Adrien Ickowicz

Dr. Adrien Ickowicz

orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
2 January 2018 in Journal of Responsible Innovation
Verified
Journal Article
Open access
KHKeith R. Hayes
Keith R. Hayes
GHGeoffrey R. Hosack
Geoffrey R. Hosack
GDGenya V. Dana
Genya V. Dana
SFScott D. Foster
Scott D. Foster
JFJessica H. Ford
Jessica H. Ford
JDJeffrey M. Dambacher
Jeffrey M. Dambacher
Synthetic gene drives could provide new solutions to a range of old problems such as controlling vector-borne diseases, agricultural pests and invasive species. In this paper, we outline methods to identify hazards and detect potentially adverse ecological outcomes at the individual (genotype, phenotype), population, community and ecosystem level, when progressing Gene Drive Modified Organisms through a phased test and release pathway. We discuss the strengths and weaknesses of checklists and structured hazard analysis techniques, identify methods to help meet some of the challenges of detecting adverse ecological outcomes in experiments and confined field trials, and discuss ways to improve the efficiency and statistical rigour of post-release monitoring strategies.

5 October 2016 in Statistics in Medicine
Verified
Journal Article
Closed access
PDF file
AIAdrien Ickowicz
Adrien Ickowicz
RSRoss Sparks
Ross Sparks

1 June 2022 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
NBNicholas Beeton
Nicholas Beeton
AWAndrew Wilkins
Andrew Wilkins
AIAdrien Ickowicz
Adrien Ickowicz
KHKeith R. Hayes
Keith R. Hayes
GHGeoffrey R. Hosack
Geoffrey R. Hosack
Malaria is one of the deadliest vector-borne diseases in the world. Researchers are developing new genetic and conventional vector control strategies to attempt to limit its burden. Novel control strategies require detailed safety assessment to ensure responsible and successful deployments. Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii, two closely related subspecies within the species complex Anopheles gambiae sensu lato (s.l.), are among the dominant malaria vectors in sub-Saharan Africa. These two subspecies readily hybridise and compete in the wild and are also known to have distinct niches, each with spatially and temporally varying carrying capacities driven by precipitation and land use factors. We model the spread and persistence of a population-modifying gene drive system in these subspecies across sub-Saharan Africa by simulating introductions of genetically modified mosquitoes across the African mainland and its offshore islands. We explore transmission of the gene drive between the two subspecies that arise from different hybridisation mechanisms, the effects of both local dispersal and potential wind-aided migration to the spread, and the development of resistance to the gene drive. Given the best current available knowledge on the subspecies’ life histories, we find that an introduced gene drive system with typical characteristics can plausibly spread from even distant offshore islands to the African mainland with the aid of wind-driven migration, with resistance beginning to take over within a decade. Our model accounts for regional to continental scale mechanisms, and demonstrates a range of realistic dynamics including the effect of prevailing wind on spread and spatio-temporally varying carrying capacities for subspecies. As a result, it is well-placed to answer future questions relating to mosquito gene drives as important life history parameters become better understood.

16 September 2021 in Parasites & Vectors
Verified
Journal Article
Open access
PDF file
AIAdrien Ickowicz
Adrien Ickowicz
SFScott D. Foster
Scott D. Foster
GHGeoffrey R. Hosack
Geoffrey R. Hosack
KHKeith R. Hayes
Keith R. Hayes
Background: Reproductive containment provides an opportunity to implement a staged-release strategy for genetic control of malaria vectors, in particular allowing predictions about the spread and persistence of (self-limiting) sterile and male-biased strains to be compared to outcomes before moving to (self-sustaining) gene-drive strains.Methods: In this study, we: (i) describe a diffusion–advection–reaction model of the spread and persistence of a single cohort of male mosquitoes; (ii) elicit informative prior distributions for model parameters, for wild-type (WT) and genetically modified dominant sterile strains (DSM); (iii) estimate posterior distributions for WT strains using data from published mark-recapture-release (MRR) experiments, with inference performed through the Delayed-Rejection Adaptive Metropolis algorithm; and (iv) weight prior distributions, in order to make predictions about genetically modified strains using Bayes factors calculated for the WT strains.Results: If a single cohort of 5000 genetically modified dominant sterile male mosquitoes are released at the same location as previous MRR experiments with their WT counterparts, there is a 90% probability that the expected number of released mosquitoes will fall to < 1 in 10 days, and that by 12 days there will be a 99% probability that no mosquitoes will be found more than 150 m from the release location.Conclusions: Spread and persistence models should form a key component of risk assessments of novel genetic control strategies for malaria vectors. Our predictions, used in an independent risk assessment, suggest that genetically modified sterile male mosquitoes will remain within the locality of the release site, and that they will persist for a very limited amount of time. Data gathered following the release of these mosquitoes will enable us to test the accuracy of these predictions and also provide a means to update parameter distributions for genetic strains in a coherent (Bayesian) framework. We anticipate this will provide additional insights about how to conduct probabilistic risk assessments of stage-released genetically modified mosquitoes.Graphical

1 February 2020 in Journal of Theoretical Biology
Verified
Journal Article
Closed access
NBNicholas Beeton
Nicholas Beeton
GHGeoffrey R. Hosack
Geoffrey R. Hosack
AWAndrew Wilkins
Andrew Wilkins
LFLawrence K. Forbes
Lawrence K. Forbes
AIAdrien Ickowicz
Adrien Ickowicz
KHKeith R. Hayes
Keith R. Hayes

3 February 2015 in Public Transport
Verified
Journal Article
Closed access
PDF file
AIAdrien Ickowicz
Adrien Ickowicz
RSRoss Sparks
Ross Sparks