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The core training program will cover various topics and will be adapted to each implementation to address specific health questions, define case studies and projects depending on the available data of the host country. The training program will be prepared jointly with a scientific committee and the lecturers. Hereafter are the main topics associated with time load for the first school that should be detailed as a curriculum to meet the training objectives.
Mathematics for modelers I
Python/R for modelers I
Statistics and statistic modeling for decision making in health
Health economics
Mathematical modeling of infectious diseases
Introduction to agent and spatial modeling
ML and AI for Health
Modeling for impact: linking modeling with policy, advocacy and communication.
Guided Team project
Ethics and law
Mathematics and Python for modelING
Mathematics and Python for modelING
Prof. Slimane Ben Miled- Heger Arfaoui (PhD) (9h)
Familiarize participants with the ways of solving complicated mathematical problems analytically and numerically using Python and R softwares and prepare them to work in a computational area.
Statistics For decision making in health
Statistics For decision making in health
R- for modeler
Maryam Diarra (PhD), Jules Tchatchueng (PhD),
Cheikh Talla (PhD) and
Khouloud Talmoudi (PhD) (12h)
Prepares participants to conduct statistical studies the field of public health and decision making
Introduction to Health economics
Introduction to Health economics
Nadia Raissi (Prof.) and Santiago Hasdeu (MD) (6h)
Exposes participants to health economics in order to develop an understanding of economic principles as applied to health and health care.
Ethics and gender
Ethics and gender
Fadwa Bouguerra (3h)
Develop proficiency in utilizing modeling techniques as a powerful tool for informing, shaping, and influencing policy decisions, advocacy efforts, and effective communication strategies.
Agent and spatial modeling
Agent and spatial modeling
Dorra Louati (PhD), Nicolas Marilleau (HdR) and Cyrine Chenaoui (11h30)
Explores how geographic information and Agent based modeling can be used to promote and support the construction and simulation of dynamic models of human and environmental systems.
ML and AI for Health
ML and AI for Health
Nesrine Ben Yahia (Prof), Anas Lahdhiri (6h)
Familiarizes participants with concepts and techniques of Artificial Intelligence and Machine Learning and to prepare them to be knowledgeable users of these techniques capable of using them to solve health care problems while being aware of their limitations.
Introduction to Mathematical modeling of infectious diseases
Introduction to Mathematical modeling of infectious diseases
Mutono Nyamai (PhD), Amira Bouhali (9h)
Trains participants to study and develop computational techniques and tools for modeling, simulating, predicting, forecasting, surveilling, mitigating, and visualizing the spread of disease.
Mathematical modeling of infectious diseases in practiCe
Mathematical modeling of infectious diseases in practiCe
Slimane Ben Miled (Prof), Amira Kebir (Ph.D.) and Zeineb Ouinissi (6h)
Trains participants to study and develop computational techniques and tools for modeling, simulating, predicting, forecasting, surveilling, mitigating, and visualizing the spread of disease.
Guided Team project
Guided Team project
Prof. Slimane Ben Miled & Ph.D. Amira Kebir (3h)
Prepares future health modelers to work within a multidisciplinary team, to formulate projects and to implement its functionalities with respect to its requirements.
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