Ebola Modelling Course for National Public Health Preparedness and Response Decision-Making

Course overview

The current outbreak of Ebola Virus Disease (EVD) caused by the Bundibugyo virus species in the Democratic Republic of Congo highlights the continued threat of emerging and re-emerging infectious diseases in the region and the need for strengthened preparedness across neighbouring countries.

As public health institutions increasingly rely on data and evidence to guide outbreak response, mathematical and epidemiological modelling has become an important tool for understanding transmission dynamics, forecasting outbreak trajectories, assessing intervention strategies, and supporting decision-making.

To effectively utilize modelling evidence, public health professionals require the capacity to interpret model outputs, understand their underlying assumptions and uncertainties, and translate insights into action. In response to this need, the Centre for Epidemiological Modelling and Analysis is organizing a two-day Ebola Modelling Course for the Kenya National Public Health Institute (KNPHI) staff.

Aim

To strengthen KNPHI's capacity to understand, interpret, and effectively utilize epidemiological modelling outputs during Ebola preparedness and response activities. 

Specifically, participants will learn on models answering three critical questions:

i) Pre-importation phase: What is Kenya’s risk of Ebola importation, and what surveillance and prevention measures does evidence support?

ii) Post-detection (if/when): If a case is confirmed, how many cases might we see? How quickly? What healthcare system surge is needed?

iii) Policy trade-offs: What are the epidemiological and economic costs of different interventions (quarantine, movement restrictions, vaccination)? Which should we prioritize?

Learning Objectives

By the end of the course, participants will be able to:

1. Understand key concepts used in infectious disease modelling and their use in outbreak preparedness and response
2. Interpret Ebola transmission models and estimate Kenya’s case risk under different scenarios
3. Identify assumptions, limitations, and data gaps that affect model reliability
4. Design and linking models worlds (idealized assumptions) with data worlds (messy, incomplete surveillance).
5. Understand what models can do (forecast if assumptions hold), and cannot do (predict exact timing, account for behaviour change).
6. Extracting insights from models for pre-importation policies (from the risk models) and rapid response plans (if cases are detected)
7. Engage effectively with modelling teams by asking critical questions and communicating evidence needs.

Target Participants

The training is intended for approximately 25 to 30 participants from KNPHI. These may include  epidemiologists, surveillance officers, emergency operations centre staff, risk assessment personnel, programme managers, laboratory representatives, technical advisors and decision-makers involved in the Ebola outbreak preparedness.

Expected Outcomes

Following the training:

• Participants will have improved understanding of infectious disease modelling concepts.
• KNPHI staff will be better equipped to interpret modelling outputs during outbreaks.
• Participants will be able to critically assess modelling assumptions and uncertainty.
• Enhanced collaboration between KNPHI and modelling teams during preparedness and response activities.
• Strengthened institutional capacity to incorporate modelling evidence into public health decision-making