Silverman, E. (2018) Bringing ALife and complex systems science to population health research. Artificial Life, 24(3), pp. 220-223. (doi: 10.1162/artl_a_00264) (PMID:30485143)
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Abstract
Despite tremendous advancements in population health in recent history, human society currently faces significant challenges from wicked health problems. These are problems where the causal mechanisms at play are obscured and difficult to address, and consequently they have defied efforts to develop effective interventions and policy solutions using traditional population health methods. Systems-based perspectives are vital to the development of effective policy solutions to seemingly intractable health problems like obesity and population aging. ALife in particular is well placed to bring interdisciplinary modeling and simulation approaches to bear on these challenges. This article summarizes the current status of systems-based approaches in population health, and outlines the opportunities that are available for ALife to make a significant contribution to these critical issues.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | No |
| Glasgow Author(s) Enlighten ID: | Silverman, Dr Eric |
| Authors: | Silverman, E. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU |
| Journal Name: | Artificial Life |
| Publisher: | MIT Press |
| ISSN: | 1064-5462 |
| ISSN (Online): | 1530-9185 |
| Published Online: | 28 November 2018 |
| Copyright Holders: | Copyright © 2018 Massachusetts Institute of Technology |
| First Published: | First published in Artificial Life 24(3):220-223 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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