Modeling differential effects of health interventions across a heterogeneous population
Abstract/Contents
- Abstract
- Populations comprising individuals with varying characteristics and needs presents a challenge to public health decision making, as people may benefit from (or be harmed by) policies to differing extents. This dissertation focuses on mathematical modeling approaches to assess the differential effects of public health interventions across heterogeneous populations and inform policy decisions. First, we develop a microsimulation model to project the impact of increased meat price on dietary consumption, obesity and mortality by sex and race. We find that increased meat price would likely reduce obesity prevalence for white males, black males, and black females, far more than for white females. We also identify black males as least likely to experience gains in life expectancy from such a price increase. Next, we create a dynamic compartmental model of the population, stratified by pain, opioid use, and opioid addiction status, to estimate the ten-year impact of 11 interventions in response to the US opioid epidemic. We find that policies that reduce the prescription opioid supply may increase heroin use and reduce quality of life in the short term, but in the long term could generate positive health benefits. Policies focused on treating addiction (or mitigating its impact) improve health without causing harm, but alone, these will not stem the epidemic. A portfolio of interventions will be needed for eventual mitigation. Finally, we offer a framework for categorizing health interventions according to the expected distribution of benefit and harm to aid decision makers in identifying tradeoffs between efficiency, equity, and harm avoidance.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Pitt, Allison Laurene |
|---|---|
| Degree supervisor | Brandeau, Margaret L |
| Thesis advisor | Brandeau, Margaret L |
| Thesis advisor | Bendavid, Eran |
| Thesis advisor | Owens, Douglas K |
| Degree committee member | Bendavid, Eran |
| Degree committee member | Owens, Douglas K |
| Associated with | Stanford University, Department of Management Science and Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Allison Laurene Pitt. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Allison Laurene Pitt
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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