Nasri Lab
Stochastic Modelling and Quantitative Insights for Health Threats Lab · Université de Montréal

Stochastic Modelling and Quantitative Insights for Health Threats

Led by Prof. Bouchra R. Nasri, our lab develops quantitative methods and computational tools to address complex public health challenges.

Biostatistics Public health threats modelling Dependence models Time series Evidence synthesis Artificial Intelligence

Prof. Bouchra R. Nasri, Ph.D.

  • Associate Professor, Department of Social and Preventive Medicine — Université de Montréal
  • Canada Research Chair, Tier 2 (2027–2031)
  • FRQS Junior 2 Scholar (2025–2027)
  • FRQS Junior 1 Scholar in AI and Digital Health (2021–2025)
  • MATRIX–Simons Young Scholar 2024
✉ bouchra.nasri@umontreal.ca 🔗 ESPUM Profile 🆔 ORCID 📚 Google Scholar

Affiliations

Organization · PositionSince
Réseau de Santé Numérique (RSN)Co-director 2024
Centre de Recherches Mathématiques (CRM)Management Committee / Scientific Advisor, STRATÉGIA program 2024–2026
Institut de valorisation des données (IVADO)IVADO Researcher 2024
Observatoire international sur les impacts sociétaux de l'IA et du numérique (OBVIA)Associate Researcher 2024
The Data Informatics Center of Epidemiology, PathCheckChair 2023–2025
Statistics Laboratory, CRMRegular Member 2021
Centre de Recherche en Santé Publique (CReSP)Regular Member 2020
Quebec Population Health Research Network (RRSPQ)Regular Member 2020–2024
Réseau Inondations InterSectoriel du Québec (RIISQ)Regular Member 2020
Machine Learning in Finance (Fin-ML)Collaborator 2020–2025

What we work on

Two threads run through the lab's research — each grounded in quantitative methods for complex data, each motivated by a real health-threat question.

Quantitative methods developments

Time series, change points, complex dependence structures, representativity problems, hierarchical modelling; stochastic modelling, large language models.

Climate-related health threats modelling

Mathematical and stochastic models for COVID-19, AMR, vector-borne diseases, and emerging threats.

Latest news

Workshops, publications, and lab highlights.

What we study

Research themes

Six interconnected areas where AI and mathematical statistics meet complex health threats, including infectious diseases, public health, exposome research, and climate-related health threats.

01

Deterministic and stochastic modelling

Compartmental models, stochastic dynamics, and surveillance-driven inference for COVID-19, antimicrobial resistance, vector-borne diseases, and emerging zoonoses.

Infectious disease modelling Public health threats modelling
02

Multivariate statistics & dependence models

Dependence structures for high-dimensional and time-varying data. Theoretical contributions on goodness-of-fit, estimation, and inference for complex multivariate data.

Copulas HMM Multivariate
03

Time series modelling

Time series, change-point detection, and spatio-temporal extensions for environmental and epidemiological data, including climate–health interactions.

Time series Change points
04

Evidence synthesis methods

Bridging quantitative methods and evidence synthesis to bring methods into practice.

Methods Reviews
05

Big data & text mining

Construction of structured data repositories from unstructured sources to feed health-threat models. Natural language processing for epidemiological surveillance.

Text mining NLP Surveillance
06

Digital health

Leadership of the Réseau santé numérique du Québec and former Chair of the PathCheck Data Informatics Center. Methods and structuring initiatives in digital health for research and innovation.

Digital health RSN PathCheck

Active grants

NSERC / Discovery Grants program (individual)2026–2031
Statistical methods for multivariate time series with complex data
B. Nasri (PI)
CIHR / Team Grant: Bringing Biology to Cancer Prevention - General Pool2026–2031
Environmental eXposure Profiling for Signatures of Early ColoRectal Cancer (EXPOSE-CRC)
B. Nasri (co-PI with V. Ho, L.-H. Tai, D. von Renteln)
FRQS / Research Scholars – Junior 2 (Individual grant, Salary award)2025–2027
Quantitative methods for assessing health risks associated with climate change
B. Nasri (PI)
New Frontiers in Research Fund – Exploration2025–2027
Integrated approach to climate change adaptation planning in multi-country water-energy-food-health-economy systems
B. Nasri (co-PI with M. Basheer)
CIHR / Catalyst Grant: Avian Influenza One Health Research2024–2027
Understanding the dynamics of Highly Pathogenic Avian Influenza (HPAI) through integrative modelling approaches
B. Nasri (PI)
CIHR / Training Grant: HRTP2024–2029
Bioinformatics, Computational Biology, Health Data Sciences
Co-Investigator (PI: M. Brazas)
CIHR / Project2025–2031
Supporting climate change interventions for urban health and equity: a participatory complex system perspective
Co-Investigator (PIs: Y. Kestens & L. Perez)
FRQS / Thematic Network2024–2032
Network Digital Health
B. Nasri (co-PI with S. Ahmed, P. Després, A. Motulsky, M. Vallières)
FRQNT (STRATÉGIA)2024–2027
Modelling Emerging Challenges
Co-Investigator & Scientific Advisor (PI: O. Cornea)
FRQNT–NSERC (NOVA)2024–2027
High-dimensional hierarchical data with complex dependency structures
B. Nasri (PI)
CIHR / Post COVID-19 Condition Research Network2023–2028
Long COVID Web: Pan-Canadian Post-COVID Condition Research Network
Co-Investigator (Nominated PI: A. Cheung)
Members & Alumni

The people behind the models.

Biostatisticians, mathematical modellers, epidemiologists, data scientists, and public and global health researchers; current members and our alumni.

A huge thank-you to the current team and to everyone who has helped build this lab over the years. Through your dedication, generosity, and hard work, we keep growing every day. This lab is ours, and its success reflects our collective commitment. THANK YOU!

Life in the Lab

Research is only one part of our daily life. We foster a welcoming, collaborative, and stimulating environment where everyone can thrive.

Life in the lab — team moments
Scientific articles

Publications

Peer-reviewed work by the lab and collaborators since 2020, organized by year and theme.

2026

On testing for independence between generalized error models of several time series

Ghoudi K., Nasri B.R., Rémillard B.N.

Journal of Time Series Analysis

2026

The effect of sudden fluctuations on a treated Hepatitis C model

Bertoune A., El Fatini M., Nasri B.R., Sekkak I.

International Journal of Biomathematics 19(4), 2450078

2026

Mechanistic modelling of highly pathogenic avian influenza: A scoping review

Wang M., Laison E.K.E., et al.

PLoS One 21(4), e0347929

2026

Fluctuations and Long-Time Stability of Multivariate Ensemble Kalman Filters

Del Moral P., Nasri B., Rémillard B.

arXiv:2601.17392

2025

Mathematical modelling of the first HIV/ZIKV co-infection cases in Colombia and Brazil

Romero-Leiton J.P., Sekkak I., Arino J., Moyles I., Nasri B.

Bulletin of Mathematical Biology 87(5), 54 cited 3×

2025

On factor copula-based mixed regression models

Krupskii P., Nasri B.R., Rémillard B.N.

Electronic Journal of Statistics 19(1), 1133–1173 cited 4×

2025

Assessing the impact of mutations and horizontal gene transfer on antimicrobial resistance

Romero-Leiton J.P., Peterson A., Aguirre P., Acharya K., Nasri B.

Computational and Applied Mathematics 44(2), 82 cited 4×

2025

Exploring Zika's Dynamics: A Scoping Review from Epidemic to Equations

Romero-Leiton J.P., Laison E.K.E., Alfaro R., et al.

Infectious Disease Modelling cited 5×

2025

Generalizability of anti–SARS-CoV-2 seroprevalence estimates to the Montréal pediatric population

Saucier A., Nasri B., McKinnon B., et al.

American Journal of Epidemiology 194(4), 1112–1121 cited 3×

2025

Dynamics of AMR beyond a single bacterial strain

Romero-Leiton J.P., Peterson A., Aguirre P., Bastidas-Caldes C., Nasri B.

Chaos, Solitons & Fractals 191, 115912 cited 3×

2025

Kindergarten teachers' changes in practice in interactive book reading following professional development

McMahon-Morin P., Gingras M.P., Halle M.C., Rezzonico S., Nasri B.

Teaching and Teacher Education 153, 104806 cited 7×

2025

Cognitive maintenance in older adults in social classes: a secondary analysis of the SHARE data

Bodryzlova Y., Nasri B., et al.

Journal of Epidemiology and Community Health 79(7), 531–538 cited 1×

2025

Considering the effects of pair formation dynamics on mpox and HIV co-infection

Machado-Marques S., Romero-Leiton J.P., Nasri B., Moyles I.R.

Scientific Reports 15(1), 36028 cited 2×

2024

Models and data used to predict the abundance and distribution of Ixodes scapularis in North America

Sharma Y., Laison E.K.E., Philippsen T., et al.

The Lancet Regional Health–Americas 32 cited 14×

2024

Predicting malaria risk considering vector control interventions under climate change

Sadoine M.L., Zinszer K., Liu Y., et al.

Scientific Reports 14(1), 2430 cited 10×

2024

Tests of independence and randomness for arbitrary data using copula-based covariances

Nasri B.R., Rémillard B.N.

Journal of Multivariate Analysis 201, 105273 cited 7×

2024

Knowledge, attitudes and practice questionnaires in dengue, Zika, chikungunya and yellow fever: a scoping review protocol

Robayo Gonzalez C.X., Nasri B., Szaroz D., Zinszer K.

BMJ Open 14(12), e090251 cited 4×

2024

Socio-demographic determinants of COVID-19 vaccine uptake in Ontario

Ortiz A.M., Nasri B.

Vaccine 42(8), 2106–2114 cited 4×

2024

Are information criteria good enough to choose the right number of regimes in hidden Markov models?

Nasri B.R., Rémillard B.N., Thioub M.Y.

Journal of Statistical Computation and Simulation 94(18), 4107–4127 cited 3×

2024

The Impact of Soft and Hard Flood Adaptation Measures on Mental Health

El-Mousawi F., Ortiz A.M., Berkat R., Nasri B.

Disaster Medicine and Public Health Preparedness 18, e118 cited 2×

2024

Effect of a whole-group intervention on children's participation in interactive book reading

McMahon-Morin P., Nasri B., Verduyckt I., Rezzonico S., Gingras M.P.

The Journal of Educational Research 117(5), 316–330 cited 3×

2024

Linking opinions on social media about COVID-19 public health measures to adherence

Denis-Robichaud J., Rees E.E., Daley P., et al.

Journal of Medical Internet Research 26, e51325 cited 1×

2023

Mathematical modeling of mpox: a scoping review

Molla J., Sekkak I., Ortiz A.M., Moyles I., Nasri B.R.

One Health 100540 cited 50×

2023

Leveraging machine learning for predicting Lyme disease cases using Twitter

Boligarla S., Laison E.K.E., Li J., et al.

BMC Medical Informatics and Decision Making 23(1), 217 cited 24×

2023

How is the COVID-19 pandemic impacting our life, mental health, and well-being? The COHESION study

Gabet S., Thierry B., Wasfi R., et al.

BMC Public Health 23(1), 2401 cited 11×

2023

Differential influence of environmental factors on malaria due to vector control interventions in Uganda

Sadoine M.L., Smargiassi A., Liu Y., et al.

Int. J. Environmental Research and Public Health 20(22), 7042 cited 11×

2023

Identifying potential Lyme disease cases using self-reported Tweets: deep learning approach

Laison E.K.E., Ibrahim M.H., Boligarla S., et al.

Journal of Medical Internet Research 25, e47014 cited 9×

2023

Modelling the transmission of dengue, zika and chikungunya: a scoping review protocol

Romero-Leiton J.P., Acharya K.R., Parmley J.E., Arino J., Nasri B.

BMJ Open 13(9), e074385 cited 9×

2023

A stochastic analysis of a SIQR epidemic model with short and long-term prophylaxis

Sekkak I., Nasri B.R., Remillard B.N., Kong J.D., El Fatini M.

Communications in Nonlinear Science and Numerical Simulation 127, 107523 cited 6×

2023

Identifiability and inference for copula-based semiparametric models

Nasri B.R., Remillard B.N.

arXiv:2301.13408 cited 5×

2022

School and community reopening during the COVID-19 pandemic: a mathematical modeling study

Yuan P., Aruffo E., Gatov E., Tan Y., Li Q., Ogden N., Collier S., Nasri B., et al.

Royal Society Open Science 9(2) cited 34×

2022

Effectiveness of non-pharmaceutical interventions to reduce SARS-CoV-2 transmission in Canada

Rees E.E., Avery B.P., Carabin H., et al.

Canada Communicable Disease Report 48(10), 438 cited 17×

2022

Change-point problems for multivariate time series using pseudo-observations

Nasri B.R., Rémillard B.N., Bahraoui T.

Journal of Multivariate Analysis 187, 104857 cited 15×

2022

Tests of serial dependence for multivariate time series with arbitrary distributions

Nasri B.R.

Journal of Multivariate Analysis cited 6×

2022

Near-optimal stochastic control for radiotherapy treatment in a random cancer model

Bouggar D., El Fatini M., El Hichamy I., Nasri B.R., Sekkak I.

Systems & Control Letters 170, 105400 cited 4×

2021

MixedIndTests: Tests of Randomness and Tests of Independence

Nasri B.R., Remillard B.N., Neslehova J.G., Genest C.

R package version 0.1.4 cited 5×

2021

GaussianHMM1d: Inference, Goodness-of-Fit and Forecast for Univariate Gaussian Hidden Markov Models

Nasri B.R., Remillard B.N.

CRAN cited 4×

2020

Goodness-of-fit for regime-switching copula models with application to option pricing

Nasri B.R., Rémillard B.N., Thioub M.Y.

The Canadian Journal of Statistics 48, 79–96 cited 26×

2020

On non-central squared copulas

Nasri B.R.

Statistics & Probability Letters 161, 108704 cited 10×

2020

Modeling hydrological inflow persistence using paleoclimate reconstructions

Nasri B.R., Boucher É., Perreault L., et al.

Water Resources Research, e2019WR025122 cited 14×

2020

Forecast of streamflows to the Arctic Ocean by a Bayesian neural network model

Rasouli K., Nasri B.R., Soleymani A., et al.

Hydrology Research cited 14×

Earlier publications on Google Scholar →
Open-source tools

Software & R packages

Statistical software developed by the lab, freely available on CRAN.

CRAN

BasicStatsPlots

Publication-Ready Data Visualization and Simple Statistical Inference — ggplot2-based charts with publication-friendly themes, plus confidence intervals, ANOVA, and linear and generalized regression. Developed with lab trainees.

Ricros Q., Roussel T., Carrière C., Nasri B.
View on CRAN →
CRAN

GenOU

Sequential Change-Point Tests for Generalized Ornstein-Uhlenbeck Processes — sequential change-point tests, parameter estimation, and goodness-of-fit tests.

Lyu Y., Nasri B.R., Rémillard B.N.
View on CRAN →
CRAN

CopulaInference

Estimation and Goodness-of-Fit of Copula-Based Models with Arbitrary Distributions — bivariate data that can be discrete, continuous, or a mixture of both, including non-central squared copula families.

Nasri B.R., Rémillard B.N.
View on CRAN →
CRAN

CopulaGAMM

Copula-Based Mixed Regression Models — estimation of 2-level factor copula-based regression models for clustered data, with discrete or continuous responses.

Krupskii P., Nasri B.R., Rémillard B.N.
View on CRAN →
CRAN

IndGenErrors

Tests of Independence Between Innovations of Generalized Error Models — independence tests for time-series innovations, usable with stochastic volatility models and hidden Markov models.

Ghoudi K., Nasri B.R., Rémillard B.N., Duchesne P.
View on CRAN →
CRAN

GenHMM1d

Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov Models — inference, goodness-of-fit tests, and predictions for continuous and discrete univariate HMMs, including zero-inflated distributions.

Nasri B.R., Thioub M.Y.
View on CRAN →
CRAN

MixedIndTests

Tests of Randomness and Tests of Independence — copula-based covariance tests for arbitrary multivariate data, including mixed discrete/continuous variables.

Nasri B.R., Rémillard B.N., Neslehova J.G., Genest C.
View on CRAN →
CRAN

HMMcopula

Markov Regime Switching Copula Models — estimation and goodness-of-fit for hidden Markov copula models with application to option pricing.

Nasri B.R., Rémillard B.N., Thioub M.Y., Pieugueu R.
View on CRAN →
CRAN

changepointTests

Change Point Tests for Joint Distributions and Copulas — tests for detecting structural breaks in multivariate time series via pseudo-observations.

Nasri B.R., Rémillard B.N.
View on CRAN →
CRAN

GaussianHMM1d

Inference, Goodness-of-Fit and Forecast for Univariate Gaussian Hidden Markov Models — full pipeline for 1D Gaussian HMMs.

Nasri B.R., Rémillard B.N.
View on CRAN →
CRAN

NCSCopula

Non-Central Squared Copula Models Estimation — implements inference for non-central squared copula families.

Nasri B.R.
View on CRAN →
Events

What's happening in the lab

Workshops, schools, and conferences organized or co-organized by the lab and its collaborators.

Lab members at workshops, schools and conferences

Upcoming events

12–13 Nov 2026

Workshop: Quantitative methods in health and co-creation of solutions

CRM · Montréal
25 Jan – 5 Feb 2027

Advancements in Multivariate Extremes Theory and Modelling the Climate Change Threats

MATRIX · Australia
8–12 Feb 2027

Multivariate Dependence Modeling Including Copula and Covariance Structure Modeling and Their Applications

MATRIX · Australia

Past events

7–9 Oct 2026

Fall school — Advanced methods in epidemiological modelling and computational biology (part II)

CRM · Montréal
29 Sep 2026

Mila community of practice: Digital health

Mila · Montréal
28 Sep – 2 Oct 2026

Aisenstadt Chair lectures — Daniela M. Witten

CRM · Montréal
14–18 Sep 2026

Workshop: Mathematical and statistical modelling of public health threats

ICM satellite event
CRM · Montréal
14–18 Sep 2026

Aisenstadt Chair lectures — Abba B. Gumel

CRM · Montréal
2026

CRM thematic semester 2026 — Mathematics for health

CRM · Montréal
May 2024

SocioEconomic Mathematical Epidemiology

BIRS · Banff, Alberta
2024

MATRIX – Simons Young Scholar Program, Australia

MATRIX · Australia
2024

Launch of the STRATEGIA program — Modelling Emerging Challenges

CRM · Montréal
2024

Multivariate Dependence Modeling: Theory and Applications

MATRIX · Australia
2024

Launch of the Réseau santé numérique du Québec

RSN · Montréal
2023

International symposium — Rethinking digital health training

Montréal · co-organized with the RSN
2023

CRM-MfPH Symposium on Mathematical Modelling of Infectious Diseases

CRM · Montréal
2023

The role of mathematics in public health: a showcase for modelling

CReSP · Montréal
2023

MfPH Workshop on Early Warning Systems for Emerging and Re-emerging Diseases

Fields Institute · Toronto

Miscellaneous

A personal corner — artwork by my nieces.

Chaymae

Chaymae artwork 1

Chaymae

Chaymae artwork 2

Ibtihal

Ibtihal artwork
Get in touch

Contact

Questions about the lab, collaborations, or graduate admissions? We'd love to hear from you.

Prof. Bouchra Nasri

🎓
Title
Associate Professor
🏛
Department
School of Public Health (ESPUM) — Social & Preventive Medicine
Université de Montréal
✉️
📍
Address
7101 Parc Avenue, Office 3109
Montréal, QC H3N 1X9
📞
Phone
514 343-7973

Prospective students

We welcome applications from motivated students interested in biostatistics, mathematical modelling, epidemiology, and data science. Please include your CV and a brief statement of interest when reaching out.

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