ORCID Profile
0000-0002-9237-7731
Current Organisation
Australian National University
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Publisher: Wiley
Date: 24-10-2021
DOI: 10.1002/EAP.2449
Abstract: Trade‐offs exist between the point of early detection and the future cost of controlling any invasive species. Finding optimal levels of early detection, with post‐border active surveillance, where time, space and randomness are explicitly considered, is computationally challenging. We use a stochastic programming model to find the optimal level of surveillance and predict damages, easing the computational challenge by combining a s le average approximation (SAA) approach and parallel processing techniques. The model is applied to the case of Asian Papaya Fruit Fly (PFF), a highly destructive pest, in Queensland, Australia. To capture the non‐linearity in PFF spread, we use an agent‐based model (ABM), which is calibrated to a highly detailed land‐use raster map (50 m × 50 m) and weather‐related data, validated against a historical outbreak. The combination of SAA and ABM sets our work apart from the existing literature. Indeed, despite its increasing popularity as a powerful analytical tool, given its granularity and capability to model the system of interest adequately, the complexity of ABM limits its application in optimizing frameworks due to considerable uncertainty about solution quality. In this light, the use of SAA ensures quality in the optimal solution (with a measured optimality gap) while still being able to handle large‐scale decision‐making problems. With this combination, our application suggests that the optimal (economic) trap grid size for PFF in Queensland is ˜0.7 km, much smaller than the currently implemented level of 5 km. Although the current policy implies a much lower surveillance cost per year, compared with the $2.08 million under our optimal policy, the expected total cost of an outbreak is $23.92 million, much higher than the optimal policy of roughly $7.74 million.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Wiley
Date: 24-08-2017
Publisher: Elsevier BV
Date: 10-2016
Publisher: Elsevier BV
Date: 2017
DOI: 10.2139/SSRN.3029073
Publisher: Wiley
Date: 05-2014
DOI: 10.1002/APP5.37
Publisher: Elsevier BV
Date: 03-2015
DOI: 10.1016/J.JVAL.2014.11.008
Abstract: Although tuberculosis is a major cause of morbidity and mortality worldwide, available funding falls far short of that required for effective control. Economic and spillover consequences of investments in the treatment of tuberculosis are unclear, particularly when steep gradients in the disease and response are linked by population movements, such as that between Papua New Guinea (PNG) and the Australian cross-border region. To undertake an economic evaluation of Australian support for the expansion of basic Directly Observed Treatment, Short Course in the PNG border area of the South Fly from the current level of 14% coverage. Both cost-utility analysis and cost-benefit analysis were applied to models that allow for population movement across regions with different characteristics of tuberculosis burden, transmission, and access to treatment. Cost-benefit data were drawn primarily from estimates published by the World Health Organization, and disease transmission data were drawn from a previously published model. Investing $16 million to increase basic Directly Observed Treatment, Short Course coverage in the South Fly generates a net present value of roughly $74 million for Australia (discounted 2005 dollars). The cost per disability-adjusted life-year averted and quality-adjusted life-year saved for PNG is $7 and $4.6, respectively. Where regions with major disparities in tuberculosis burden and health system resourcing are connected through population movements, investments in tuberculosis control are of mutual benefit, resulting in net health and economic gains on both sides of the border. These findings are likely to inform the case for appropriate investment in tuberculosis control globally.
Publisher: Public Library of Science (PLoS)
Date: 09-07-2020
Publisher: University of Wisconsin Press
Date: 28-06-2012
DOI: 10.3368/LE.88.3.478
Publisher: Elsevier BV
Date: 2018
DOI: 10.2139/SSRN.3122125
Publisher: Elsevier BV
Date: 08-2017
Publisher: Wiley
Date: 15-11-2019
Publisher: Elsevier BV
Date: 09-2022
DOI: 10.1016/J.PREVETMED.2022.105703
Abstract: Foot-and-mouth disease (FMD) is arguably the most damaging animal disease, affecting three-quarters of the global livestock population. This paper provides a cost-benefit analysis of the first five-year program that used vaccination to contain and control FMD in an endemic country, Vietnam. Our spatial and dynamic model to simulate FMD outbreaks fully considered the distance among livestock premises, their herd sizes, and composition, all of which significantly affect FMD transmission. Our program benefit was consistently estimated due to the Law of Large Number and the design of pairing the control and treatment scenarios which allowed capturing the true benefit of each outbreak realization. The data used to monetize the program benefit were largely drawn from Vietnam's context and statistics, thus obviating the need to make many potentially undue assumptions. Meanwhile, the program costs were actual spending and allocated budget. We found that the vaccination program is highly cost-effective for Vietnam, yielding a net present value of US$136 million (in 2006 prices) over five years and a benefit-cost ratio of 5.7. Our results were robust to different assumptions about the vaccine effectiveness of the livestock unit.
Publisher: Cambridge University Press (CUP)
Date: 2011
DOI: 10.1093/PAN/MPQ026
Abstract: This paper analyzes the properties of the fixed-effects vector decomposition estimator, an emerging and popular technique for estimating time-invariant variables in panel data models with group effects. This estimator was initially motivated on heuristic grounds, and advocated on the strength of favorable Monte Carlo results, but with no formal analysis. We show that the three-stage procedure of this decomposition is equivalent to a standard instrumental variables approach, for a specific set of instruments. The instrumental variables representation facilitates the present formal analysis that finds: (1) The estimator reproduces exactly classical fixed-effects estimates for time-varying variables. (2) The standard errors recommended for this estimator are too small for both time-varying and time-invariant variables. (3) The estimator is inconsistent when the time-invariant variables are endogenous. (4) The reported s ling properties in the original Monte Carlo evidence do not account for presence of a group effect. (5) The decomposition estimator has higher risk than existing shrinkage approaches, unless the endogeneity problem is known to be small or no relevant instruments exist.
Publisher: Elsevier BV
Date: 2018
DOI: 10.2139/SSRN.3122095
Publisher: Springer Science and Business Media LLC
Date: 22-02-2020
Publisher: Cambridge University Press (CUP)
Date: 2011
DOI: 10.1093/PAN/MPR012
Abstract: Fixed effects vector decomposition (FEVD) is simply an instrumental variables (IV) estimator with a particular choice of instruments and a special case of the well-known Hausman-Taylor IV procedure. Plümper and Troeger (PT) now acknowledge this point and disown the three-stage procedure that previously defined FEVD. Their old recipe for SEs, which has regrettably been used in dozens of published research papers, produces dramatic overconfidence in the estimates. Again PT concede the point and now adopt the standard IV formula for SEs. Knowing that FEVD is an application of IV also has the benefit of focusing attention on the choice of instruments. Now it seems PT claim that the FEVD instruments are always the best choice, on the grounds that one cannot know whether any potential instrument is correlated with the unit effect. One could just as readily make the same specious claim about other estimators, such as ordinary least squares, and support it with similar Monte Carlo assumptions and evidence.
No related grants have been discovered for Hoa-Thi-Minh Nguyen.