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Dive into the research topics where Luke Mondor is active.

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Featured researches published by Luke Mondor.


Emerging Infectious Diseases | 2012

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications

Luke Mondor; John S. Brownstein; Emily H. Chan; Lawrence C. Madoff; Marjorie P. Pollack; David L. Buckeridge; Timothy F. Brewer

To compare the timeliness of nongovernmental and governmental communications of infectious disease outbreaks and evaluate trends for each over time, we investigated the time elapsed from the beginning of an outbreak to public reporting of the event. We found that governmental sources improved the timeliness of public reporting of infectious disease outbreaks during the study period.


Ibm Journal of Research and Development | 2012

An infrastructure for real-time population health assessment and monitoring

David L. Buckeridge; Masoumeh T. Izadi; Arash Shaban-Nejad; Luke Mondor; Christian Jauvin; Laurette Dubé; Yeona Jang

The fragmented nature of population health information is a barrier to public health practice. Despite repeated demands by policymakers, administrators, and practitioners to develop information systems that provide a coherent view of population health status, there has been limited progress toward developing such an infrastructure. We are creating an informatics platform for describing and monitoring the health status of a defined population by integrating multiple clinical and administrative data sources. This infrastructure, which involves a population health record, is designed to enable development of detailed portraits of population health, facilitate monitoring of population health indicators, enable evaluation of interventions, and provide clinicians and patients with population context to assist diagnostic and therapeutic decision-making. In addition to supporting public health professionals, clinicians, and the public, we are designing the infrastructure to provide a platform for public health informatics research. This early report presents the requirements and architecture for the infrastructure and describes the initial implementation of the population health record, focusing on indicators of chronic diseases related to obesity.


international world wide web conferences | 2013

Vaccine attitude surveillance using semantic analysis: constructing a semantically annotated corpus

Stephanie Brien; Nona Naderi; Arash Shaban-Nejad; Luke Mondor; Doerthe Kroemker; David L. Buckeridge

This paper reports work in progress to semantically annotate blog posts about vaccines to use in the Vaccine Attitude Surveillance using Semantic Analysis (VASSA) framework. The VASSA framework combines semantic web and natural language processing (NLP) tools and techniques to provide a coherent semantic layer across online social media for assessment and analysis of vaccination attitudes and beliefs. We describe how the blog posts were sampled and selected, our schema to semantically annotate concepts defined in our ontology, details of the annotation process, and inter-annotator agreement on a sample of blog posts.


world congress on medical and health informatics, medinfo | 2013

PHIO: a knowledge base for interpretation and calculation of public health indicators.

Arash Shaban-Nejad; Anya Okhmatovskaia; Masoumeh T. Izadi; Nona Naderi; Luke Mondor; Christian Jauvin; David L. Buckeridge

Existing population health indicators tend to be out-of-date, not fully available at local levels of geography, and not developed in a coherent/consistent manner, which hinders their use in public health. The PopHR platform aims to deliver an electronic repository that contains multiple aggregated clinical, administrative, and environmental data sources to provide a coherent view of the health status of populations in the province of Quebec, Canada. This platform is designed to provide representative information in near-real time with high geographical resolution, thereby assisting public health professionals, analysts, clinicians and the public in decision-making. This paper presents our ongoing efforts to develop an integrated population health indicator ontology (PHIO) that captures the knowledge required for calculation and interpretation of health indicators within a PopHR semantic framework.


Age and Ageing | 2015

Weather warnings predict fall-related injuries among older adults

Luke Mondor; Katia Charland; Aman Verma; David L. Buckeridge

BACKGROUND weather predictions are a useful tool for informing public health planning and prevention strategies for non-injury health outcomes, but the association between winter weather warnings and fall-related injuries has not been assessed previously. OBJECTIVE to examine the association between fall-related injuries among older adults and government-issued winter weather warnings. METHODS using a dynamic cohort of individuals ≥65 years of age who lived in Montreal between 1998 and 2006, we identified all fall-related injuries from administrative data using a validated set of diagnostic and procedure codes. We compared rates of injuries on days with freezing rain or snowstorm warnings to rates observed on days without warnings. We also compared the incidence of injuries on winter days to non-winter days. All analyses were performed overall and stratified by age and sex. RESULTS freezing rain alerts were associated with an increase in fall-related injuries (incidence rate ratio [IRR] = 1.20, 95% confidence interval [CI]: 1.08-1.32), particularly among males (IRR = 1.31, 95% CI: 1.10-1.56), and lower rates of injuries were associated with snowstorm alerts (IRR = 0.89, 95% CI: 0.80-0.99). The rate of fall-related injuries did not differ seasonally (IRR = 1.00, 95% CI: 0.97-1.03). CONCLUSIONS official weather warnings are predictive of increases in fall-related injuries among older adults. Public health agencies should consider using these warnings to trigger initiation of injury prevention strategies in advance of inclement weather.


digital government research | 2012

A knowledge-based architecture for integrating and interpreting population health data

Arash Shaban-Nejad; Yu Ma; Masoumeh T. Izadi; Laurette Dubé; Luke Mondor; David L. Buckeridge

In this paper, we describe our ongoing effort on the design and development of a knowledge-based system for monitoring and analyzing evidence-based population health indicators, with focus on indicators of chronic diseases related to obesity. The knowledge based system facilitates measuring the quality of obesity prevention programs and assists diagnostic and therapeutic decision-making and policy development.


national conference on artificial intelligence | 2013

Population Health Record: An Informatics Infrastructure for Management, Integration, and Analysis of Large Scale Population Health Data

Masoumeh T. Izadi; Arash Shaban-Nejad; Anya Okhmatovskaia; Luke Mondor; David L. Buckeridge


Online Journal of Public Health Informatics | 2014

A Probabilistic Case-finding Algorithm for Chronic Disease Surveillance

Stephanie Brien; Luke Mondor; Nancy E. Mayo; David L. Buckeridge


international semantic web conference | 2013

A hybrid natural language approach to manage semantic interoperability for public health analytics

Maxime Lavigne; Arash Shaban-Nejad; Anya Okhmatovskaia; Luke Mondor; David L. Buckeridge


CEUR Workshop Proceedings | 2013

PopHR: An integrated semantic framework for population health surveillance

Arash Shaban-Nejad; Christian Jauvin; Maxime Lavigne; Masoumeh T. Izadi; Luke Mondor; Anya Okhmatovskaia; David L. Buckeridge

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Laurette Dubé

Desautels Faculty of Management

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