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What a difference a stochastic process makes : epidemiological-based real options models of optimal treatment of disease
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Dangerfield, C. E., Whalley, A. Elizabeth, Hanley, N. and Gilligan, C. A. (2018) What a difference a stochastic process makes : epidemiological-based real options models of optimal treatment of disease. Environmental and Resource Economics, 70 (3). pp. 691-711. doi:10.1007/s10640-017-0168-x
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Official URL: http://dx.doi.org/10.1007/s10640-017-0168-x
Abstract
The real options approach has been used within environmental economics to investigate the impact of uncertainty on the optimal timing of control measures to minimise the impacts of invasive species, including pests and diseases. Previous studies typically model the growth in infected area using geometric Brownian motion (GBM). The advantage of this simple approach is that it allows for closed form solutions. However, such a process does not capture the mechanisms underlying the spread of infection. In particular the GBM assumption does not respect the natural upper boundary of the system, which is determined by the maximum size of the host species, nor the deceleration in the rate of infection as this boundary is approached. We show how the stochastic process describing the growth in infected area can be derived from the characteristics of the spread of infection. If the model used does not appropriately capture uncertainty in infection dynamics, then the excessive delay before treatment implies that the full value of the option to treat is not realised. Indeed, when uncertainty is high or the disease is fast spreading, ignoring the mechanisms of infection spread can lead to control never being deployed. Thus the results presented here have important implications for the way in which the real options approach is applied to determine optimal timing of disease control given uncertainty in future disease progression.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QH Natural history R Medicine > RA Public aspects of medicine S Agriculture > SB Plant culture |
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| Divisions: | Faculty of Social Sciences > Warwick Business School | ||||||||
| Library of Congress Subject Headings (LCSH): | Introduced organisms -- Control -- Mathematical models, Pests -- Control -- Mathematical models, Diseases -- Control -- Mathematical models, Stochastic processes | ||||||||
| Journal or Publication Title: | Environmental and Resource Economics | ||||||||
| Publisher: | Springer | ||||||||
| ISSN: | 0924-6460 | ||||||||
| Official Date: | July 2018 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 31 July 2017 | ||||||||
| Volume: | 70 | ||||||||
| Number: | 3 | ||||||||
| Page Range: | pp. 691-711 | ||||||||
| DOI: | 10.1007/s10640-017-0168-x | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| Funder: | Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Great Britain. Department for Environment, Food and Rural Affairs (DEFRA), Economic and Social Research Council (Great Britain) (ESRC), Great Britain. Forestry Commission, Natural Environment Research Council (Great Britain) (NERC), Scotland. Scottish Government | ||||||||
| Grant number: | BB/L012561/ (BBSRC) |
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