A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making
Abstract Introduction The United States has been unsuccessful in containing the rapid spread of COVID‐19. The complex epidemiology of the disease and the fragmented response to it has resulted in thousands of ways in which spread has occurred, creating a situation where each community needs to creat...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-04-01
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| Series: | Learning Health Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/lrh2.10295 |
| _version_ | 1818018935143923712 |
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| author | Margaret Holly Sophia Bartels Ninon Lewis Paul Howard Rohit Ramaswamy |
| author_facet | Margaret Holly Sophia Bartels Ninon Lewis Paul Howard Rohit Ramaswamy |
| author_sort | Margaret Holly |
| collection | DOAJ |
| description | Abstract Introduction The United States has been unsuccessful in containing the rapid spread of COVID‐19. The complex epidemiology of the disease and the fragmented response to it has resulted in thousands of ways in which spread has occurred, creating a situation where each community needs to create its own local, context‐specific learning model while remaining compliant to county or state mandates. Methods In this paper, we demonstrate how cross sector collaborations can use the Cynefin Framework, a tool for decision‐making in complex systems, to guide community response to the COVID‐19 pandemic. Results We explore circumstances under which communities can inhabit each of the four domains of systems complexity represented in the Cynefin framework: simple, complicated, chaotic, and complex, and describe the decision‐making process in each domain that balances health, economic, and social well‐being. Conclusion This paper serves as a call to action for the creation of community learning systems to improve community resilience and capacity to make better‐informed decisions to address complex public health problems during the pandemic and beyond. |
| first_indexed | 2024-04-14T07:46:06Z |
| format | Article |
| id | doaj.art-78541796f1d249b082bf9d7f70429b6e |
| institution | Directory Open Access Journal |
| issn | 2379-6146 |
| language | English |
| last_indexed | 2024-04-14T07:46:06Z |
| publishDate | 2022-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Learning Health Systems |
| spelling | doaj.art-78541796f1d249b082bf9d7f70429b6e2022-12-22T02:05:20ZengWileyLearning Health Systems2379-61462022-04-0162n/an/a10.1002/lrh2.10295A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐makingMargaret Holly0Sophia Bartels1Ninon Lewis2Paul Howard3Rohit Ramaswamy4Department of Health Policy and Management Gillings School of Global Public Health, University of North Carolina at Chapel Hill Chapel Hill North Carolina USADepartment of Health Behavior Gillings School of Global Public Health, University of North Carolina at Chapel Hill Chapel Hill North Carolina USAInstitute for Healthcare Improvement Boston Massachusetts USAInstitute for Healthcare Improvement Boston Massachusetts USADepartment of Maternal and Child Health, Gillings School of Global Public Health University of North Carolina at Chapel Hill Chapel Hill North Carolina USAAbstract Introduction The United States has been unsuccessful in containing the rapid spread of COVID‐19. The complex epidemiology of the disease and the fragmented response to it has resulted in thousands of ways in which spread has occurred, creating a situation where each community needs to create its own local, context‐specific learning model while remaining compliant to county or state mandates. Methods In this paper, we demonstrate how cross sector collaborations can use the Cynefin Framework, a tool for decision‐making in complex systems, to guide community response to the COVID‐19 pandemic. Results We explore circumstances under which communities can inhabit each of the four domains of systems complexity represented in the Cynefin framework: simple, complicated, chaotic, and complex, and describe the decision‐making process in each domain that balances health, economic, and social well‐being. Conclusion This paper serves as a call to action for the creation of community learning systems to improve community resilience and capacity to make better‐informed decisions to address complex public health problems during the pandemic and beyond.https://doi.org/10.1002/lrh2.10295community learningCynefin frameworkdecision‐making in complex systems |
| spellingShingle | Margaret Holly Sophia Bartels Ninon Lewis Paul Howard Rohit Ramaswamy A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making Learning Health Systems community learning Cynefin framework decision‐making in complex systems |
| title | A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making |
| title_full | A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making |
| title_fullStr | A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making |
| title_full_unstemmed | A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making |
| title_short | A learning approach to community response during the COVID‐19 pandemic: Applying the Cynefin framework to guide decision‐making |
| title_sort | learning approach to community response during the covid 19 pandemic applying the cynefin framework to guide decision making |
| topic | community learning Cynefin framework decision‐making in complex systems |
| url | https://doi.org/10.1002/lrh2.10295 |
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