A Complexity Lens on the COVID-19 Pandemic

Document Type : Viewpoint

Authors

1 Geneva Transformative Governance Lab, Global Studies Institute, University of Geneva, Geneva, Switzerland

2 School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China

3 Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland

4 Geneva Centre of Humanitarian Studies, Faculty of Medicine, University of Geneva and Graduate Institute of International and Development Studies, Geneva, Switzerland

5 Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada

6 Infection Control Programme, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland

7 Bren School of Environmental Science and Management, University of California at Santa Barbara, Santa Barbara, CA, USA

Keywords

Main Subjects

Full Text

Introduction

The most striking feature of the coronavirus disease 2019 (COVID-19) pandemic and associated responses is its social and ecological complexity. Applying a complexity lens can improve our understanding of the current COVID-19 pandemic but how can this best be done? Complexity science is not a unified theory but rather a collection of concepts, theories, and methods that are increasingly influencing a range of scholarly disciplines. Complex systems can be simply defined as “co-evolving multilayer networks.”1... (Read more...)

References

  1. Thurner S, Klimek P, Hanel R. Introduction to the Theory of Complex Systems. Oxford: Oxford University Press; 2018.
  2. Maani N, Galea S. COVID-19 and underinvestment in the public health infrastructure of the United States. Milbank Q. 2020;98(2):250-259. doi:10.1111/1468-0009.12463
  3. Baum F, Freeman T, Musolino C, et al. Explaining covid-19 performance: what factors might predict national responses? BMJ. 2021;372:n91. doi:10.1136/bmj.n91
  4. Frieden TR, Lee CT. Identifying and interrupting superspreading events-implications for control of severe acute respiratory syndrome coronavirus 2. Emerg Infect Dis. 2020;26(6):1059-1066. doi:10.3201/eid2606.200495
  5. Centola D. How Behavior Spreads: The Science of Complex Contagions. Princeton, NJ: Princeton University Press; 2018.
  6. Bauch CT, Galvani AP. Epidemiology. Social factors in epidemiology. Science. 2013;342(6154):47-49. doi:10.1126/science.1244492
  7. Ren XL, Gleinig N, Helbing D, Antulov-Fantulin N. Generalized network dismantling. Proc Natl Acad Sci U S A. 2019;116(14):6554-6559. doi:10.1073/pnas.1806108116
  8. Baumann M, Beier M, Brinkmann M, et al. A proactive approach to fight SARS-CoV-2 in Germany and Europe. Psycho-social Impact of the COVID-19 Pandemic Project. 2021.
  9. Taylor L. Covid-19: Brazil's hospitals close to collapse as cases reach record high. BMJ. 2021;372:n800. doi:10.1136/bmj.n800
  10. Tran PB, Hensing G, Wingfield T, et al. Income security during public health emergencies: the COVID-19 poverty trap in Vietnam. BMJ Glob Health. 2020;5(6):e002504. doi:10.1136/bmjgh-2020-002504
  11. Watts DJ. A simple model of global cascades on random networks. Proc Natl Acad Sci U S A. 2002;99(9):5766-5771. doi:10.1073/pnas.082090499
  12. Rajan D, Koch K, Rohrer K, et al. Governance of the Covid-19 response: a call for more inclusive and transparent decision-making. BMJ Glob Health. 2020;5(5):e002655. doi:10.1136/bmjgh-2020-002655
  13. Folke C. Resilience (republished). Ecol Soc. 2016;21(4):44. doi:10.5751/ES-09088-210444
  14. Legido-Quigley H, Asgari N, Teo YY, et al. Are high-performing health systems resilient against the COVID-19 epidemic? Lancet. 2020;395(10227):848-850. doi:10.1016/s0140-6736(20)30551-1
  15. Guasti P. The impact of the Covid-19 pandemic in Central and Eastern Europe: the rise of autocracy and democratic resilience. Democr Theory. 2020;7(2):47-60. doi:10.3167/dt.2020.070207
  16. Solé R, Elena SF. Viruses as Complex Adaptive Systems. Princeton, NJ: Princeton University Press; 2018.
  17. Medley GF, Vassall A. When an emerging disease becomes endemic. Science. 2017;357(6347):156-158. doi:10.1126/science.aam8333
  18. Young OR. Governing Complex Systems: Social Capital for the Anthropocene. Cambridge, MA: MIT Press; 2017.
  19. Diamond J. Upheaval: Turning Points for Nations in Crisis. Little, Brown; 2019.
  20. Runge J, Bathiany S, Bollt E, et al. Inferring causation from time series in Earth system sciences. Nat Commun. 2019;10(1):2553. doi:10.1038/s41467-019-10105-3
  21. Shea K, Runge MC, Pannell D, et al. Harnessing multiple models for outbreak management. Science. 2020;368(6491):577-579. doi:10.1126/science.abb9934
  22. Wernli D, Jørgensen PS, Parmley EJ, et al. Evidence for action: a One Health learning platform on interventions to tackle antimicrobial resistance. Lancet Infect Dis. 2020;20(12):e307-e311. doi:10.1016/s1473-3099(20)30392-3
International Journal of Health Policy and Management

Articles in Press, Corrected Proof
Available Online from 26 May 2021

Files

History

  • Receive Date: 21 August 2020
  • Revise Date: 29 April 2021
  • Accept Date: 30 April 2021

Share

How to cite

Statistics