Mitrani-Reiser J, Sell TK, Watson CR, Ward D, Slemp C, Burhans R, Gill K, Igusa T, Zhao X, Aguirre B, Trainor J, Nigg J, Inglesby T, Carbone E, Kendra JM.
PMID: 28633681
Disaster Med Public Health Prep. 2018 Feb;12(1):127-137. doi: 10.1017/dmp.2017.39. Epub 2017 Jun 21.

OBJECTIVE: Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a...

Cite
Links JM, Schwartz BS, Lin S, et al. COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster Med Public Health Prep. 2017;12(1):127-137doi: 10.1017/dmp.2017.39.
Links, J. M., Schwartz, B. S., Lin, S., Kanarek, N., Mitrani-Reiser, J., Sell, T. K., Watson, C. R., Ward, D., Slemp, C., Burhans, R., Gill, K., Igusa, T., Zhao, X., Aguirre, B., Trainor, J., Nigg, J., Inglesby, T., Carbone, E., & Kendra, J. M. (2018). COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster medicine and public health preparedness, 12(1), 127-137. https://doi.org/10.1017/dmp.2017.39
Links, Jonathan M, et al. "COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters." Disaster medicine and public health preparedness vol. 12,1 (2018): 127-137. doi: https://doi.org/10.1017/dmp.2017.39
Links JM, Schwartz BS, Lin S, Kanarek N, Mitrani-Reiser J, Sell TK, Watson CR, Ward D, Slemp C, Burhans R, Gill K, Igusa T, Zhao X, Aguirre B, Trainor J, Nigg J, Inglesby T, Carbone E, Kendra JM. COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters. Disaster Med Public Health Prep. 2018 Feb;12(1):127-137. doi: 10.1017/dmp.2017.39. Epub 2017 Jun 21. PMID: 28633681; PMCID: PMC8743042.
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Systems-based practice in graduate medical education: systems thinking as the missing foundational construct.

Teaching and learning in medicine

Colbert CY, Ogden PE, Ownby AR, Bowe C.
PMID: 21516607
Teach Learn Med. 2011 Apr;23(2):179-85. doi: 10.1080/10401334.2011.561758.

BACKGROUND: Since 2001, residencies have struggled with teaching and assessing systems-based practice (SBP). One major obstacle may be that the competency alone is not sufficient to support assessment. We believe the foundational construct underlying SBP is systems thinking, absent...

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Colbert CY, Ogden PE, Ownby AR, et al. Systems-based practice in graduate medical education: systems thinking as the missing foundational construct. Teach Learn Med. 2011;23(2):179-85doi: 10.1080/10401334.2011.561758.
Colbert, C. Y., Ogden, P. E., Ownby, A. R., & Bowe, C. (2011). Systems-based practice in graduate medical education: systems thinking as the missing foundational construct. Teaching and learning in medicine, 23(2), 179-85. https://doi.org/10.1080/10401334.2011.561758
Colbert, Colleen Y, et al. "Systems-based practice in graduate medical education: systems thinking as the missing foundational construct." Teaching and learning in medicine vol. 23,2 (2011): 179-85. doi: https://doi.org/10.1080/10401334.2011.561758
Colbert CY, Ogden PE, Ownby AR, Bowe C. Systems-based practice in graduate medical education: systems thinking as the missing foundational construct. Teach Learn Med. 2011 Apr;23(2):179-85. doi: 10.1080/10401334.2011.561758. PMID: 21516607.
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Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach.

Medical decision making : an international journal of the Society for Medical Decision Making

Zwick ED, Pepperell CS, Alagoz O.
PMID: 33904344
Med Decis Making. 2021 Aug;41(6):641-652. doi: 10.1177/0272989X211007842. Epub 2021 Apr 27.

OBJECTIVE: A recent study reported a tuberculosis (TB) outbreak in which, among newly infected individuals, exposure to additional active infections was associated with a higher probability of developing active disease. Referred to as METHODS: We built an ABM of...

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Zwick ED, Pepperell CS, Alagoz O. Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach. Med Decis Making. 2021;41(6):641-652doi: 10.1177/0272989X211007842.
Zwick, E. D., Pepperell, C. S., & Alagoz, O. (2021). Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach. Medical decision making : an international journal of the Society for Medical Decision Making, 41(6), 641-652. https://doi.org/10.1177/0272989X211007842
Zwick, Erin D, et al. "Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach." Medical decision making : an international journal of the Society for Medical Decision Making vol. 41,6 (2021): 641-652. doi: https://doi.org/10.1177/0272989X211007842
Zwick ED, Pepperell CS, Alagoz O. Representing Tuberculosis Transmission with Complex Contagion: An Agent-Based Simulation Modeling Approach. Med Decis Making. 2021 Aug;41(6):641-652. doi: 10.1177/0272989X211007842. Epub 2021 Apr 27. PMID: 33904344; PMCID: PMC8295181.
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Complex systems analysis by integrative omics.

Blood

Thongboonkerd V.
PMID: 34914830
Blood. 2021 Dec 16;138(24):2448-2450. doi: 10.1182/blood.2021012974.

No abstract available.

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Thongboonkerd V. Complex systems analysis by integrative omics. Blood. 2021;138(24):2448-2450doi: 10.1182/blood.2021012974.
Thongboonkerd, V. (2021). Complex systems analysis by integrative omics. Blood, 138(24), 2448-2450. https://doi.org/10.1182/blood.2021012974
Thongboonkerd, Visith. "Complex systems analysis by integrative omics." Blood vol. 138,24 (2021): 2448-2450. doi: https://doi.org/10.1182/blood.2021012974
Thongboonkerd V. Complex systems analysis by integrative omics. Blood. 2021 Dec 16;138(24):2448-2450. doi: 10.1182/blood.2021012974. PMID: 34914830.
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Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic.

History and philosophy of the life sciences

Maziarz M, Zach M.
PMID: 33471199
Hist Philos Life Sci. 2021 Jan 20;43(1):10. doi: 10.1007/s40656-020-00357-4.

Agent-based models (ABMs) are one of the main sources of evidence for decisions regarding mitigation and suppression measures against the spread of SARS-CoV-2. These models have not been previously included in the hierarchy of evidence put forth by the...

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Maziarz M, Zach M. Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic. Hist Philos Life Sci. 2021;43(1):10doi: 10.1007/s40656-020-00357-4.
Maziarz, M., & Zach, M. (2021). Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic. History and philosophy of the life sciences, 43(1), 10. https://doi.org/10.1007/s40656-020-00357-4
Maziarz, Mariusz, and Zach, Martin. "Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic." History and philosophy of the life sciences vol. 43,1 (2021): 10. doi: https://doi.org/10.1007/s40656-020-00357-4
Maziarz M, Zach M. Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic. Hist Philos Life Sci. 2021 Jan 20;43(1):10. doi: 10.1007/s40656-020-00357-4. PMID: 33471199; PMCID: PMC7816743.
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Systematic analysis for the relationship between obesity and tuberculosis.

Public health

Chachaima-Mar J, Sánchez-Velazco D, Ugarte-Gil C.
PMID: 34088511
Public Health. 2021 Sep;198:e5-e6. doi: 10.1016/j.puhe.2021.03.026. Epub 2021 Jun 02.

No abstract available.

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Chachaima-Mar J, Sánchez-Velazco D, Ugarte-Gil C. Systematic analysis for the relationship between obesity and tuberculosis. Public Health. 2021;198:e5-e6doi: 10.1016/j.puhe.2021.03.026.
Chachaima-Mar, J., Sánchez-Velazco, D., & Ugarte-Gil, C. (2021). Systematic analysis for the relationship between obesity and tuberculosis. Public health, 198e5-e6. https://doi.org/10.1016/j.puhe.2021.03.026
Chachaima-Mar, J, et al. "Systematic analysis for the relationship between obesity and tuberculosis." Public health vol. 198 (2021): e5-e6. doi: https://doi.org/10.1016/j.puhe.2021.03.026
Chachaima-Mar J, Sánchez-Velazco D, Ugarte-Gil C. Systematic analysis for the relationship between obesity and tuberculosis. Public Health. 2021 Sep;198:e5-e6. doi: 10.1016/j.puhe.2021.03.026. Epub 2021 Jun 02. PMID: 34088511.
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Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support.

BMC health services research

McGrath SP, MacKenzie T, Perreard I, Blike G.
PMID: 34416882
BMC Health Serv Res. 2021 Aug 20;21(1):843. doi: 10.1186/s12913-021-06855-w.

BACKGROUND: Allocation of limited resources to improve quality, patient safety, and outcomes is a decision-making challenge health care leaders face every day. While much valuable health care management research has concentrated on administrative data analysis, this approach often falls...

Cite
McGrath SP, MacKenzie T, Perreard I, et al. Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support. BMC Health Serv Res. 2021;21(1):843doi: 10.1186/s12913-021-06855-w.
McGrath, S. P., MacKenzie, T., Perreard, I., & Blike, G. (2021). Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support. BMC health services research, 21(1), 843. https://doi.org/10.1186/s12913-021-06855-w
McGrath, Susan P, et al. "Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support." BMC health services research vol. 21,1 (2021): 843. doi: https://doi.org/10.1186/s12913-021-06855-w
McGrath SP, MacKenzie T, Perreard I, Blike G. Characterizing rescue performance in a tertiary care medical center: a systems approach to provide management decision support. BMC Health Serv Res. 2021 Aug 20;21(1):843. doi: 10.1186/s12913-021-06855-w. PMID: 34416882; PMCID: PMC8379722.
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Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach.

Epidemics

Farthing TS, Lanzas C.
PMID: 34798545
Epidemics. 2021 Dec;37:100524. doi: 10.1016/j.epidem.2021.100524. Epub 2021 Nov 12.

Nonpharmaceutical interventions for minimizing indoor SARS-CoV-2 transmission continue to be critical tools for protecting susceptible individuals from infection, even as effective vaccines are produced and distributed globally. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission...

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Farthing TS, Lanzas C. Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach. Epidemics. 2021;37:100524doi: 10.1016/j.epidem.2021.100524.
Farthing, T. S., & Lanzas, C. (2021). Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach. Epidemics, 37100524. https://doi.org/10.1016/j.epidem.2021.100524
Farthing, Trevor S, and Lanzas, Cristina. "Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach." Epidemics vol. 37 (2021): 100524. doi: https://doi.org/10.1016/j.epidem.2021.100524
Farthing TS, Lanzas C. Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach. Epidemics. 2021 Dec;37:100524. doi: 10.1016/j.epidem.2021.100524. Epub 2021 Nov 12. PMID: 34798545; PMCID: PMC8588587.
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Showing 361 to 370 of 370 entries