1 |
Limitations in the data and evidence available to inform modelled analyses |
2 |
Limitations in the ability of models to represent complex policy scenarios, such as targeting of risk groups not represented in existing models |
3 |
Difficulty in anticipating factors that could negatively impact the outcomes of modelled policy scenarios, such as those that involve novel interventions or aggressive expansion of existing services |
4 |
Difficulty in describing the uncertainty in modelled results and how this should impact decision-making |
5 |
Differences in the modelling and estimation approaches taken by modelling teams, with the potential that different models could provide different policy advice, given the same country context and policy question |
6 |
Scarcity of human resources (worldwide and within high-burden countries) to meet the demand for modelling technical assistance, and lack of information for country TB programmes on what modelling support is available |
7 |
Differences in the level of experience, understanding or expectations of the modelling process by in-country stakeholders and international funders, and related to this, difference in the confidence placed in modelled analyses by local and international stakeholders |