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Epidemiology crash course poster

Introduction to Concepts in Epidemiology

 

The University of Nairobi Center for Epidemiological Modelling and Analysis is offering an introductory in-person training on Concepts in Epidemiology.

 

Venue: University of Nairobi

Date: 25th - 29th November 2024

Mode of Training Session: In-Person

Application Deadline: 8th November 2024

Pre-requisite

Participants are required to bring their own laptops for the hands-on exercises.

Suggested readings will be shared ahead of the trainings.

There is a short deadline for applications, which closes on 8th November 2024

Successful applicants shall be notified by 12th November 2024

 

Apply Here

 

This training will focus on:

  • Understanding the fundamental principles of epidemiology as applied to public health
    and veterinary science
  • Learning how to apply appropriate epidemiological study designs and measures to
    investigate disease-related events in a population 
  • Demonstrating how to critically analyze epidemiological data and present the results of
    statistical analyses with appropriate inferences.
  • Learning how to appropriately evaluate the strengths and limitations of epidemiological
    studies, including bias, confounding, and effect modification
  • Exploring how to utilize epidemiological principles to design and conduct studies,
    interpret diagnostic tests performance, and apply findings to inform decision-making

 

Who is this course for?

This training is designed for individuals involved in epidemiologic research, public health, or working in global health in their roles as:

  • Public health/healthcare professionals from hospitals, ministry of health, ministry
    of livestock and fisheries
  •  Project managers and coordinators involved in disease control and prevention
    programs.
  • Researchers, postgraduate students in epidemiology, medicine/pharmacology,
    public health/health policy, health system and services, veterinary medicine,
    veterinary public health or related fields