|Course Date||Onsite fees:||Live Online fee:||Register
Onsite in Nairobi, Kenya
|22/01/2024 To 02/02/2024||1,900 USD
| 1,140 USD
|08/04/2024 To 19/04/2024||1,900 USD
| 1,140 USD
|01/07/2024 To 12/07/2024||1,900 USD
| 1,140 USD
|07/10/2024 To 18/10/2024||1,900 USD
| 1,140 USD
Infectious diseases are disorders caused by organisms such as bacteria, viruses, fungi, protozoa, helminths, prions or parasites and they include SARS-CoV-2, Zika, Ebola, HIV/AIDS, swine flu, MERS CoV, ringworm, trichinosis, influenza, rabies, measles, rubella, tuberculosis and malaria among others. With the increased emergence and re-emergence of these diseases, there has been equally increased use of mathematical modelling to support relevant infectious diseases stakeholders (public health, pharmaceutical industry professionals, policy makers, infectious diseases researchers) in understanding the transmission and control of these diseases. This is possible when professionals are capable of interpreting and effectively evaluating both epidemiological data and the findings of mathematical modelling studies. This 10 days course will equip participants with knowledge on infectious diseases and hands on skills on use of R studio software in mathematical modelling of infectious diseases.
Who should attend?
Public health, medical, pharmaceutical industry professionals, policy makers, veterinary scientists, medical statisticians and infectious disease researchers and anybody who is looking forward to analysing and interpreting epidemiological data on infectious diseases and predicting the potential impact of infectious diseases control programmes.
What you will learn
By the end of the training participants will be able to:
· Understand fundamental statistical concepts
· Analyze data by applying appropriate statistical techniques
· Write a simple mathematical model that is appropriate for a specific infectious disease and related research question
· Learn R Programming
· Analyse the dynamics of the model
· Use the model to consider varying cost and intervention scenarios
· Construct valid mathematical models capturing the natural history of a given infectious disease.
· Use a calibrated model to create model projections for different intervention scenarios
· Implement a mathematical model in R, calibrating it against epidemiological data in order to estimate key model parameters
· Explain the strengths and limitations of a mathematical model in relation to given research and policy questions
Module 1: R Programming
Module 2: Understanding type of data and type of data analysis
Module 3: Test statistics
Module 4: Test of associations
Module 5: Developing infectious disease models
Module 6: Introduction to the main types of models that can be employed
Module 7: Analysis of data and applications of modelling of seroprevalence data
Module 8: Additional methods and dynamics - stochastic and network modelling, health economics and sensitivity analyses
Module 9: Applications of modelling
Module 10: Case study of data analysis and modelling of infectious disease of participants’ choice
This training can also be customized for your institution upon request. You can also have it delivered your preferred location. For further inquiries, please contact us through Mobile: +254 732 776 700 or +254 759 285 295. You can also email us on: email@example.com
Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.
The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.
Accommodation is arranged upon request. For reservations contact us through Mobile: +254 732 776 700/+254 759 285 295 or Email: firstname.lastname@example.org
Payment should be transferred to FineResults Research Limited bank before commencement of training. Send proof of payment through the email: email@example.com