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| Content Provider | ACM Digital Library |
|---|---|
| Author | Arora, Hina Raghu, T. S. Vinze, Ajay |
| Copyright Year | 2011 |
| Abstract | This research addresses complexities inherent in dynamic decision making settings represented by global disasters such as influenza pandemics. By coupling a theoretically grounded Equation-Based Modeling (EBM) approach with more practically nuanced Agent-Based Modeling (ABM) approach we address the inherent heterogeneity of the “influenza pandemic” decision space more effectively. In addition to modeling contributions, results and findings of this study have three important policy implications for pandemic containment; first, an effective way of checking the progression of a pandemic is a multipronged approach that includes a combination of pharmaceutical and non-pharmaceutical interventions. Second, mutual aid is effective only when regions that have been affected by the pandemic are sufficiently isolated from other regions through non-pharmaceutical interventions. When regions are not sufficiently isolated, mutual aid can in fact be detrimental. Finally, intraregion non-pharmaceutical interventions such as school closures are more effective than interregion nonpharmaceutical interventions such as border closures. |
| Starting Page | 1 |
| Ending Page | 25 |
| Page Count | 25 |
| File Format | |
| ISSN | 2158656X |
| DOI | 10.1145/2070710.2070714 |
| Volume Number | 2 |
| Issue Number | 4 |
| Journal | ACM Transactions on Management Information Systems (TMIS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-01-05 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Dynamic decision making Multiagent simulation Pandemics Public health Resource allocation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Management Information Systems Computer Science |
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