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Master of Statistics and Data Science

Master of Statistics and Data Science

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Being the cornerstone of public, international and global health, epidemiology is the study of the distribution and determinants of health-related outcomes and diseases in populations.  Epidemiological information is the basis for planning and evaluating preventive or control strategies; it shapes policy decisions and evidence-based practices in public health.

The design of epidemiological studies and  intervention measures, the collection and analysis of epidemiological data require appropriate expertise in statistical methodology in combination with knowledge of other scientific disciplines such as medical biology, computer sciences, social sciences, etc.

Statistical methodology in general and in epidemiology in particular rests on solid mathematical and probabilistic foundations. This is why foundational courses are offered, in a step-up design, during the first year, supported by a broad introduction to medical and molecular biology: linear models (regression, analysis of variance, etc.), generalized linear models (logistic regression, Poisson regression, etc.), multivariate methods, longitudinal data, Bayesian methodology, so on. Further, during the second year, in addition to three foundational courses, specialized courses are offered in spatial epidemiology, digital epidemiology, mathematical modelling of infectious diseases, environmental epidemiology and microbial risk assessment.

Evidently, fluency in the use of statistical software is expected, which is why not only dedicated courses but also assignments and course work throughout the courses focus on the computational aspects.

Statisticians needs to be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.

For more detailed information on the curriculum of this specialization, please consult the course overview or the studyguide.


Major relevance to COVID-19

This programme is highly relevant for many aspects of the COVID-19 pandemic !

Students learn about the mathematical models for predicting the evolution of an outbreak and how the models can be used for evaluating preventive and control strategies that are considered by policy makers. These models are essential for supporting policy makers in making decisions to, for example, flatten the curve. Students learn about the particularities of epidemiological data: where to find them, how to design surveys, what are potential sources of bias, ....
Without such knowledge, the models may give incorrect predictions, lead to the wrong conclusions when comparing countries, etc. In the course Spatial Epidemiology, students learn how to study the geographical spread of diseases and relate the risk of disease to environmental factors. For example, does temperature and UV intensity affect the risk of COVID-19? Many techniques that are used today require intensive computations and very big and heterogeneous datasets from various origins and study designs. Also these aspects are studied in this programme. Once the data analyses are finished, the results need to be communicated to the wider public and to the policy makers. This requires very good communication skills; e.g it is not easy to communicate the uncertainty that comes with the conclusions, or explain the shortcomings of the epidemiological data and the potential biases.

Some of the key lecturers in this programme (e.g. prof. Niel Hens and prof. Christel Faes) are heavily involved in studying the COVID-19 pandemic and are advising the Belgian government. They all have dozens of years of experience with modelling infectious diseases, not only in Belgium but worldwide (e.g. ebola, malaria, ...). 

For additional information on (some of) the data aspects of the COVID-19 pandemic, do visit the COVID-19 pages of our Data Science Institute.



Statisticians are in high demand, also in the field of epidemiology and public, international and global health. You will find them in different institutes, in the role of quantitative epidemiologist, statistician as well as in the manager’s chair. Many are employed by universities, governmental agencies, such as health research institutes, food safety departments, health knowledge centers, regulatory authorities, etc. You will meet them at local, national, European, and international governments, throughout the globe. Indeed, solving global health and development problems is amongst the key drivers to become a statistician with expertise in quantitative epidemiology. Many of our former graduates originate from countries at large, complete their master training at Hasselt University, and continue towards PhD research or seek employment in yet another country. And yes, several have become professors, conducting path-breaking research and contributing towards training the next generation!



Upcoming ...



Programme coordinator: prof. dr. Niel Hens (niel.hens[at]uhasselt.be)
Administrative info: Peter Vandoren (peter.vandoren[at]uhasselt.be)