Selected Projects

How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices

Postdoctoral Research. York University/Mount Sinai Hospital
Collaborators: Amy Hurford (Memorial U), Rita Finley (PHAC), David Patrick (UBC/BCCDC), Jianhong Wu (York U) and Andrew Morris (Sinai Health System/U of Toronto).
Two indices summarize the impact of antibiotic resistance on empiric therapy, accounting for drug availability and pathogen importance. They can be calculated from cumulative antibiogram data, and used to assess trends, interventions and potential threats.
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Benefits and unintended consequences of antimicrobial de-escalation

Postdoctoral Research. York University/Mount Sinai Hospital
Collaborators:  Xi Huo (Ryerson U), Lindsey Falk (U of Toronto), Amy Hurford (Memorial U), Kunquan Lan (Ryerson U), Bryan Coburn (U of Toronto),  Jianhong Wu (York U), and Andrew Morris (Sinai Health System/U of Toronto)
Inadequate empiric therapy delays recovery and increases mortality, and resistance threatens the effectiveness of empiric drugs. De-escalation strategies aim to minimize the use of empiric drugs by switching to narrow spectrum alternatives when lab results indicate susceptibility. We investigated the consequences of this strategy using simulation models.
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The effects of forest spatial structure on insect outbreaks: insights from a host-parasitoid model

PhD project. University of Toronto. Supervisor: Marie-Josée Fortin
Collaborators: Greg Dwyer (U of Chicago), Christina Cobbold (U of Glasgow), Kyle Haynes (U of Virginia)
2015. The American Naturalist 185(5): E130-E152 http://www.jstor.org/stable/10.1086/680860.
We investigated the effects of landscape configuration and other factors on a spatial model of host-parasitoid (forest tent caterpillar) population dynamics. We also developed a new approximation technique to simplify model analysis and parameter estimation.
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Pollen cone production in jack pine: spatial and temporal patterns subject to natural disturbance by the jack pine budworm

PhD project. University of Toronto. Supervisor: Marie-Josée Fortin
Collaborators: Vince Nealis and Jacques Régnière (Canadian Forest Service)
Canadian Journal of Forest Research. 2014. Vol. 44, No. 3 : pp. 195-211
We used generalized linear mixed regression models to distinguish effects of defoliation on pollen cone production from spatially synchronous background variation in cone production.
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Does damage-dependent long-distance dispersal explain mountain pine beetle spread?

PhD project. University of Toronto. Supervisor: Marie-Josée Fortin
We investigated how well a discretized integro-difference model of mountain pine beetle population dynamics predicts the occurrence of new infestations in British Columbia.
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BCMPB: Mountain pine beetle projection model

Consulting project for the BC Forest Service, led by Marvin Eng and Adrian Walton.
Collaborators: Andrew Fall (Gowlland Technologies), Peter Hall (BC Forest Service),
Terry Shore and Bill Riel (Canadian Forest Service)
I collaborated on modeling mountain pine beetle dynamics and management across British Columbia.
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