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Understand the dynamics of Highly Pathogenic Avian Influenza (HPAI) through integrative modelling approaches, $149 920 [Principal applicant]
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Bioinformatics, Computational Biology, Health Data Sciences, CIHR/Training Grant: HRTP, $5 550 000 [Co-Applicant]
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Network Digital health & FRQS /Thematic Network, $3 600 000 [co-Principal applicant]
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Modélisation des défis émergents (STRATÉGIA), $885 825 [Co-Applicant]
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High-dimensional hierarchical data with complex dependency structures, $233 125 [Principal applicant]
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Long COVID Web: Pan-Canadian Post-COVID Condition Research Network, $19 999 923 [Co-Applicant]
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Epidemiological modelling of behavioural impact on Mpox mitigation strategies, $412 000 [Principal applicant]
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Modelling human behaviour response to public policy and its impact on infectious disease spread - case studies using AI/ML, data science, game theory and optimization, $200 000 [Co-Applicant]
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Modèles de dépendance de séries temporelles en grandes dimensions /Dependence modelling for high dimensional time series [Principal applicant, individual grant] ($15 000)
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Dependence modelling for arbitrary distributions [Principal applicant, individual grant] ($127 500)
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Climate changes and their impacts on public health [Start-up grant] ($20 000)
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Chercheure boursière Junior 1 FRQS en intelligence artificielle en santé et santé numérique : Surveillance en temps réel des risques des changements climatiques sur la santé publique ($80 000) [Principal applicant, individual grant]
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Chercheurs-boursiers Junior 1 en intelligence artificielle et santé numérique ($225 075) [Principal applicant, individual grant]
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Using personal social media to enhance event-based surveillance of COVID-19: a proof of concept, $270,273 [Co-Applicant]
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Mathematics for public health (Fields Institute), $3M [Co-Applicant]
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Identifying disease determinants and forecasting potential of co-circulating arboviruses, $317,476 [Co-Applicant]
Stochastic Prediction of Emerging Climate-Related and Health Threats @ UdeM
Compartmental models
A stochastic analysis of a SIQR epidemic model with short and long-term prophylaxis. (Submitted by Sekkak*, Nasri,* Rémillard*, Kong and Khalifi, 2022+).
Containing and managing an emerging disease outbreak: a stochastic modelling approach. I. Sekkak, J. D. Kong, B. Nasri and M. El Fatini. Revision requested SIAM Journal on ADS
Near-optimal stochastic control for radiotherapy treatment in a random cancer model. Bouggar Driss; Mohamed El Fatini; Imane El Hichamy; Bouchra R. Nasri, Idriss Sekkak. Submitted
Is there a risk of Chikungunya outbreak with autochthonous transmission in Ontario, Canada? Under Review Acta Tropica. (Submitted by Song, Ogden, Rees, Deng, Nasri, Moyles, Jin, Zhu, 2022+).
A review of empirical processes and its applications in probability and statistics: A random walk through empirical processes (2022). Canadian Journal of Statistics (by Csörgő, Dwason, Nasri, Rémillard).
School and community reopening during the COVID-19 pandemic: a mathematical modeling study (2022). Royal Society Open Science (by Yuan, Aruffo, Ogden, Tan, Gatov, Gournis, Collier, Nasri, Moyles, Li, Zhu)
Text Classification; Social media data
Other stochastic models.
A Deep Learning-based Approach for Early Detection of Potential COVID-19 Patients Using Self-Reported Symptoms on Twitter. In preparation
Exploration of Lyme Disease Incidence Rate Modeling and Risk Assessment Mapping using Twitter and Google search. In preparation
Goodness-of-fit tests and regime selection procedures for general autoregressive hidden Markov Models with covariates (Submitted by Nasri, Rémillard, Thioub, 2022+).
Spatio-temporal Markov regime-switching models based on copulas (In preparation, 2022+).
Hydrological regime variability over the Quebec-Labrador peninsula (Canada) during the last centuries (2020). Water Resources Research (by Nasri, Boucher, Perreault, Rémillard, Huard, Nicault).
GaussianHMM1d: Inference, Goodness-of-Fit, and Forecast for Univariate Gaussian Hidden Markov Models Version 1.0.1. https://cran.r-project.org/web/packages/GaussianHMM1d (by Nasri, Rémillard 202
Thioub, M.Y., B. Nasri, R.Pieugueu and B. Rémillard (2018). HMMcopula: Markov regime-switching copula models estimation and goodness of fit. https://cran.r-project.org/web/packages/HMMcopula/index.html.
Nasri, B.R. and Thioub, M.Y. GenHMM1d: Goodness-of-Fit for Univariate Hidden Markov Models Version 0.1.0. https://cran.rproject.org/web/packages/GenHMM1d/index.html
Images of Arctic sea extent provided by the National Snow & Ice Data Center.
