12. Uncertainty and Sensitivity Analysis
Overview
This module explores the role of uncertainty and sensitivity analysis in modelling and decision-making. Participants examine how uncertainty arises from assumptions, data limitations, and model structure, and how it can influence interpretation and policy recommendations. The module emphasises the importance of transparently communicating uncertainty to support informed and responsible decision-making.
By the end of this module, participants should be able to:
Explain what types of uncertainty exist in modelling
Understand how sensitivity analysis is used to assess the robustness of results
Demonstrate how uncertainty can be communicated effectively to non-technical audiences
Parameter uncertainty
Structural uncertainty
Data limitations and variability
Sensitivity analysis
Communicating confidence and uncertainty
Delivery Plan
This module consists of a teaching session (1.5 hour), including case studies, followed by an interactive exercise and discussion.
| Topic | Description | Duration | Format |
| Introduction to Uncertainty | Why uncertainty exists in all models Different sources and types of uncertainty |
45 min | Presentation |
| Sensitivity Analysis | Understanding how assumptions affect outputs Examples of sensitivity and uncertainty in malaria models |
45 min | Presentation and discussion |
| Interactive Exercise | Participants review outputs under different assumptions and conduct basic sensitivity analysis Explore how changing parameters influences conclusions |
90-120 min | Small group break out exercise |
| Communicating Uncertainty | Avoiding overconfidence in communication Presenting uncertainty clearly and constructively |
30 min | Group discussion (plenary) |
| Reflection and Wrap-Up | Key lessons for interpreting and communicating uncertainty Where to next |
10 min | Discussion |
Practical Exercise
Exercise Title: SPPF - Exploring Uncertainty and Sensivity Analysis in Malaria Modelling
SPPF is an interactive malaria modelling tool for a single patch (one geographic/age group) for P. falciparum malaria.
Instructions (Part A)
Using the interactive SPPF modelling tool, participants:
Run a baseline and scenarios of your choice
Explore the results
Run the sensitivity analysis
Identify which assumptions most influence outcomes
Discuss implications for policy recommendations
Groups compare approaches and interpretation.
Optional Extension (Part B)
If there is time, an extension of the group exercise is to consider the following hypothetical situations:
Groups A & B: Recent global instability in health financing has led to cautious donor spending. While the SMC funding is secured now, there remains uncertainty in the costs of delivery (enrolling participants into the SMC programme) and the drug cost. Explore the impact of cost uncertainty on the implementation of your SMC intervention.
Groups C & D: Artemisinin resistance is a current threat. The current baseline settings assume that 5% of treatments are failing due to artemisinin resistance. Resistance will have an effect on the impact of your SMC intervention. Redefine the baseline and consider different background resistance scenarios to estimate the impact that increased resistance after 2020 has on your intervention.
Facilitator Guidance
Reinforce that uncertainty does not make modelling “wrong” or unusable
Encourage discussion on balancing confidence and caution
Use practical examples to demonstrate sensitivity analysis
Focus on implications for decision-making and communication
Materials and Resources
SPPF Tool access
Facilitator presentation slides